HOME top logo CONTACT US ENGLISH

회원로그인 login

로그인영역

Refereed Journals

HOME :: 연구 활동 > 발표 논문

  • International
  • Ryu, D., Lim, C., and Kim, K., "Development of a service blueprint for the online-to-offline integration in service," Journal of Retailing and Consumer Services, Accepted for publication.

    Abstract

    Online-to-offline (O2O) integration refers to the incorporation of separate online and offline service processes into a single service delivery. Advances in mobile devices and information and communication technology enable the O2Ointegration, which has been applied to many services. This study proposes a new service blueprint, called the O2O Service Blueprint (O2O SB), which is specialized in visualizing and analyzing the service processes of the O2O integration. A comprehensive literature review and text mining analysis are conducted on massive quantities of literature, articles, and application introductions to understand characteristics of the O2O integration and extract keywords relevant to the O2O integration. Comparisons of the O2O SB with the conventional service blueprint and Information Service Blueprint validate that our proposal can address the limitations of existing service blueprints. An evaluation through expert interviews confirms the completeness, utility, and versatility of the O2O SB. The proposed O2O SB presents a complete picture of the entire service process, whether online or offline. This SB helps users systematically understand the processes and formulate strategies for service improvement.
  • Lee, D., Yang, J., Lee, C., and Kim, K., "A data-driven approach to selection of critical process steps in the semiconductor manufacturing process considering missing and imbalanced data," Journal of Manufacturing Systems, Vol. 52, 146-156, 2019.

    Abstract

    Semiconductor wafers are fabricated through sequential process steps. Some process steps have a strong relationship with wafer yield, and these are called critical process steps. Because wafer yield is a key performance index in wafer fabrication, the critical process steps should be carefully selected and managed. This paper proposes a systematic and data-driven approach for identifying the critical process steps. The proposed method considers troublesome properties of the data from the process steps such as imbalanced data, missing values, and random sampling. As a case study, we analyzed hypothetical operational data and confirmed that the proposed method works well.
  • Lee, D., Lee, C., Choi, S., and Kim, K., "A method for wafer assignment in semiconductor wafer fabrication considering both quality and productivity perspectives," Journal of Manufacturing Systems, Vol. 52, 23-31, 2019.

    Abstract

    In the semiconductor wafer fabrication process, wafers go through a series of sequential process steps. Typically, each process step has several machines, and the wafers are assigned to one whenever they enter the process step. When assigning wafers to machines, it is important to consider both the quality and productivity perspectives. Major semiconductor companies in Korea have recently implemented a wafer assignment system to improve wafer yield, a critical measure for semiconductor quality. This system, however, does not consider the productivity perspective. This paper presents a systematic method for assigning wafers to maximize the wafer yield while satisfying a predetermined target level of productivity. A simple hypothetical example is presented to illustrate the method.
  • Park, S., Shin, W., and Kim, K., "Assessing a social responsibility model for sustainable company growth in the fourth industrial revolution,"International Journal of Quality and Service Sciences, Vol.11, No. 3, 334-345, 2019.

    Abstract

    Purpose: The Fourth Industrial Revolution (4th IR) affects the mode of company management. In this paper, a revised social responsibility (SR) model is presented as an evaluation tool for corporate social responsibility (CSR) performance for sustainable organizational growth in the era of the 4th IR.

    Design/methodology/approach: To develop an SR model that can be used well in the era of the 4th IR, the key references are “ISO 26000: Guidance on Social Responsibility” and “the Global Reporting Initiative (GRI) Guidelines.” For ISO 26000 and the GRI guidelines, see the homepages in the References section. On the basis of these guidelines, a new SR model for sustainable development in the 4th IR is developed in this paper.

    Findings: For a new SR model in the 4th IR, the concepts of management quality, quality responsibility, creating shared value, social value and open data and open quality management (QM) are incorporated into the existing International Organization for Standardization (ISO) 26000 evaluation criteria.

    Originality/value: The 4th IR is changing the concepts of both QM and SR. To the best of the authors’ knowledge, the new concept of SR is yet to be discussed extensively. In this paper, a new SR model is suggested to reflect the characteristics of the 4th IR.
  • Lim, C., Kim, M., Kim, K., Kim, K., and Paul, M., "Customer Process Management: A Framework for Using Customer-related Data to Create Customer Value,"Journal of Service Management, Vol. 30, No. 1, 105-131, 2019.

    Abstract

    Purpose: The proliferation of customer-related data provides companies with numerous service opportunities to create customer value. This study develops a framework to use this data to provide services.

    Design/methodology/approach: This study conducted four action research projects on the use of customer-related data for service design with industry and government. Based on these projects, a practical framework was designed, applied, and validated, and was further refined by analyzing relevant service cases and incorporating the service and operations management literature.

    Findings: The proposed customer process management (CPM) framework suggests steps a service provider can take when providing information to its customers to improve their processes and create more value-in-use by using data related to their processes. The applicability of this framework is illustrated using real examples from the action research projects and relevant literature.

    Originality/value: “Using data to advance service” is a critical and timely research topic in the service literature. This study develops an original, specific framework for a company’s use of customer-related data to advance its services and create customer value. Moreover, the four projects with industry and government are early CPM case studies with real data.
  • Lim, C., Kim, K., Kim, M., and Kim, K., "Multi-Factor Service Design: Identification and Consideration of Multiple Factors of the Service in its Design Process,"Service Business, Vol. 13, No. 1, 51-74, 2019.

    Abstract

    Service design is a multidisciplinary area that helps innovate services by bringing new ideas to customers through a design-thinking approach. Services are affected by multiple factors, which should be considered in designing services. In this paper, we propose the multi-factor service design (MFSD) method, which helps consider the multi-factor nature of service in the service design process. The MFSD method has been developed through and used in five service design studies with industry and government. The method addresses the multi-factor nature of service for systematic service design by providing the following guidelines: (1) identify key factors that affect the customer value creation of the service in question (in short, value creation factors), (2) define the design space of the service based on the value creation factors, and (3) design services and represent them based on the factors. We provide real stories and examples from the five service design studies to illustrate the MFSD method and demonstrate its utility. This study will contribute to the design of modern complex services that are affected by varied factors.
  • Kim, K., Kim, K., Lee, D., and Kim, M., "Identification of Critical Quality Dimensions for Continuance Intention in mHealth Services: Case Study of Onecare Service," International Journal of Information Management, Vol. 46, 187-197, 2019.

    Abstract

    Mobile health (mHealth) services support the continuous health-related monitoring, feedback, and behavior modification of individuals and populations through the use of personal mobile communication devices. Poor service quality is a major reason why many users have discontinued using mHealth services. However, only a few studies have identified the critical quality components for continuance intention. The current study aims to identify the crucial quality dimensions for users’ continuance intention in an mHealth service called Onecare. This service provides various forms of support for the day-to-day health behavior monitoring of college students by utilizing daily behavior data. In this research, five major quality dimensions of mHealth services, namely, content quality, engagement, reliability, usability, and privacy, were derived from existing studies. The effect of each quality dimension on continuance intention was estimated by analyzing the survey responses of 191 Onecare service users. The quality dimension with the most considerable effect on continuance intention was determined to be engagement followed by content quality and reliability. By contrast, the effects of usability and privacy on continuance intention were insignificant. Furthermore, this study found that the optimal quality management strategy can change depending on the objective, i.e., to increase continuance intention or satisfaction. These results will help mHealth service managers allocate their limited resources to effectively and efficiently improve continuance intention. Future research is required to verify if the findings of this study are generalizable to any population because the sample used in this work was specific to Korean college students.
  • Kim, K., Lim, C. Kim, K., Kang, S., You, H., Jun, C., Shin, S., Choo, D., and Kim, J., "Development of Service Concepts that Utilize Health-related Data: A Case Study with the National Health Insurance Service of South Korea,"IISE Transactions on Healthcare Systems Engineering, Vol. 8, No. 4, 237-249, 2018.

    Abstract

    The South Korean government retains valuable health-related data of nearly all citizens. This data set includes insurance data, diagnosis history data, treatment history data, and medical examination data. This paper presents a case study with the National Health Insurance Service of South Korean government to develop service concepts that utilize such health-related data. A service concept indicates what to offer to customers and how to offer it. In the case study, 138 service ideas that utilize health-related data were generated based on literature and focus group interviews with 14 experts. The ideas were evaluated by 20 experts via focus group interviews. Eight new service concepts were designed based on the ideas, and then evaluated by 19 experts and 612 citizens. The service concepts are expected to improve the national healthcare system of South Korea. This paper also presents key dimensions of health-related data utilization services and issues in developing such services, which were identified based on the case study. The original contribution of this study is the development of health-related data utilization service concepts at a national scale. This work will serve as a foundational reference for future research aimed at developing such services.
  • Heo, J., Lim, C., and Kim, K., "A Customer-oriented Model of Product-Service System Lifecycle," International Journal of Product Lifecycle Management, Vol.11, No. 4, 350-367, 2018.

    Abstract

    A product-service system (PSS) is an integrated bundle of products and services, which aims at creating customer utility and enhancing manufacturers’ competitiveness. Given that products and services are integrated over a specific cycle, PSS lifecycle has become a key notion in PSS research. However, most studies focus on PSS lifecycle from a provider perspective although the essence of PSS is to create customer utility. The current work proposes a customer-oriented model of PSS lifecycle as a solid basis for analyzing PSS from a customer perspective. A two-phase procedure was conducted to develop the model. In phase 1, customer activities in 118 PSS cases were analyzed to identify three specific types of PSS lifecycle (product-, use-, and result-oriented PSS). In phase 2, one general type of PSS lifecycle was analyzed by analyzing three specific types. In addition, their usefulness in PSS research was shown through an example on car-related PSS cases. The proposed model comprises one general and three specific types of PSS lifecycle. Four stages (“plan,” “decide,” “solve,” and “end”) were formed in the general type while seven stages were formed for product-oriented PSS, six for use-oriented PSS, and five for result-oriented PSS. The proposed model can be utilized to supplement the existing studies to consider the PSS mechanism from a customer perspective. A concrete notion of PSS lifecycle from a customer perspective may contribute to customer-oriented PSS innovations.
  • Lim, C., Kim, K., and Maglio, P., "Smart Cities with Big Data: Reference Models, Challenges, and Considerations," Cities, Vol. 82, No. 1, 86-99, 2018.

    Abstract

    Cities worldwide are attempting to transform themselves into smart cities. Recent cases and studies show that a key factor in this transformation is the use of urban big data from stakeholders and physical objects in cities. However, the knowledge and framework for data use for smart cities remain relatively unknown. This paper reports findings from an analysis of various use cases of big data in cities worldwide and the authors' four projects with government organizations toward developing smart cities. Specifically, this paper classifies the urban data use cases into four reference models and identifies six challenges in transforming data into information for smart cities. Furthermore, building upon the relevant literature, this paper proposes five considerations for addressing the challenges in implementing the reference models in real-world applications. The reference models, challenges, and considerations collectively form a framework for data use for smart cities. This paper will contribute to urban planning and policy development in the modern data-rich economy.
  • Kim, K., Kim, K., Lim, C., and Heo, J., "Development of a Lifelogs-based Daily Wellness Score to Advance a Smart Wellness Service,"Service Science, Vol. 10, No. 4, 408-422, 2018.

    Abstract

    Smart wellness services collect various types of lifelogs such as walking steps and sleep duration via smart devices. However, most of the existing smart wellness services focus on displaying each individual lifelog to users. Therefore, they have limitations on supporting overall and easy understanding of various lifelogs. A lifelogs-based daily wellness score (LDWS) is a useful tool to resolve such limitations. LDWS combines the lifelogs into a score to represent an overall level of daily health behaviors, thus, supporting overall and easy health behavior monitoring of users. This research developed LDWS as part of developing a smart wellness service for college students (SWSCS) in collaboration with an IT company. Lifelogs of 41 college students were collected through a four-week pilot run of SWSCS and were subsequently fitted to a random effects model. Based on the model estimates, LDWS was determined by linearly aggregating seven behavior variables. Utility of the developed LDWS was validated through a second pilot run of SWSCS. This paper also discusses the potential use of LDWS for SWSCS and the factors to be considered for developing a lifelogs-based wellness score for a smart wellness service. This research would contribute to advancing smart wellness services with lifelogs.
  • Lim, C. and Kim, K., "Experience Design Board: A Tool for Visualizing and Designing Experience-centric Service Delivery Processes,"Journal of Retailing and Consumer Services, Vol. 45, No. 1, 142-151, 2018.

    Abstract

    Experience-centric service (ExS) is a type of service through which customers experience emotionally appealing events and activities that result in distinctive memory. The literature argues that ExS design should be a research priority in this experience economy, yet little is known on how to articulate ExSs in their design. This paper proposes a tool called Experience Design Board for visualizing an ExS delivery process as a basis for its analysis and design. The tool is a matrix-shaped board where the key factors of experience creation in ExS (namely, servicescape, frontstage employees, other customers, backstage employees, and technology support systems) are represented in rows, and the customer experience phases are placed in columns. The tool is useful in analyzing and designing how the key factors of ExS create customer experience. The tool integrates several work streams within the evolving ExS literature into its structure and is generic enough to accommodate various ExSs in physical and digital experience contexts. By visualizing an ExS delivery process from beginning to end, the designer can obtain a systematic understanding of the essential attributes of ExS and can use it for an effective design. This tool would serve as a basis for service design in this experience economy.
  • Kim, M., Lim, C., and Kim, K., "A Data-driven Approach to Designing New Services for Vehicle Operations Management,"International Journal of Industrial Engineering: Theory, Applications and Practice, Vol.25, No. 5, 2018.

    Abstract

    Various types and massive amounts of data are collected in the automotive industry. Such data proliferation facilitates and improves the design of services for vehicle operations management (VOM). A VOM service is a service that helps drivers drive safely, conveniently, and pleasurably with the use of VOM-related data. Despite the applicability of big data to VOM service design, few efforts have been made to establish a big data-based design process for VOM services. To fill the research gap, this study proposes an approach to analyzing and utilizing VOM-related data for designing VOM services. The proposed approach aids service designers in designing VOM services by using VOM-related data. A case study on the design of an eco-driving service, a popular VOM service, is presented to demonstrate the feasibility and effectiveness of the approach. The proposed approach could facilitate the design of VOM services and provide a foundation for data-driven service innovations.
  • Lee, J., Kwon, R., Kim, H., Kang, S., Kim, K., and Jun. C., "A Data-Driven Procedure of Providing a Health Promotion Program for Hypertension Prevention,"Service Science, Vol. 10, No. 3, 289-301, 2018.

    Abstract

    We propose a two-step procedure based on data analytics to help service providers to efficiently and effectively implement a health promotion program to prevent hypertension. First, we developed a prediction model to identify people who are at risk for developing hypertension. Then, to eliminate specific risk factors for each of these individuals, we proposed four methods to create an index that represents the importance of each intervention program, which is a subprogram of the health promotion program. This index can be used to recommend appropriate intervention programs for each individual. We used the national sample cohort database of South Korea to offer a case study of the implementation of the proposed procedure. The constructed prediction model using logistic regression has adequate accuracy, and the proposed index that uses different methods has similar results to those of a doctor. This two-step procedure by automatic modeling based on data will be useful to save human resources and to provide informative and personalized results based on individual healthcare records.
  • Lim, C. and Maglio, P., "Data-Driven Understanding of Smart Service Systems Through Text Mining,"Service Science, Vol. 10, No. 2, 154-180, 2018.

    Abstract

    Smart service systems are everywhere, in homes and in the transportation, energy, and healthcare sectors. However, such systems have yet to be fully understood in the literature. Given the widespread applications of and research on smart service systems, we used text mining to develop a unified understanding of such systems in a data-driven way. Specifically, we used a combination of metrics and machine learning algorithms to preprocess and analyze text data related to smart service systems, including text from the scientific literature and news articles. By analyzing 5,378 scientific articles and 1,234 news articles, we identify important keywords, 16 research topics, 4 technology factors, and 13 application areas. We define “smart service system” based on the analytics results. Furthermore, we discuss the theoretical and methodological implications of our work, such as the 5Cs (connection, collection, computation, and communications for co-creation) of smart service systems and the text mining approach to understand service research topics. We believe this work, which aims to establish common ground for understanding these systems across multiple disciplinary perspectives, will encourage further research and development of modern service systems.
  • Lim, C., Kim, K., Kim, M., Heo, J., Kim, K., and Maglio, P., "From Data to Value: A Nine-factor Framework for Data-based Value Creation in Information-intensive Services,"International Journal of Information Management, Vol. 39, No. 1, 121-135, 2018.

    Abstract

    Service is a key context for the use of information technology (IT) as IT digitizes the information interactions within service and facilitates value creation, thereby contributing to service innovation. The recent proliferation of (big) data provides numerous opportunities for information-intensive services (IISs), in which information interactions have the most effect on value creation. In the modern data-rich economy, understanding mechanisms and related factors of the data-based value creation in IISs is essential in improving such services with IT. This study identifies nine key factors that characterize the data-based value creation: (1) data source, (2) data collection, (3) data, (4) data analysis, (5) information on the data source, (6) information delivery, (7) customer (information user), (8) value in information use, and (9) provider network. These nine factors were identified and defined on the basis of our action research through six projects with industry and government that used specific datasets to design new IISs as well as on the basis of analysis of data use in 149 IIS cases. This paper demonstrates the utility of the nine factors in describing, analyzing, and designing the full spectrum from data collection to value creation in IISs. Our main contribution is to provide a simple yet comprehensive and empirically tested basis for the use and management of data to facilitate service value creation in this data-rich economy.
  • Kim, M., Lim, C., Lee, C., Kim, K., Park, Y., and Choi, S., "Approach to Service Design Based on Customer Behavior Data: A Case Study on Eco-driving Service Design Using Bus Drivers,"Service Business, Vol. 12, No. 1, 203-227, 2018.

    Abstract

    Various types and massive amounts of customer behavior data are collected in various industries, such as transportation, healthcare, hospitality, and logistics. The use of customer behavior data can improve the design activities of service firms. Despite the applicability of customer behavior data to service design, only a few studies have examined an approach to utilize customer behavior data in service design. This study proposes an approach for designing services with customer behavior data. The approach is based on a case study on eco-driving service design with the behavior data of bus drivers. This study extends the research on service design by demonstrating how customer behavior data are utilized for service design and assisting service designers in designing services with customer behavior data.
  • Lee, D., Yang, J., and Kim, K., "Dual-Response Optimization Using a Patient Rule Induction Method,"Quality Engineering, Vol. 30, No.4, 610-620, 2018.

    Abstract

    A dual-response surface optimization approach assumes that response surface models of the mean and standard deviation of a response are fitted well to experimental data. However, it is often difficult to satisfy this assumption when dealing with a large volume of operational data from a manufacturing line. The proposed method attempts to optimize the mean and standard deviation of the response without building response surface models. Instead, it searches for an optimal setting of input variables directly from operational data by using a patient rule induction method. The proposed approach is illustrated with a step-by-step procedure for an example case.
  • Lim, C., Kim, M., Kim, K., Kim, K., and Maglio, P., "Using Data to Advance Service: Managerial Issues and Theoretical Implications from Action Research,"Journal of Service Theory and Practice, Vol. 28, No. 1, 99-128, 2018.

    Abstract

    The proliferation of (big) data provides numerous opportunities for service advances in practice, yet research on using data to advance service is at a nascent stage in the literature. Many studies have discussed phenomenological benefits of data to service. However, limited research describes managerial issues behind such benefits, although a holistic understanding of the issues is essential in using data to advance service in practice and provides a basis for future research. Our objective is to address this research gap. Design/methodology/approach: “Using data to advance service” is about change in organizations. Thus, this study uses action research methods of creating real change in organizations together with practitioners, thereby adding to scientific knowledge about practice. The authors participated in five service design projects with industry and government that used different datasets to design new services. Findings: Drawing on lessons learned from the five projects, this study identifies empirically eleven managerial issues that should be considered in data-use for advancing service. In addition, by integrating the issues and relevant literature, this study offers theoretical implications for future research. Originality/value: “Using data to advance service” is a research topic that emerged originally from practice. Action research or case studies on this topic are valuable in understanding practice and in identifying research priorities by discovering the gap between theory and practice. This study used action research over many years to observe real-world challenges and to make academic research relevant to the challenges. We believe our empirical findings will help improve service practices of data-use and stimulate future research.
  • Lee, D., Jeong, I., and Kim, K., "A desirability function method for optimizing mean and variability of multiple responses using a posterior preference articulation approach,"Quality and Reliability Engineering International, Vol. 34, No. 3, 360-376, 2018.

    Abstract

    A desirability function approach has been widely used in Multi-Response Optimization (MRO) due to its simplicity. Most of the existing desirability function-based methods assume that the variability of the response variables is stable; thus, they focus mainly on the optimization of the mean of multiple responses. However, this stable variability assumption often does not apply in practical situations; thus, the quality of the product or process can be severely degraded due to the high variability of multiple responses. In this regard, we propose a new desirability function method to simultaneously optimize both the mean and variability of multiple responses. In particular, the proposed method uses a posterior preference articulation approach, which has an advantage in investigating tradeoffs between the mean and variability of multiple responses. It is expected that process engineers can use this method to better understand the tradeoffs, thereby obtaining a satisfactory compromise solution.
  • Kim, K., Kim, H., Yim, J., Heo, J., Kim, M., Shin, S., and Ahn, H., "Evaluation of Smartphone User Experience: Identification of Key Items and Their Relationships,"International Journal of Mobile Communications, Vol. 16, No. 2, 167-189, 2018.

    Abstract

    User experience (UX) refers to the comprehensive experience of a user when interacting with a product. UX plays an essential role in enhancing the value of a product in the current marketplace. Compared with a feature phone, a smartphone enables users to significantly extend the usage of the device. Given the impressive market growth of the smartphone, evaluating its UX has become important in its development process. However, studies on the evaluation of smartphone UX are limited. Thus, we conducted a study on smartphone UX from the perspective of UX evaluation. At first, a total of 329 evaluation items for smartphone UX were identified based on literature review and user study, and they were categorized as product, context, and emotion items. Then, to utilize the items in the three categories, we proposed a two-phase procedure for UX evaluation consisting of identification of key items (Phase 1) and identification of causal relationships among the key items (Phase 2). As a case study, seven key contexts were identified and the relationships of key items were statistically identified based on 461 user data. The results of this study can help practitioners evaluate their smartphone UX in a systematic manner.
  • Heo, J., Lim, C., and Kim, K., "Scales for Measuring Mobile Service Quality (M-SQ): A Literature Review and Identification of Key Dimensions,"International Journal of Services and Operations Management, Vol. 27, No. 4, 524-548, 2017.

    Abstract

    Mobile service quality (m-SQ) is vital to manage the competitiveness of a company in the mobile business market. Existing studies on m-SQ share key characteristics of m-service in general, such as mobility and context awareness. A set of common m-SQ dimensions that reflects such key characteristics would serve as the theoretical backbone of m-SQ. This research aims to conduct a comprehensive review of existing studies on m-SQ scales and identify key dimensions of m-SQ to understand the essence of m-SQ scales. A total of 45 existing studies on m-SQ scales were reviewed and seven key dimensions of m-SQ scales were identified. This study is expected to serve as a solid knowledge base for conducting new investigations on m-SQ scale development as well as help practitioners utilize m-SQ scales.
  • Shin, W., Lee, H., Kim, K., and Chung, B., "Developing a quality prioritization procedure for IPTV service,"Service Business, Vol. 11, No. 2, 427-449, 2017.

    Abstract

    This study developed a procedure to determine the quality priorities of the internet protocol television (IPTV) service. First, a set of key elements of IPTV service quality was developed based on a literature review and a focus group interview. Second, analytic hierarchy process and the Kano model were applied to identify the requirements of experts and customers, respectively. The experts measured the importance and difficulty of management, whereas the customers measured the satisfaction level and importance of each quality element. Third, quality priorities were calculated through the entropy principle and scenario-based analysis. The proposed procedure is illustrated with a case study of a telecommunications company in Korea.
  • Heo, J. and Kim, K., "Development of a Scale to Measure the Quality of Mobile Location-Based Services,"Service Business, Vol. 11, No. 1, 141-159, 2017.

    Abstract

    Mobile location-based service (m-LBS) presents attractive business opportunities for various companies. Recent improvements of technologies have resulted in a dramatic growth of m-LBSs. However, development of scales for evaluating the m-LBS quality has scarcely been addressed. This study aims to develop a new scale applicable to evaluating m-LBS quality. The scale was qualitatively designed at first, and the designed scale was assessed with a total number of 281 responded survey data. As a result, a m-LBS quality scale was developed, which consists of 9 quality dimensions and 29 measurement items. The distinctive characteristic of m-LBS is captured by a newly defined dimension called "localization" and its three measurement items (namely, organization, update, and inclusiveness). The proposed scale was shown to be statistically reliable and valid. The results of this study would significantly contribute to providing a valid scale for use in measuring the m-LBS quality.
  • He Y., He Z., Lee, D., Kim, K., Zhang L., and Yang, X., "Robust Fuzzy Programming Method for MRO Problems Considering Location Effect, Dispersion Effect and Model Uncertainty,"Computers & Industrial Engineering, Vol. 105, No. 1, 76-83, 2017.

    Abstract

    In this paper, considering the uncertainty associated with the fitted response surface models and the satisfaction degrees of the response values with respect to the given targets, we construct the robust membership functions of the responses in three cases and explain their practical meanings. We translate the feasible regions of multiple responses optimization (MRO) problems into ∂-level sets and incorporate the model uncertainty with the confidence intervals simultaneously to ensure the robustness of the feasible regions. Then we develop the robust fuzzy programming (RFP ) approach to solve the multiple responses optimization (MRO) problems. The key advantage of the presented method is that it takes account of the location effect, dispersion effect and model uncertainty of the multiple responses simultaneously and thus can ensure the robustness of the solution. An example from literatures is illustrated to show the practicality and effectiveness of the proposed algorithm. Finally some comparisons and discussions are given to further illustrate the developed approach.
  • Kim, K., Lim, C., Heo, J., Lee, D., Hong, Y., and Park, K., "An evaluation scheme for product?service system models: development of evaluation criteria and case studies,"Service Business, Vol. 10, No. 3, 507-530, 2016.

    Abstract

    A product?service system (PSS) integrates products and services to ful?ll customer needs and create sustainability. PSS evaluation requires the use of diverse criteria because PSSs are complex systems with multiple stakeholders and perspectives. This paper proposes an evaluation scheme for PSS models that con-sists of a set of 94 evaluation criteria and an evaluation procedure. The proposed set of criteria encompasses both provider and customer perspectives, all of the 3P (pro?tability, planet, and people) values and various PSS lifecycle phases, whereas existing studies only partially cover these aspects of PSS. The proposed set serves as an evaluation criterion repository, and users can easily identify the criteria relevant to the evaluation targets. Using the proposed set is more ef?cient than starting from scratch. The proposed evaluation scheme can be used either to compare different PSS models or to evaluate a single model. Case studies show that the proposed scheme can suf?ciently evaluate both existing and newly launched PSS models as well as models under development. The proposed scheme is expected to serve as an ef?cient and effective aid for practitioners in PSS development.
  • Seo, J., Lee, D., Lee, K., Kim, K., and Kim, K., "Optimizing a blend of a mixture slurry in chemical mechanical planarization for advanced semiconductor manufacturing using a posterior preference articulation approach to dual response surface optimization,"Applied Stochastic Models in Business and Industry, Vol. 32, No. 5, 648-659, 2016.

    Abstract

    Semiconductors are fabricated through unit processes including photolithography, etching, diffusion, ion implantation, deposition, and planarization processes. Chemical mechanical planarization (CMP), which is essential in advanced semiconductor manufacturing processes, aims to achieve high planarity across the wafer surface. This paper presents a case study in which the optimal blend of mixture slurry was obtained to improve the two response variables (material loss and roughness) at the same time. The mixture slurry consists of several pure slurries; when all of the abrasive particles within the slurry are of the same size, the slurry is referred to as a pure slurry. The optimal blend was obtained by applying a multi-response surface optimization method. In particular, the recently developed posterior approach to dual response surface optimization was employed, which allows the CMP process engineer to investigate trade-offs between the two response variables. The two responses were better with the obtained blend than the existing blend.
  • Lim, C., Kim, M., Heo, J., and Kim, K., "Design of informatics-based services in manufacturing industries: case studies using large vehicle-related databases,"Journal of Intelligent Manufacturing, Vol. 29, No. 3, 497-508, 2015.

    Abstract

    Numerous companies in manufacturing industries have “servitized” their value propositions to address issues on product commoditization and sustainability. A key component of servitization is informatics, which transforms product and customer data into information for customers. In this study, informatics-based service is defined as a type of service wherein informatics is crucial to customer value creation. Despite the importance of this concept, studies on the design of informatics-based services in manufacturing industries are rare. This paper reports on two case studies on such designs. Informatics-based services have been designed for a major Korean automobile manufacturer and the Korea Transportation Safety Authority (TS) based on their large vehicle-related databases. The first case study with the automobile manufacturer aims to design vehicle operations and health management services for passenger vehicle drivers while the second study with TS focuses on the design of driving safety enhancement services for commercial vehicle (i.e., bus, taxi, and truck) drivers. Based on the case studies, this paper discusses various aspects of informatics-based service design in manufacturing industries. This study would assist researchers and practitioners in designing new informatics-based services and contribute to promoting and inspiring research on intelligent services in manufacturing industries under the current information economy.
  • Kwon, R., Kim, K., and Kim, K., Hong, Y., and Kim, B., "Evaluating servicescape designs using a VR-based laboratory experiment: A case of a Duty-free Shop,"Journal of Retailing and Consumer Services, Vol. 26, 32-40, 2015.

    Abstract

    Servicescape is one of the most important dimensions by which customers evaluate their shopping experience in a retail service. This research aimed to evaluate the servicescape design of the JDC Duty-free Shop in a systematic manner. The virtual reality (VR) model was used to visualize various options for the servicescape design. The preferred design was determined from experimental results and then applied to the servicescape redesign of the shop. This research supports the relationship between servicescape design and customer perception, as well as the effectiveness of a VR-based laboratory experiment in evaluating servicescape design.
  • Lim, C. and Kim, K.,"IT-enabled Information-Intensive Service," IT Professional, Vol. 17, No.2, 26-32, 2015.

    Abstract

    Information-intensive service (IIS) is a type of service in which information interactions have a highly significant effect on service value creation. Recent innovations in information and communication technology (IT) have facilitated the creation of various types of IT-enabled IIS (IT-IIS), in which IT is essential for information interactions. This article first introduces the generic composition of IIS value creation system. Viewing the composition of IIS value creation system from an IT-oriented perspective, this article then proposes classifications of various types of IT-IIS. Understanding of the generic composition and classifications of IT-IIS serves as a basis for designing new IT-IISs. This article also introduces two IT-IIS design case studies that the authors recently conducted. This article would help IT professionals pursue IT-enabled business innovation.
  • Lim, C. and Kim, K.,"Information Service Blueprint: A Service Blueprinting Framework for Information-Intensive Services," Service Science, Vol. 6, No. 4, 2014.

    Abstract

    Information-intensive service (IIS) is a type of service in which information interactions have the most effect on service value creation. Recent innovations of information and communication technology have created various types of IISs, and the literature argues that IIS should be a research priority in this information economy. This research proposes a new service blueprinting framework specialized to IISs, called Information Service Blueprint. The framework user can succinctly capture the big-picture and key points of the complex IIS process in question by blueprinting an IIS. Information Service Blueprint has served as a basis for blueprinting IISs in IIS design projects with industry and government. An experiment to compare Information Service Blueprint with the conventional Service Blueprint also confirms its utility for blueprinting IISs. This research would serve as a basis for analyzing and designing IISs
  • Lee, D. and Kim, K., "Determining the target value of ACICD to optimize the electrical characteristics of semiconductors using dual response surface optimization," Applied Stochastic Models in Business and Industry (ASMBI), Vol. 29, No. 4, 377-386, 2013.

    Abstract

    After Cleaning Inspection Critical Dimension (ACICD), one of the main variables in the etch process, affects the electrical characteristics of fabricated semiconductor chips. Its target value should be determined to minimize the bias and variability of these electrical characteristics. This paper presents a case study in which the target value of ACICD is determined by the dual response optimization method. In particular, the recently developed posterior approach to dual response optimization is employed allowing the analyst to determine easily the optimal compromise between bias and variability in the electrical characteristics. The performance at the obtained optimal ACICD setting has been shown to be better than that at the existing setting
  • Kim, K., Lim, C., Lee, D., Lee, J., Hong, Y., and Park, K., "A Concept Generation Support System for Product-Service System Development," Service Science, Vol. 4, No. 4, 349-364, 2012.

    Abstract

    A product-service system (PSS) is a novel type of business model that integrates products and services in a single system. It provides a strategic alternative to product-oriented economic growth and price-based competition in the global market. This research proposes a methodology to support the generation of innovative PSS concepts, called the PSS concept generation support system. The models and strategies of 118 existing PSS cases were analyzed, and the insights extracted were used to develop the methodology. The methodology consists of various tools and a systematic procedure to support the generation process. It is generic enough to be applied to a variety of PSS contexts. The methodology is demonstrated and verified via case studies on the washing machine and refrigerator industries. The proposed PSS concept generation support system can serve as an efficient and effective aid to PSS designers for new PSS development.
  • Lim, C., Kim, K., Hong, Y., and Park, K., "PSS Board: A Structured Tool for Product-Service System Process Visualization," Journal of Cleaner Production (JCP), Vol. 37, 42-53, 2012.

    Abstract

    The product-service system (PSS) is a system in which its integrated products and services jointly fulfill customer needs. The current research proposes a structured tool called the PSS Board to visualize the PSS process. This is a matrix board where the customer activities, state of the products, services, dedicated infrastructures, and partners are placed in rows, and the general PSS process steps are placed in columns. The visualized PSS on the board shows how the PSS provider and its partners aid customers’ job execution process. Previous PSS cases are visualized based on the proposed PSS Board; the utility of the PSS Board is also identified. The current research can serve as an effective basis to analyze PSS from the perspective of fulfilling customer needs, thus supporting companies in diagnosing and elaborating their respective PSSs.
  • Lee, H., Kim, J., Park, J., Kim, K., and Hong, Y., "A Strategy Matrix for the Product-Service System," Information-An International Interdisciplinary Journal, Vol. 15, No.8, 3391-3400, 2012.

    Abstract

    This study aims to design the strategy matrix for the product-service system (PSS) which integrates products and services. This study reviews major studies of the PSS; discusses the necessity for the PSS classification; proposes a new classification; and suggests a strategy matrix for the PSS. The results have practical implications for firms pursuing competitive advantage and sustainable growth.
  • Lee, D. and Kim, K., "Interactive Weighting of Bias and Variance in Dual Response Surface Optimization," Expert Systems With Applications (ESWA), Vol.39, No.5, 5900-5906, 2012.

    Abstract

    In dual response surface optimization, minimizing weighted mean squared error (WMSE) is a simple yet effective way of obtaining a satisfactory solution. To minimize WMSE, the weights of the squared bias and variance should be determined in advance. Determining the weights in accordance with the decision maker (DM)’s preference structure regarding the tradeoffs between the two responses is critical and difficult. In this study, we develop an interactive weighting method where the DM provides his/her preference information in the form of pairwise comparisons. Our method estimates the weights based on the pairwise comparisons in an interactive manner. The method obtains a satisfactory solution through several pairwise comparisons in the case examples that we tested.
  • Lee, D., Kim, K., and Koksalan, M., "An Interactive Method to Multiresponse Surface Optimization Based on Pairwise Comparisons," IIE Transactions, Vol.44, No.1, 13-26, 2012.

    Abstract

    In multiresponse surface optimization, responses are often in conflict. To obtain a satisfactory compromise, the preference information of a decision maker (DM) on the tradeoffs among the responses should be incorporated into the problem. We propose an interactive method where the DM provides preference information in the form of pairwise comparisons. The results of pairwise comparisons are used to estimate the preference parameter values in an interactive manner. The method is effective in that a highly satisfactory solution can be obtained.
  • Kwak, D. and Kim, K., "A Data Mining Approach Considering Missing Values for the Optimization of Semiconductor-Manufacturing Processes," Expert Systems With Applications, Vol 39, 2590-2596, 2012.

    Abstract

    Due to the rapid development of information technologies, abundant data have become readily available. Data mining techniques have been used for process optimization in many manufacturing processes in automotive, LCD, semiconductor, and steel production, among others. However, a large amount of missing values occurs in the data set due to several causes (e.g., data discarded by gross measurement errors, measurement machine breakdown, routine maintenance, sampling inspection, and sensor failure), which frequently complicate the application of data mining to the data set. This study proposes a new procedure for optimizing processes called missing values-Patient Rule Induction Method (m-PRIM), which handles the missing-values problem systematically and yields considerable process improvement, even if a significant portion of the data set has missing values. A case study in a semiconductor manufacturing process is conducted to illustrate the proposed procedure.
  • Lee, D. and Kim, K., "A Review on Posterior and Interactive Solution Selection Methods to Multiresponse Surface Optimization," Journal of Quality, Vol. 18, No. 4, 279-301, 2011.

    Abstract

    The responses in multiresponse surface optimization are often in conflict. To obtain a satisfactory compromise, the preference information of a decision maker (DM) on the tradeoffs among the responses should be incorporated into the problem. In most existing works, the DM is required to provide his/her preference information through preference parameters before solving the problem. However, extracting the preference parameter values representing the preference structure of the DM is often difficult. To overcome these difficulties, several alternative methods that do not require the preference information of the DM before solving the problem have been suggested. These alternative methods assess the preference parameters of the DM in a posteriori or progressive manner and are called posterior or interactive methods, respectively. This paper reviews specific types of posterior and interactive methods, which are referred to as solution selection methods. In solution selection methods, the DM provides his/her preference information in the form of solution selection. The required information is easy for the DM to provide.
  • Lee, D., Kim, K., and Koksalan, M., "A Posterior Preference Articulation Approach to Multiresponse Surface Optimization," European Journal of Operational Research, Vol. 210, No. 2, 301-309, 2011.

    Abstract

    In multiresponse surface optimization (MRSO), responses are often in conflict. To obtain a satisfactory compromise, the preference information of a decision maker (DM) on the tradeoffs among the responses should be incorporated into the problem. In most existing work, the DM expresses a subjective judgment on the responses through a preference parameter before the problem-solving process, after which a single solution is obtained. In this study, we propose a posterior preference articulation approach to MRSO. The approach initially finds a set of nondominated solutions without the DM's preference information, and then allows the DM to select the best solution from among the nondominated solutions. An interactive selection method based on pairwise comparisons made by the DM is adopted in our method to facilitate the DM's selection process. The proposed method does not require that the preference information be specified in advance. It is easy and effective in that a satisfactory compromise can be obtained through a series of pairwise comparisons, regardless of the type of the DM's utility function.
  • Burger, T., Kim, K., and Meiren, T., "A Structured Test Approach for Service Concepts," International Journal of Service Science, Management, Engineering and Technology (IJSSMET), Vol. 1, No. 4, 12-21, 2010.

    Abstract

    To assure new services attain a certain level of quality, services should be developed and tested systematically like products or software. In practice, this is rarely the case, especially in regards to the testing of service concepts due to appropriate solutions, processes, and methodology seem to be missing. In this paper, the authors propose an approach to how service testing can be realized in practice and present supporting processes, methods, and technologies for testing services in laboratory environments.
  • Kim, H., Kim, K., and Kwak, D., "A Case Study on Modeling and Optimizing Photolithography Stage of Semiconductor Fabrication Process," Quality and Reliability Engineering International, Vol. 26, No. 7, 765-774, 2010.

    Abstract

    Photolithography in the semiconductor fabrication process is the core stage that determines the quality of semiconductor chips. The fabrication process is a batch process that causes variation in the quality of chips; thus, uniformity has always been an important goal of the process. This research is a case study on optimizing the photolithography stage to improve uniformity and the target achievement of critical dimension (CD), a quality measure of semiconductor chips. The case study finds the optimal setting of input variables in photolithography by applying multivariate normal linear (MVNL) modeling with operational data obtained by sampling during manufacturing. The predicted performance of the optimal setting is found to be close to the limit of improvement estimated based on the model. For practitioners, several issues that can be considered for better optimization are also provided.
  • Kim, D., Kim, K., and Park, K., "Compromising Prioritization from Pairwise Comparisons Considering Type I and II Errors," European Journal of Operational Research, Vol. 204, No. 2, 285-293, 2010.

    Abstract

    We explore an important problem in prioritizing product design alternatives, using a real-world case. Despite the importance of prioritization in the area of new product development, the development of systematic schemes has been limited and the concepts and methods developed in the decision analysis area do not seem to be used actively. Therefore, we propose a new method, referred to as the compromising prioritization technique, to prioritize the product design alternatives based on paired comparisons. It introduces type I and type II errors and compromises these two errors to arrive at a desirable order of alternatives. To accomplish this, the two indices of homogeneity and separation are developed together with a heuristic algorithm. A comparative study is also conducted to support our method for use in product development and analogous areas. We then demonstrate how to use the developed compromising prioritization technique using a case study on the asymmetric digital subscriber line (ADSL)-based high-speed internet service product.
  • Jeong, I., Kim, K., and Lin, D., "Bayesian Analysis for Weighted Mean Squared Error in Dual Response Surface Optimization," Quality and Reliability Engineering International, Vol. 26, No. 5, 417-430, 2010.

    Abstract

    Dual response surface optimization considers the mean and the variation simultaneously. The minimization of Mean Squared Error (MSE) is an effective approach in dual response surface optimization. Weighted MSE (WMSE) is formed by imposing the relative weights, on the squared bias and variance components of MSE. To date, a few methods have been proposed for determining. The resulting from these methods is either a single value or an interval. This paper aims at developing a systematic method to choose a value when an interval of is given. Specifically, this paper proposes a Bayesian approach to construct a probability distribution of Once the probability distribution of is constructed, the expected value of can be used to form WMSE.
  • Kwak, D., Kim, K., and Lee, M., "Multistage PRIM: Patient Rule Induction Method for Optimization of a Multistage Manufacturing Process," International Journal of Production Research, Vol. 48, No. 12, 3461-3473, 2010.

    Abstract

    Industries such as automotive, LCD, PDP, semiconductor and steel produce products through multistage manufacturing processes. In a multistage manufacturing process, performances of stages are not independent. Therefore, the relationship between stages should be considered when optimizing the multistage manufacturing process. This study proposes a new procedure of optimizing a multistage manufacturing process, called Multistage PRIM (Patient Rule Induction Method). Multistage PRIM extends the scope of process optimization from a single stage to the multistage process, and it can use the information encapsulated in the relationship between stages when maximizing each stage's performance. A case study in a multistage steel manufacturing process is conducted to illustrate the proposed procedure.
  • Lee, D., Jeong, I., and Kim, K., "A Posterior Preference Articulation Approach to Dual-Response Surface Optimization," IIE Transactions, Vol. 42, No. 2, 161-171, 2009.

    Abstract

    In dual response surface optimization, the mean and standard deviation responses are often in conflict. To obtain a satisfactory compromise, a Decision Maker (DM)'s preference information on the tradeoffs between the responses should be incorporated into the problem. In most existing works, the DM expresses the subjective judgment on the responses through a preference parameter before the problem-solving process, after which a single solution is obtained. In this study, we propose a posterior preference articulation approach to dual response surface optimization. The posterior preference articulation approach initially finds a set of nondominated solutions without the DM's preference information, and then allows the DM to select the best solution among the nondominated solutions. The proposed method enables the DM to obtain a satisfactory compromise solution with minimum cognitive effort and gives him/her the opportunity to explore and better understand the tradeoffs between the two responses
  • Kim, K., Shin, W., Min, D., Kim, H., Yoo, J., Lim, H., Lee, S., and Jeong, Y., "Service Quality Model for IPTV Service: Identification of Key Features and Their Relationships," International Journal of Industrial Engineering: Theory, Applications and Practice, Vol. 16, No. 4, 305-317, 2009.

    Abstract

    Because of the rapid growth of the service sector, an effective and systematic methodology for quality analysis and improvement is increasingly important. An internet protocol television (IPTV) service provides various contents on demand via television and set-top box with internet line. Its global market size is rapidly growing, but there is a lack of systematic analysis about IPTV service quality. The purpose of this paper is to develop an IPTV service quality model and identify key features and their relationships. The quality function deployment (QFD) method is applied in two phases. The results of QFD application are analyzed and key features and their relationships are identified. Moreover, examples of applying the analysis to improve IPTV service quality are developed for IPTV service providers. As the analysis provided is general and applicable to other services, this paper provides insights into improving service quality, not only for ITPV service providers, but also for service providers in many kinds of industries.
  • Jeong, I. and Kim, K., "An Interactive Desirability Function Method to Multiresponse Optimization," European Journal of Operational Research, Vol. 195, No. 2, 412-426, 2009.

    Abstract

    Multiresponse optimization problems often involve incommensurate and conflicting responses. To obtain a satisfactory compromise in such a case, a decision maker (DM)'s preference information on the tradeoffs among the responses should be incorporated into the problem. This paper proposes an interactive method based on the desirability function approach to facilitate the preference articulation process. The proposed method allows the DM to adjust any of the preference parameters, namely, the shape, bound, and target of a desirability function in a single, integrated framework. The proposed method would be highly effective in generating a compromise solution that is faithful to the DM's preference structure.
  • Kim, D. and Kim, K., "Robustness Indices and Robust Prioritization in QFD," Expert Systems With Applications, Vol. 36, No. 2, 2651-2658, 2009.

    Abstract

    The prioritization of engineering characteristics (ECs) provides an important basis for decision-making in QFD. However, the prioritization results in the conventional QFD may be misleading since it does not consider the uncertainty of input information. This paper develops two robustness indices and proposes the notion of robust prioritization that ensures the EC prioritization to be robust against the uncertainty. The robustness indices consider robustness from two perspectives, namely, the absolute ranking of ECs and the priority relationship among ECs. Based on the two indices, robust prioritization seeks to identify a set of ECs or a priority relationship among ECs in such a way that the result of robust prioritization is stable despite the uncertainty. Finally, the proposed robustness indices and robust prioritization are demonstrated in a case study conducted on the ADSL-based high-speed internet service.
  • Lee, M., Kim, K.,, "MR-PRIM: Patient Rule Induction Method for Multiresponse Optimization," Quality Engineering, Vol. 20, No. 2, 232-242, 2008.

    Abstract

    Most of the works in multiresponse surface methodology have been focusing mainly on the optimization issue, assuming that the data have been collected and suitable models have been built. Though crucial for optimization, a good empirical model is not easy to obtain from the manufacturing process data. This article proposes a new approach to solving the multiresponse problem directly without building a model?an approach called patient rule induction method for multiresponse optimization (MR-PRIM). MR-PRIM is an extension of PRIM to multiresponse problems. Three major characteristic features of MR-PRIM are discussed as the new approach is applied to the case of a steel manufacturing process.
  • Cho, H., Kim, K., and Jeong, M., "Determination of influential factors and diagnostics using multivariate statistical relationships between variables and faults," Expert Systems with Applications, Vol. 35, No. 1, 30-40, 2008.

    Abstract

    This paper proposes a variable influence (VI) index-based on-line method for diagnosing discontinuous processes. The VI index is developed using the concept of contribution plots, and can be used to explain the influence of a process variable on a specific fault. The proposed method consists of two phases: on-line VI model-building and on-line diagnosis via VI index comparison. In the on-line VI model-building phase, the on-line VI model is constructed using on-line fault data and used as a reference model for the on-line diagnosis of a new batch. The on-line diagnosis phase is triggered by an out-of-control signal of a new batch. It calculates the VI index values for new process data available at that time, which are compared with the on-line VI index values of the on-line VI model stored in the data/model base. The proposed method has the advantage that it does not require any process knowledge of operators and can automatically select an assignable cause via the comparison of VI index values. A case study on a PVC batch process is conducted to demonstrate the diagnosis performance of the proposed method. The performance of the proposed method is also evaluated when an on-line mode is not considered in the proposed framework.
  • Hong, S., Han, S., and Kim, K., "Optimal Balancing of Multiple Affective Satisfaction Dimensions: A Case Study on Mobile Phones," International Journal of Industrial Ergonomics, Vol. 38, No. 3-4, 272-279, 2008.

    Abstract

    Most of the works in multiresponse surface methodology have been focusing mainly on the optimization issue, assuming that the data have been collected and suitable models have been built. Though crucial for optimization, a good empirical model is not easy to obtain from the manufacturing process data. This paper proposes a new approach to solving the multiresponse problem directly without building a model-an approach called 'patient rule induction method for multiresponse optimization (MR-PRIM)'. MR-PRIM is an extension of PRIM to multiresponse problems. Three major characteristic features of MR-PRIM are discussed as the new approach is applied to the case of a steel manufacturing process.
  • Kim, K. and Kim, D., "Research Issues in Robust QFD," Industrial Engineering and Management Systems, Vol. 7, No. 2, 93-100, 2008.

    Abstract

    Quality function deployment (QFD) provides a specific approach for ensuring quality throughout each stage of the product development and production process. Since the focus of QFD is placed on the early stage of product development, the uncertainty in the input information of QFD is inevitable. If the uncertainty is neglected, the QFD analysis results are likely to be misleading. It is necessary to equip practitioners with a new QFD methodology that can model, analyze, and dampen the effects of the uncertainty and variability in a systematic manner. Robust QFD is an extended version of QFD methodology, which is robust to the uncertainty of the input information and the resulting variability of the QFD output. This paper discusses recent research issues in Robust QFD. The major issues are related with the determination of overall priority, robustness evaluation, robust prioritization, and web-based Robust QFD optimizer. Our recent research results on the issues are presented, and some of future research topics are suggested.
  • Min, D. and Kim, K., "An Extended QFD Planning Model for Selecting Design Requirements with Longitudinal Effect Consideration," Expert Systems With Applications, Vol. 35, No. 4, 1546-1554, 2008.

    Abstract

    An extended QFD planning model is presented for selecting design requirements (DRs) that consider longitudinal effect. In the proposed model, the longitudinal effect is incorporated by introducing a time dimension into the existing house of quality structure. As a consequence of explicitly considering the longitudinal effect, the proposed model yields not only an optimal set of DRs but also the timing of their selection. The proposed model is demonstrated through a case study for improving customer loyalty in the high-speed internet service.
  • Lee, M. and Kim, K., "Expected Desirability Function: Consideration of Both Location and Dispersion Effects in Desirability Function Approach," Quality Technology and Quantitative Management, Vol. 4, No. 3, 365-377, 2007.

    Abstract

    A new type of desirability function for a multiresponse problem is proposed. The proposed desirability function, called an expected desirability function, is defined as the average of the conventional desirability values based on the probability distribution of the predicted response variable. The major advantage of the proposed approach over the conventional desirability function approach is that it considers the dispersion effects as well as the location effects of the responses. Moreover, it is shown that the proposed approach results in a higher process capability than the conventional desirability approach, especially in the asymmetric nominal-the-best-type response case.
  • Kim, D., Lee, M., and Kim, K., "A Systematic Method for Generating Engineering Characteristic Candidates in Quality Function Deployment," International Journal of Industrial Engineering:Theory, Applications and Practice, Vol. 14, No. 2, 179-187, 2007.

    Abstract

    The set of the engineering characteristics (ECs) in quality function deployment (QFD) should be comprehensive enough to explain all the given customer requirements. The identification of such a set of ECs, which is currently done using brainstorming in practice, is a challenging task. Notwithstanding the rapid growth of the QFD literature, development of a systematic procedure for identifying ECs has scarcely been addressed. This paper proposes a systematic method for generating EC candidates. By providing a step-by-step procedure, the proposed method ensures that all the important ECs are identified, the generated ECs are measurable, and subjective judgments are minimally required. Hence, the shortcomings associated with the existing practice based on brainstorming can be effectively overcome. The unique characteristics of the proposed method are also demonstrated via a case study.
  • Kim, K., Kim, D., and Min, D., "Robust QFD: Framework and a Case Study," Quality and Reliability Engineering International, Vol. 23, No. 1, 31-44, 2007.

    Abstract

    Quality function deployment (QFD) provides a specific approach for ensuring quality throughout each stage of the product development. Since the focus of QFD is placed on the early stage of product development, the uncertainty in the input information of QFD is inevitable. If the uncertainty is neglected, the QFD analysis results can be misleading. This paper proposes an extended version of the QFD methodology, called Robust QFD, which is capable of considering the uncertainty of the input information and the resulting variability of the output. The proposed framework aims to model, analyze, and dampen the effects of the uncertainty and variability in a systematic manner. The proposed framework is demonstrated through a case study on the AD니-based high-speed Internet service.
  • Kim, K., Jeong, I., Park, J., Park, Y., Kim, C., and Kim, T., "The Impact of Network Service Performance on Customer Satisfaction and Loyalty: High-speed Internet Service Case in Korea," Expert Systems with Applications, Vol. 32, No. 3, 822-831, 2007.

    Abstract

    The high-speed internet service has achieved a remarkable increase in penetration in recent years. In order to survive in this competitive market, companies should continue to improve their service performance. The high level of service performance is believed to be an effective way to improve customer satisfaction and loyalty. This paper aims to identify the causal relationship among network performance, customer satisfaction, and customer loyalty in the high-speed internet service context. Using the data collected from 51 current users of a VD니 service in Korea, this paper derives two types of the causal relationship models, namely, cross-sectional model and longitudinal model. The modeling results are discussed from both descriptive and prescriptive perspectives.
  • Kim, K., Cho, H., Jeong, I., Park, J., Park, Y., Kim, C., and Kim, T., "Service Quality Analysis and Improvement: Development of a Systematic Framework (a Case Study)," International Journal of Industrial Engineering: Theory, Applications and Practice, Vol. 13, No. 2, 177-187, 2006.

    Abstract

    As the service sector is rapidly growing, one of the challenges faced by the entire service industries is the lack of effective methodologies for quality analysis and improvement. In service industries, the service quality serves as both a customer retention tool and a business differentiator in local and global competition. This paper aims at developing a systematic framework for service quality analysis and improvement. The proposed framework advantageously integrates quality function deployment (QFD) and structural equation modeling (SEM). More specifically, the framework utilizes QFD to collect, organize, and analyze qualitative information. The results of QFD are used as the basis for developing a service quality improvement strategy. Then, SEM is employed in building and analyzing quantitative models to devise a detailed strategy for the improvement. The proposed framework is demonstrated through a case study on the asymmetric digital subscriber lines (ADSL) service of a major telecommunication company in Asia. This framework can be utilized for an effective analysis and improvement of service quality not just in the telecommunication industry, but also in any service industry which collects customer satisfaction and service performance data as part of its daily operation.
  • Kim, K. and Lin, D., "Optimization of Multiple Responses Considering Both Location and Dispersion Effects," European Journal of Operational Research, Vol. 169, No. 1, 133-145, 2006.

    Abstract

    An integrated modeling approach to simultaneously optimizing both the location and dispersion effects of multiple responses is proposed. The proposed approach aims to identify the setting of input variables to maximize the overall minimal satisfaction level with respect to both location and dispersion of all the responses. The proposed approach overcomes the common limitation of the existing multiresponse approaches, which typically ignore the dispersion effect of the responses. Several possible variations of the proposed model are also discussed. Properties of the proposed approach are reveled via a real example.
  • Kim, K., Lee, D., and Lee, M., "Determining Product Platform Elements for Mass Customization," International Journal of Productivity and Quality Management, Vol. 1, No. 1/2, 168-182, 2006.

    Abstract

    This paper addresses the issue of how to determine the physical elements of a product which should be included in the product platform, called the product platform elements, for mass customisation. Two types of indices, namely, the similarity index and the sensitivity index, are proposed to determine the product platform elements from the mass and the customisation perspectives, respectively. The physical elements with a large similarity index and a small sensitivity index are selected as the product platform elements. The proposed methodology is demonstrated via a case study. The product platform developed in the proposed methodology should be useful in accommodating various customer tastes while maintaining the cost efficiency of mass production.
  • Cho, H., Kim, K., and Jeong, M., "On-line monitoring and diagnosis of batch processes: empirical model-based framework and a case study," International Journal of Production Research, Vol. 44, No. 12, 2361-2378, 2006.

    Abstract

    An empirical model-based framework for monitoring and diagnosing batch processes is proposed. With the input of past successful and unsuccessful batches, the off-line portion of the framework constructs empirical models. Using online process data of a new batch, the online portion of the framework makes monitoring and diagnostic decisions in a real-time basis. The proposed framework consists of three phases: monitoring, diagnostic screening, and diagnosis. For monitoring and diagnosis purposes, the multiway principal-component analysis (MPCA) model and discriminant model are adopted as reference models. As an intermediate step, the diagnostic screening phase narrows down the possible cause candidates of the fault in question. By analysing the MPCA monitoring model, the diagnostic screening phase constructs a variable influence model to screen out unlikely cause candidates. The performance of the proposed framework is tested using a real dataset from a PVC batch process. It has been shown that the proposed framework produces reliable diagnosis results. Moreover, the inclusion of the diagnostic screening phase as a pre-diagnostic step has improved the diagnosis performance of the proposed framework, especially in the early time intervals.
  • You, H., Ryu, T., Oh, K., Yun, M., and Kim, K., "Development of customer satisfaction models for automotive interior materials," International Journal of Industrial Ergonomics, Vol. 36, No. 4, 323-330, 2006.

    Abstract

    As the functional characteristics of passenger vehicles reach satisfactory levels, customers' concerns with the ergonomic and aesthetic aspects of the interior design have increased. The present study developed satisfaction models of automotive interior materials for six parts including crash pad, steering wheel, transmission gearshift knob, audio panel, metal grain inlay, and wood grain inlay. Based on literature survey, customer reviews on the web, and expert opinions, 8-15 material design variables were de?ned for the interior parts. The material design characteristics of 30 vehicle interiors were measured and customer satisfaction with the vehicle interiors was evaluated by 30 participants in the 20-30-year-old range. The material design variables were screened by evaluating their statistical, technical, and practical signi?cance and satisfaction models were developed by quanti?cation I analysis. The satisfaction models were used to identify relatively important design variables and preferred design features for the interior parts.
  • Jeong, I., Kim, K., and Chang, S., "Optimal Weighting of Bias and Variance in Dual Response Surface Optimization," Journal of Quality Technology, Vol. 37, No. 3, 236-247, 2005.

    Abstract

    Dual response surface optimization simultaneously considers the mean and the standard deviation of a response. The minimization of the mean squared error (MSE) is a simple, yet effective approach in dual response surface optimization. The bias and variance components of MSE need to be weighted properly if they are not of the same importance in the given problem situation. To date, the relative weights of bias and variance have been equally set or determined only by the data. However, the weights should be determined in accordance with the tradeoffs on various factors in quality and costs. In this paper, we propose a systematic method to determine the weights of bias and variance in accordance with a decision maker's preference structure regarding the tradeoffs.
  • Ko, Y., Kim, K., and Jun, C., "A New Loss Function- Based Method for Multiresponse Optimization," Journal of Quality Technology, Vol. 37, No. 1, 50-59, 2005.

    Abstract

    A new loss function-based method for multiresponse optimization is presented. The proposed method introduces predicted future responses in a loss function, which accommodates robustness and quality of predictions as well as bias in a single framework. Properties of the proposed method are illustrated with two examples. We show that the proposed method gives more reasonable results than the existing methods when both robustness and quality of predictions are important issues.
  • Balamurali, S., Park, H., Jun, C., Kim, K., and Lee, J., "Designing of Variables Repetitive Group Sampling Plan Involving Minimum Average Sample Number," Communications in Statistics - Simulation and Computation, Vol. 34, 799-809, 2005.

    Abstract

    This article proposes the variables repetitive group sampling plan where the quality characteristic follows normal distribution or lognormal distribution and has upper or lower specification limit. The problem is formulated as a nonlinear programming problem where the objective function to be minimized is the average sample number and the constraints are related to lot acceptance probabilities at acceptable quality level (AQL) and limiting quality level (LQL) under the operating characteristic curve. Sampling plan tables are constructed for the selection of parameters indexed by AQL and LQL in the cases of known standard deviation and unknown standard deviation. It is shown that the proposed sampling plan significantly reduces the average sample number as compared with the single and double sampling plans
  • Jeong, I. and Kim, K., "D-STEM: A Modified Step Method with Desirability Function Concept," Computers and Operations Research, Vol. 32, No. 12, 3175-3190, 2005.

    Abstract

    Step method (STEM) is one of the well-known multi-objective optimization techniques. STEM has proven to be effective in extracting a decision maker (DM)'s preference information for a satisfactory compromise. However, it has been criticized for not considering the differing degrees of satisfaction associated with an objective function value, and for not providing flexible options in the process of preference information extraction. This paper proposes a modified STEM, called D-STEM, to overcome the methodological limitations of STEM. D-STEM utilizes the concept of a desirability function to realistically model the differing degrees of satisfaction. D-STEM also allows a DM to choose either tightening or relaxation, which makes the preference articulation process more efficient and effective. The advantages of D-STEM are demonstrated through an illustrative example.
  • Park, K. and Kim, K., "Optimizing Multi-Response Surface Problems: How to Use Multi-Objective Optimization Techniques," IIE Transactions, Vol. 37, No. 6, 523-532, 2005.

    Abstract

    A common problem encountered in product or process design is the selection of optimal parameter levels that involves the simultaneous consideration of multiple response characteristics, called a multi-response surface problem. Notwithstanding the importance of multi-response surface problems in practice. the development of an optimization scheme has received little attention. In this paper, we note that Multi-Response surface Optimization(MRO) can be viewed as a Multi-Objective Optimization(MOO) and that various techniques developed in MOO can be successfully utilized to deal with MRO problems. We also show that some of the existing desirability function approaches can, in fact, be characterized as special forms of MOO. We then demonstrate some MOO principles and methods in order to illustrate how these approaches can be employed to obtain more desirable solutions to MRO problems.
  • Cho, H., Kim, K., and Jeong, M., "Multivariate Statistical Diagnosis Using Trigangular Representation of Fault Patterns in Principal Component Space," International Journal of Production Research, Vol. 43, No. 24, 5181-5198, 2005.

    Abstract

    A pattern-based multivariate statistical diagnosis method is proposed to diagnose a process fault on-line. A triangular representation of process trends in the principal component space is employed to extract the on-line fault pattern. The extracted fault pattern is compared with the existing fault patterns stored in the fault library. A diagnostic decision is made based on the similarity between the extracted and the existing fault patterns, called a similarity index. The diagnosis performance of the proposed method is demonstrated using simulated data from Tennessee Eastman process. The diagnosis success rate and robustness to noise of the proposed method are also discussed via computational experiments.
  • Cho, H. and Kim, K., "Diagnosing Batch Processes with Insufficient Data: Generation of Pseudo Batches," International Journal of Production Research, Vol. 43, No. 14, 2997-3009, 2005.

    Abstract

    To ensure the safety of a batch process and the quality of its final product, one needs to quickly identify an assignable cause of a fault. Cho and Kim (2003) recently proposed a diagnosis method for batch processes using Fisher's Discriminant Analysis (FDA), which showed a satisfactory performance on industrial batch processes. However, their method (or any other method based on empirical models) has a major limitation when the fault batches available for building an empirical diagnosis model are insufficient. This is a highly critical issue in practice because sufficient fault batches are likely to be unavailable. In this work, we propose a method to handle the insufficiency of the fault data in diagnosing batch processes. The basic idea is to generate so-called pseudo batches from known fault batches and utilise them as part of the diagnosis model data. The performance of the proposed method is demonstrated using a real data set from a PVC batch process. The proposed method is shown to be capable of handling the data insufficiency problem successfully, and yields a reliable diagnosis performance.
  • Han, S., Kim, K., Yun, M., Hong, S., and Kim, J., "Identifying Mobile Phone Design Features Critical to User Satisfaction," Human Factors and Ergonomics in Manufacturing, Vol. 14, No. 1, 15-29, 2004.

    Abstract

    A variety of mobile phones are available to consumers. They differ from each other in many design features including shape, color, size, and material. This study attempts to identify some of the design features of a mobile phone critical to user satisfaction. Empirical models linking design features to satisfaction levels were developed and used to identify critical design features. Design properties common to "desirable" and "undesirable" phones were then extracted by comparing the values of the critical design features. The approach used in this study may help the product designers identify critical design features with their desirable properties in a systematic manner.
  • Jeong, I. and Kim, K., "Interactive Desirability Function Approach to Multi-Response Surface Optimization," International Journal of Reliability, Quality, and Safety Engineering, Vol. 10, No. 2, 205-217, 2003.

    Abstract

    A common problem encountered in product or process design is the selection of optimal parameters that involves simultaneous consideration of multiple response characteristics, called a multiple response surface (MRS) problem. There are several approaches proposed for multiple response surface optimization (MRO), including the priority-based approach, the desirability function approach, and the loss function approach. The existing MRO approaches require that all the preference information of a decision maker be articulated prior to solving the problem. However, it is difficult for the decision maker to articulate all the preference information in advance. This paper proposes an interactive approach, called an interactive desirability function approach (IDFA), to overcome the common limitation of the existing approaches. IDFA focuses on extracting the decision maker's preference information in an interactive manner. IDFA requires no explicit tradeoffs among the responses and gives an opportunity for the decision maker to learn his/her own tradeoff space. Consequently, through IDFA, it is more likely that the decision maker finds a solution which is faithful to his/her preference structure.
  • Kim, K., Cho, H., Jeong, I., and Lim, I., "A Synopsis of Recent Methodological Enhancements on Quality Function Deployment," International Journal of Industrial Engineering: Theory, Applications and Practice, Vol. 10, No. 4, 462-466, 2003.

    Abstract

    Quality Function Deployment (QFD) is a concept and mechanism for translating the "voice of the customer" through the various stages of product planning, engineering, and manufacturing into a final product. Notwithstanding the rapid growth of the QFD literature, development of systematic procedures for an effective use of QFD has scarcely been addressed. In this paper, we first review the limitations of the existing QFD framework, and then present a synopsis of the recent methodological enhancement on QFD.
  • Cho, H. and Kim, K., "Handling Data Insufficiency Problem in Diagnosing Batch Processes," International Journal of Reliability, Quality, and Safety Engineering, Vol. 10, No. 2, 171-184, 2003.

    Abstract

    To ensure safety of a batch process and quality of its _nal product, one needs to quickly identify an assignable cause of a fault. To solve the diagnosis problem of a batch process, Cho and Kim6 proposed a new statistical diagnosis method based on Fisher discriminant analysis (FDA). They showed satisfactory diagnosis performance on industrial batch processes. However, the diagnosis method of Cho and Kim6 has a major limitation: it does not work when the fault data available for building the discriminant model are insucient. In this work, we propose a method to handle the insu_ciency of the fault data in diagnosing batch processes. The diagnosis performance of the proposed method is demonstrated using a data set from a PVC batch process. The proposed method is shown to be able to handle the data insu_ciency problem, and yield reliable diagnosis performance.
  • Cho, H. and Kim, K., "A Method for Predicting Future Observations in the Monitoring of a Batch Process," Journal of Quality Technology, Vol. 35, No. 1, 59-69, 2003.

    Abstract

    Batch processes play an important role in the production of low-volume, high-value products such as polymers, pharmaceuticals, and biochemicals. Multiway Principal Components Analysis (MPCA), one of the multivariate projection methods, has been widely used for monitoring batch processes. One major problem in the on-line application of MPCA is that the input data matrix for MPCA is not complete until the end of the batch operation, and thus the unmeasured portion of the matrix (called the "future observations") has to be predicted. In this paper we propose a new method for predicting the future observations of the batch that is currently being operated (called the "new batch"). The proposed method, unlike the existing prediction methods, makes extensive use of the past batch trajectories. The past batch trajectory which is deemed the most similar to the new batch is selected from the batch library and used as the basis for predicting the unknown part of the new batch. A case study on an industrial PVC batch process has been conducted. The results show that the proposed method results in more accurate prediction and has the capability of detecting process abnormalities earlier than the existing methods.
  • Cho, H. and Kim, K., "Fault Diagnosis of Batch Processes Using Discriminant Model," International Journal of Production Research, Vol. 42, No. 3, 597-612, 2002.

    Abstract

    A new statistical online diagnosis method for a batch process is proposed. The proposed method consists of two phases: offline model building and online diagnosis. The offline model building phase constructs an empirical model, called a discriminant model, using various past batch runs. When a fault of a new batch is detected, the online diagnosis phase is initiated. The behaviour of the new batch is referenced against the model, developed in the offline model building phase, to make a diagnostic decision. The diagnosis performance of the proposed method is tested using a dataset from a PVC batch process. It has been shown that the proposed method outperforms existing PCA-based diagnosis methods, especially at the onset of a fault.
  • Kim, K., Han, S., Yun, M., and Kwahk, J., "A Systematic Procedure for Modeling Usability Based on Product Design Variables: A Case Study in Audio-Visual Consumer Electronic Products," International Journal of Occupational Safety and Ergonomics, Vol. 8, No. 3, 387-406, 2002.

    Abstract

    A systematic modeling approach to describing, prescribing, and predicting usability of a product has been presented. Given the evaluation results of the usability dimension (UD) and the measurement of the product's design variables, referred to as the human interface elements (HIEs), the approach enables one to systematically assess the relationship between the UD and HIEs. The assessed relationship is called a usability model. Once built, such a usability model can relate, in a quantitative manner, the HIEs directly to the UDs, and thus can serve as an effective aid to designers by evaluating and predicting the usability of an existing or hypothetical product. A usability model for elegance of audiovisual consumer electronic products has been demonstrated.
  • Shin, J., Kim, K., and Chandra, M., "Consistency Check of a House of Quality Chart," International Journal of Quality and Reliability Management, Vol. 19, No. 4, 471-484, 2002.

    Abstract

    Quality Function Deployment (QFD) is a cross-functional planning tool which ensures that the voice of the customer is systematically deployed throughout the product planning and design stages. One of the common mistakes in QFD is to perform analysis using an inconsistent house of quality (HOQ) chart. An inconsistent HOQ chart is one in which the information from the roof matrix is inconsistent with that from the relationship matrix. This paper develops a systematic procedure to check the consistency of an HOQ chart. The proposed consistency check can be performed prior to QFD's main analysis to ensure the validity of the final results. A procedure for identifying the source of the inconsistency, if the HOQ chart should fail the consistency test, is also developed. The proposed procedures are illustrated through examples.
  • Yi, G., Shin, J., Cho, H., and Kim, K., "Quality Oriented Shop Floor System for Large Scale Manufacturing Processes: Functional Framework and Experimental Results," Journal of Manufacturing Systems, Vol. 21, No. 3, 187-199, 2002.

    Abstract

    It is now widely accepted within the industrial community that quality assurance is essential for future survival and competitiveness. However, most activities for improving quality in large-scale manufacturing processes have been performed offline, without being integrated into the conventional shop floor control system (SFCS). In general, the SFCS has focused only on efficient production planning and scheduling. The goal of the paper is to propose the functional framework of a quality-oriented shop floor control system (QSFCS) for large-scale manufacturing processes, and then to test this framework on a real process. The proposed system is composed of two auxiliary components, one for matching sensory data and quality inspection data (data matching) and the other for defining the expert knowledge of the operator (knowledge acquisition), and three primary components that entail building prediction and control models (model design), and analyzing, diagnosing, and optimizing the processes to improve product quality (feedforward adjustment, online adjustment). A partial least-square (PLS) method is employed to cope with the massive data sets online because of its minimal demands on measurement scales and sample size, and its ability to handle large numbers of highly correlated variables. The proposed framework is applied to the shadow mask manufacturing process, which consists of a few hundred process parameters and about 40 quality characteristics. The experimental case study shows that the quality deficiencies are reduced from 5% or 10% of occurrence to nearly 0%.
  • Shin, J. and Kim, K., "Effect and Choice of the Weighting Scale in QFD," Quality Engineering, Vol. 12, No. 3, 347-356, 2000.

    Abstract

    Keywords: Quality Function Deployment; House of Quality Chart; Weighting Scale; Normalization
  • Shin, J. and Kim, K., "Complexity Reduction of a Design Problem in QFD Using Decomposition," Journal of Intelligent Manufacturing, Vol. 11, No. 4, 339-354, 2000.

    Abstract

    Quality function deployment (QFD) is a cross-functional planning tool that ensures that the voice of the customer is systematically deployed throughout the product planning and design stages. Although many success applications of QFD have been reported worldwide, designers face impediments to the adoption of QFD as a product design aid. One of the dif culties associated with the application of QFD is the large size of a house of quality (HOQ) chart, which is the principal tool for QFD. It is well-known that it becomes more difficult and inefficient to manage a design project as the problem size becomes larger. This paper proposes to develop formal approaches to reducing the size of an HOQ chart using the concept of design decomposition. The decomposition approaches developed attempt to partition an HOQ chart into several smaller sub-HOQ charts which can be solved efficiently and independently. By decomposing a large HOQ chart into smaller sub-HOQ charts, the design team not only can enhance the concurrency of the design activities, but also reduce the amount of the time, effort, and cognitive burden required for the analysis. This would help to obviate the objections to the adoption of QFD as a product design aid and improve the efficiency of its use in practice.
  • Han, S., Yun, M., Kim, K., and Kwahk, J., "Evaluation of product usability: development and validation of usability dimensions and design elements based on empirical models," International Journal of Industrial Ergonomics, Vol. 26, 477-488, 2000.

    Abstract

  • Kim, K. and Lin, D., "Simultaneous Optimization of Mechanical Properties of Steel by Maximizing Exponential Desirability Functions," Applied Statistics (Journal of the Royal Statistical Society - Series C), Vol. 49, 311-325, 2000.

    Abstract

    Usability defined in this study consists of the following two groups of dimensions: objective performance and subjective image/impression, which are considered equally important in designing and evaluating consumer electronic products. This study assumes that the degree of each usability dimension can be estimated by the design elements of the products. A total of 48 detailed usability dimensions were identified and defined in order to explain the usability concept applicable to the consumer electronic products. The user interface of the consumer electronic products was decomposed into specific design elements (defined as human interface elements: HIEs). A total of 88 HIEs were measured for 36 products by using a measurement checklist developed in this study. In addition, each usability dimension was evaluated by using the modified free modulus method. Multiple linear regression techniques were used to model the relationship between the usability and the design elements. As a result, 33 regression models were developed. The models are expected to help the designers not only identify important design variables but also predict the level of usability of a specific consumer electronic product. The approach used in this study is expected to provide an innovative and systematic framework for enhancing the usability of the consumer electronic products as well as other consumer products with minor modifications.
  • Kim, K., Moskowitz, H., Dhingra, A., and Evans, G., "Fuzzy Multicriteria Models for Quality Function Deployment," European Journal of Operational Research, Vol. 121, No. 3, 504-518, 2000.

    Abstract

    A modeling approach to optimize a multiresponse system is presented. The approach aims to identify the setting of the input variables to maximize the degree of overall satisfaction with respect to all the responses. An exponential desirability functional form is suggested to simplify the desirability function assessment process. The approach proposed does not require any assumptions regarding the form or degree of the estimated response models and is robust to the potential dependences between response variables. It also takes into consideration the difference in the predictive ability as well as relative priority among the response variables. Properties of the approach are revealed via two real examples - one classical example taken from the literature and another that the authors have encountered in the steel industry.
  • Kwon, H., Kim, K., and Chandra, J., "An Economic Selective Assembly Procedure for Two Mating Components with Equal Variance," Naval Research Logistics, Vol. 46, 809-821, 1999.

    Abstract

    An economic procedure of selective assembly is proposed when a product is com- posed of two mating components. The major quality characteristic of the product is the clearance between the two components. The components are divided into several classes prior to assembly. The component characteristics are assumed to be independently and normally distributed with equal variance. The procedure is designed so that the proportions of both components in their corresponding classes are the same. A cost model is developed based on a quadratic loss function and methods of obtaining the optimal class limits as well as the optimal number of classes are provided. Formulas for obtaining the proportion of rejection and the unavailability of mating components are also provided. The proposed model is compared with the equal width and the equal area partitioning methods using a numerical example.
  • Phillips, P. and Kim, K., "Taguchi Parameter Design with Multiple Quality Characteristics Using Desirability Functions with MSE," Quality Management Journal, Vol. 6, No. 4, 26-40, 1999.

    Abstract

    Taguchi parameter design is used extensively in industry to determine the optimal set of process parameters necessary to produce a product that meets or exceeds customer expectations of performance while minimizing performance variation. The majority of research in Taguchi parameter design has concentrated on approaches to optimize process parameters based on experimental observation of a single quality characteristic. This paper develops a statistical method, the DMT method, to evaluate and optimize multiple quality characteristic problems. The method incorporates desirability functions, a performance statistic based on the mean squared error, and data-driven transformations to provide a systematic approach that is adjustable to variety of situations and easy for non-experts to apply. This paper presents the DMT method in a step-by-step format and applies the method to tow examples to illustrate its applicability to a variety of parameter design problems.
  • Yun, M., Han, S., Kim, K., and Han, S., "Measuring Customer Perceptions on Product Usability: A Selection and Screening Process to Determine Critical Design Variables Using the Data from Consumer Preference Survey," The Japanese Journal of Ergonomics, Vol. 35, No. 2, 40-43, 1999.

    Abstract

  • Kim, K. and Lin, D., "Dual Response Surface Optimization: A Fuzzy Modeling Approach," Journal of Quality Technology, Vol. 30, No. 1, 1-10, 1998.

    Abstract

    In modern quality engineering, dual response surface methodology is a powerful tool. In this paper, we introduce a fuzzy modeling approach to optimize the dual response system. We demonstrate our approach in two examples and show the advantages of our method by comparing it with existing methods.
  • Park, T. and Kim, K., "Determination of an Optimal Set of Design Requirements Using House of Quality," Journal of Operations Management, Vol. 16, No. 5, 569-581, 1998.

    Abstract

    Quality Function Deployment (QFD) has been used to translate customer needs and wants into technical design requirements in order to increase customer satisfaction. QFD utilizes the house of quality (HOQ), which is a matrix providing a conceptual map for the design process, as a construct for understanding Customer Requirements (CRs) and establishing priorities of Design Requirements (DRs) to satisfy them. Some methodological issues occurring in the conventional HOQ are discussed, and then a new integrative decision model for selecting an optimal set of DRs is presented using a modified HOQ model. The modified HOQ prioritization procedure employs a multi-attribute decision method for assigning relationship ratings between CRs and DRs instead of a conventional relationship rating scale, such as 1-3-9. The proposed decision model has been applied to an indoor air quality improvement problem as an illustrative example.
  • Shin, J., Fong, D., and Kim, K., "Complexity Reduction of a House of Quality Chart Using Correspondence Analysis," Quality Management Journal, Vol. 5, No. 4, 46-58, 1998.

    Abstract

    This article presents a model for determining the composition of a United States peacekeeping force deployed to Bosnia. The model, which is loosely based on Quality Function Deployment (QFD), uses three matrices in series to relate the interests of stakeholders involved in the conict to the composition of the US force deployed in Bosnia. In addition, we have used AHP to determine the weighted importance of various stakeholders and the intensity of the relationship between the variables involved in the model. The recommendations of the model are more or less validated by the actual force composition currently deployed in Bosnia. The advantage of the model is to add "fine tuning" and precision to an otherwise ad hoc decision making process concerning the deployment of armed forces. The model can be used in other force composition planning scenarios.
  • Moskowitz, H. and Kim, K., "QFD Optimizer: A Novice Friendly Quality Function Deployment Decision Support System for Optimizing Product/Service Designs," Computers and IE, Vol. 32, No. 3, 641-655, 1997.

    Abstract

    A novice-friendly decision support system prototype for quality function deployment (QFD) called QFD Optimizer is developed based upon an integrated mathematical programming formulation and solution approach. QFD Optimizer not only helps a design team build a house of quality chart, but also supports them in understanding and analyzing the system interrelationships, as well as obtaining optimal target engineering characteristic values. QFD Optimizer was tested experimentally and in a real design setting on students and practitioners to ascertain its potential viability and effectiveness. The results suggest that it has the potential to help users find improved feasible designs yielding higher customer satisfaction (i.e., improving quality of design) more rapidly (i.e., reduce the design cycle time), compared with the current manual, ad hoc approach, QFD Optimizer can be used by novice as well as expert users, and leads to a better understanding of complex interrelationships between customer needs and the engineering characteristics and among the engineering characteristics. Hence, it can and has been used as an effective quality improvement training tool, and shows promise for application in practice.
  • Shin, J. and Kim, K., "Restructuring a House of Quality Using Factor Analysis," Quality Engineering, Vol. 9, No. 4, 739-746, 1997.

    Abstract

    Keywords: Quality Function Deployment; Product Design Chracteristics; Factor Analysis
  • Kim, K., "Determining Optimal Design Characteristic Levels in QFD," Quality Engineering, Vol. 10, No. 2, 295-307, 1997.

    Abstract

    Keywords: Quality Function Deployment; Target Design Chracteristics; Optimization; Spreadsheet
  • Kim, K. and Chen, H., "A Comparison of Fuzzy and Nonparametric Linear Regression," Computers and Operations Research, Vol. 24, No. 6, 505-519, 1997.

    Abstract

    Nonparametric linear regression and fuzzy linear regression have been developed based on different perspectives and assumptions, and thus there exist conceptual and methodological differences between the two approaches. This article describes their comparative characteristics such as basic assumptions, parameter estimation, and applications, and then compares their predictive and descriptive performances by a simulation experiment to identify the conditions under which one method performs better than the other. The experimental results indicate that nonparametric linear regression is superior to fuzzy linear regression in predictive capability, whereas their descriptive capabilities depend on various factors. When the size of the data set is small, error terms have small variability, or when the relationships among variables are not well specified, fuzzy linear regression outperforms nonparametric linear regression with respect to descriptive capability. The conditions under which each method can be used as a viable alternative to the conventional least squares regression are also identified. The findings of this article would be useful in selecting the proper regression methodology to employ under specific conditions for descriptive and predictive purposes.
  • Kim, K., Moskowitz, H., and Koksalan, M., "Fuzzy Versus Statistical Linear Regression," European Journal of Operational Research, Vol. 92, 417-434, 1996.

    Abstract

    Statistical linear regression and fuzzy linear regression have been developed from different perspectives, and thus there exist several conceptual and methodological differences between the two approaches. The characteristics of both methods, in terms of basic assumptions, parameter estimation, and application are descried and contrasted. Their descriptive and predictive capabilities are also compared via a simulation experiment to identify the conditions under which one outperforms the other. It turns out that statistical linear regression is superior to fuzzy linear regression in terms of predictive capability, whereas their comparative descriptive performance depends on various factors associated with the data set (size, quality) and proper specificity of the model (aptness of the model, heteroscedasticity, autocorrelation, nonrandomness of error terms). Specifically, fuzzy linear regression performance becomes relatively better, vis-vis statistical linear regression, as the size of the data set diminishes and the aptness of the regression model deteriorates. Fuzzy linear regression may thus be used as a viable alternative to statistical linear regression in estimating regression parameters when the data set is insufficient to support statistical regression analysis and/or the aptness of the regression model is poor (e.g., due to vague relationship among variables and poor model specification).
  • Moskowitz, H. and Kim, K., "On Assessing the H Value in Fuzzy Linear Regression," Fuzzy Sets and Systems, Vol. 58, 303-327, 1993.

    Abstract

    There are certain circumstances under which the application of statistical regression is not appropriate or even feasible because it makes rigid assumptions about the statistical properties of the model. Fuzzy regression, a nonparametric method, can be quite useful in estimating the relationships among variables where the available data are very limited and imprecise, and variables are interacting in an uncertain, qualitative, and fuzzy way. Thus, it may have considerable practical applications in many management and engineering problems. In this paper, the relationship among the H value, membership function shape, and spreads of fuzzy parameters in fuzzy linear regression is determined, and the sensitivity of the spread with respect to the H value and membership function shape is examined. The spread of a fuzzy parameter increases as a higher value of H and/or a decreasingly concave or increasingly convex membership function is employed. By utilizing the relationship among the H value, membership function, and spreads of the fuzzy parameters, a systematic approach to assessing a proper H parameter value is also developed. the approach developed and illustrated enables a decision maker's beliefs regarding the shape and range of the possibility distribution of the model to be reflected more systematically, and consequently should yield more reliable and realistic results from fuzzy regression. The resulting regression equations could, for example, also be used as constraints in a fuzzy mathematical optimization model, such as in quality function deployment.
  • Domestic
  • 배영목, 김민준, 김광재, 전치혁, 변상수, 박개명 "다변량 관리도를 활용한 선박 메인 엔진의 이상 관리 상한선 결정에 관한 연구,"대한조선학회지, Vol. 55, No. 6, 505-513, 2018.

    Abstract

    Main engine failures in ship operations can lead to a major damage in terms of the vessel itself and the financial cost. In this respect, condition monitoring of a vessel’s main engine condition is crucial in ensuring the vessel's performance and reducing the maintenance cost. The collection of a huge amount of vessel operational data in the maritime industry has never been easier with the advent of advanced data collection technologies. Real-time monitoring of the condition of a vessel’s main engine has a potential to create significant value in maritime industry. This study presents a case study on the establishment of upper control limit to detect vessel’s main engine failures using multivariate control chart. The case study uses sample data of an ocean-going vessel operated by a major marine services company in Korea, collected in the period of 2016.05-2016.07. This study first reviews various main engine-related variables that are considered to affect the condition of the main engine, and then attempts to detect abnormalities and their patterns via multivariate control charts. This study is expected to help to enhance the vessel’s availability and provide a basis for a condition-based maintenance that can support proactive management of vessel’s main engine in the future.
  • 김민준, 임치현, 이창호, 김광재, 전진우, 박용성 "운전자의 위험운전 행동 분석을 통한 시내버스 안전운전 지원 서비스 기회 도출,"대한산업공학회지, Vol. 41, No. 5, 499-510, 2015.

    Abstract

    The purpose of this research is to identify new service opportunities for enhancing driving safety of intra-city buses based on driving behavior analysis. Service opportunity identification involves finding target customers of service (to whom), motivations for service (why), service contents (what), and service delivery process (when, where). This paper presents an analysis of driving behaviors using the operational data of intra-city buses in conjunction with traffic accident data and drivers’ driving history data. This paper also presents four identified service opportunities based on the data analysis results. This research would contribute to enhancing driving safety of intra-city buses in Korea and serve as a basis for developing new services for driving safety enhancement.
  • 이동희, 정인준, 김광재, "쌍대반응표면최적화의 방법론 및 응용: A Literature Review," 대한산업공학회지, Vol. 39, No. 5, 341-350, 2013.

    Abstract

    Dual response surface optimization (DRSO), inspired by Taguchi’s philosophy, attempts to optimize the process mean and variability by using response surface methodology. Researches on DRSO were extensively done in 1990’s and have been matured recently. This paper reviews the existing DRSO methods from the decision making perspective. More specifically, this paper classifies the existing DRSO methods based on the optimization criterion and the timing of preference articulation. Also, some of case studies are reviewed. Extension to multiresponse optimization, triple response surface optimization, and application of data mining method are suggested as future research issues.
  • 김진민, 박진수, 박광태, 김광재, 홍유석, "제품-서비스 통합시스템(Product-Service System)에서의 수익분배모형," 한국경영과학회지, Vol. 36, No. 4, 81-89, 2011.

    Abstract

    In recent business environments, the competition among firms is shifting from the competition based on individual firm only to the competition based on alliance of firms. This is because it is not easy for a firm to perform all functions which consumers want. Thus, it is more effective to combine core competencies of different firms based on a strategic partnership. It is essential to establish a strategic partnership and this strategic partnership is a key success factor in PSS(Product-Service System) which combines products and services. In this paper, we propose a profit sharing model for PSS partnership. We first analyze customer's utility using Cobb-Douglas utility function and then propose the PSS profit sharing ratio considering functionalities and cost structures based on the combination ratio of PSS. This paper helps firms to develop partnership strategies for PSS.
  • 김광재, 홍유석, 박광태, 임치현, 허준연, 강창묵, 백민정, 박근완, "제품-서비스 통합시스템: 현황 및 연구방향," 대한산업공학회지, Vol. 37, No. 3, 234-247, 2011.

    Abstract

    Product-service system (PSS) is a novel type of business model integrating products and services in a single system. It provides a strategic alternative to product-oriented economic growth and price-based competition in the global market. This paper first reviews the current status of PSS, including its concept, characteristics, benefits, and cases. This paper then reviews the existing literature and identifies major research issues for three main phases of a PSS development lifecycle, namely, PSS design, PSS evaluation, and PSS operation. This research is expected to contribute to promoting awareness and improving understanding of PSS in our society and planning of future research in this field.
  • 강창묵, 홍유석, 김광재, 박광태, "제품-서비스-시장참여자의 에코시스템 분석을 위한 관계 기반 모델 개발," 대한산업공학회지, Vol. 37, No. 1, 41-54, 2011.

    Abstract

    A central theme in recent IT (information technology) industry is a mobile ecosystem. While a concept of business ecosystem, which is an economic community of firms and individuals producing and consuming goods and services, has been around for about 20 years now, the recent spotlight is mainly caused by the enormous success of iPhone. Many hand-set makers or platform developers want to mimic Apple's iPhone ecosystem from which both application developers and hand-set users can benefit. In this study, a representation model of the business ecosystem is proposed for supporting systematic design and analysis of ecosystems. Whereas previous studies also proposed some representation models, they emphasized only on the value chain between participating players. The proposed model, which is named relation-based ecosystem model, represents an ecosystem with the requirement relationships between product and service components and the roles of players, as well as their value chain. Such comprehensive representation explicitly reveals the strategic difference between ecosystems. This advantage was illustrated by comparing a Korean traditional mobile ecosystem and an emerging smart-phone ecosystem represented by the proposed model.
  • 김진민, 왕지영, 박광태, 김광재, 홍유석, "제품-서비스 통합 성공요인에 대한 연구," 경영교육연구, Vol. 13, No. 3, 31-58, 2010.

    Abstract

    Modern industrialized economies have been dominated by service sector industries. In this regards, the portion of service sector in industry is growing faster recently. According to this movement, manufacturers try to combine the intangible service with their existing tangible products to fulfill specific customer needs. It has been called as concepts of "servitization" or "Product-Service System(PSS)." In other words, manufacturers are facing new opportunities that lead them to maintain sustainable competitive advantage. Companies should also attempt to utilize "service innovation" constantly for creating new services or improving existing services in order to satisfy the unique needs of customers. The objective of this study is to find the key success factors of four companies which did successful service innovation. First, this paper introduces the concept of Product-Service Systems and servitizaiton and presents four companies based on classification framework of Shumenner's service process matrix. Second, this paper analyzes four business models of companies through the binding platform of buyer utility map and value curve. Finally, this paper derives common and unique key success factors from four business models for creating new added value sources, competitive edge and sustainability.
  • 김광재, 홍유석, 신동민, 조남욱, 정재윤, 이연희, 박하영, 홍정완, 강완모, 신하용, "서비스 혁신 연구 : 프레임워크와 연구이슈," 대한산업공학회지, Vol. 35, No. 4, 226-247, 2009.

    Abstract

    The competitiveness of the service sector is driven by its productivity. Services innovation is essential to enhancing service productivity. This paper first presents a framework for services innovation. The framework consists of three main phases of a service lifecycle (namely, service development, service operation, and service improvement), which are supported by IT infrastructure and service RnD management functions. This paper then identifies major research issues that should be investigated in the near future. The current issues of three representative service industries (namely, healthcare service, telecommunications service, and financial service) are also discussed
  • 임현민, 김광재, 유재형, "QFD 방법론에 의한 IPTV 서비스 품질 핵심 요소 도출 및 분석," KNOM Review, Vol. 11, No. 1, 56-74, 2008.

    Abstract

    IPTV 시장 성장과 더불어 사용자 단말 기술 발달 및 사용자의 서비스 요구사항 증대로 인한 IPTV 환경 변화가 가속화 되고 있으며 이러한 환경 변화에 대응하기 위하여 IPTV 서비스에 대한 품질 관리 요소를 도출하고 지속적인 관리를 통하여 고객 체감 품질 만족도를 제고해야 한다. IPTV 서비스의 본원적 QoE(Quality of Experience)에 대한 전반적 향상을 위해서는 QoE, QoS(Quality of Service), NP(Network Performance)의 전반적 향상이 요구되는데 한정적 자원으로 최대의 효과를 얻기 위해서는 각 품질 요소를 구성하는 항목 중 영향도가 큰 항목들을 우선적으로 향상시키고 관리하는 것이 중요하다. 본 논문에서는 IPTV 품질 요소를 구성하는 항목 중 영향도가 큰 항목을 IPTV 서비스 품질 핵심 요소라 정의하고 이를 도출하기 위해 QFD(Quality Function Deployment) 방법론을 적용한 사례와 그 결과로 도출된 IPTV 서비스 품질 핵심 요소를 기술하고 IPTV 서비스 품질 핵심 요소 간 상관 관계 및 인과 관계를 도출하여 분석한다.
  • 박양병, 임석철, 홍성조, 김광재, 윤명환, 김종화, 이덕주, 조남욱, 서영보, "산업공학 학부교육의 탐색: 졸업생 설문조사 결과를 중심으로," IE Interfaces, Vol. 20, No. 1, 1-10, 2007.

    Abstract

    The main purpose of this research is to find out whether curriculums of industrial engineering (IE) departments meet the demand of IE graduates working in various fields. The research was conducted as an online questionnaire survey selecting IE Graduates working in industries as practising engineers. 1,324 participants were validated among 1,477 participants. 13 fields were selected and used in the survey. Those were; 1) Mathematical statistics, 2) Computer, 3) Purchase, 4) Production system, 5) Logistics, 6) Marketing, 7) Monetary, 8) Experiment methods, 9) Operations Research (OR), 10) Human Factors, 11) Quality, 12) Engineering management, and 13) Information systems. Using the 5-scale Likert rating, each education subject was assessed both in terms of its usefulness in practices and the amount it being taught in school. As a result, courses such as motion/time study, linear programming that IE has traditionally focused showed less usefulness in practices while it is taught in relatively large amount in schools. However, courses such as 6 sigma, CRM which are closely related to industrial practices showed high usefulness in practices compared with low degree of teaching in school. This was the first ever large scale survey conducted for IE graduates in Korea. The result of survey displayed many helpful information on current status and future direction of IE education in Korea.
  • 김광재, 민대기, 육진범, 박정석, 이지형, 최재경, 류경석, "고객 중심의 컨버전스 서비스 컨셉 개발: 절차 체계 및 통신 컨버전스 서비스 사례 연구," IE interfaces, Vol. 19, No. 2, 140-152, 2006.

    Abstract

    Today, many companies realize that the effort to develop new products/services faster that customers want and continue to purchase is crucial for their survival. As the service sector is rapidly growing, one of the challenges faced by the service industries is the lack of effective methodologies for new service development. This paper proposes a systematic framework for developing new service concepts, with an emphasis on generating innovative, convergence-type service concepts from the customer's perspective. The framework consists of three phases ? identification of customer needs (Phase I), extraction of new service opportunities (Phase II), and generation of new service concepts (Phase III). The proposed framework is demonstrated through a case study in the telecommunications industry. In the case study, a survey was conducted on ten customers to identify the latent customer needs; 61 new service opportunities were extracted; and 129 new service concepts were generated.
  • 김광재, 육진범, 김광수, "BPM 기반의 6 시그마: 개념 및 절차 모델," 대한산업공학회지, Vol. 32, No. 4, 314-322, 2006.

    Abstract

    Despite its brilliant success, Six Sigma has suffered from two shortcomings, namely, the lack of a systematic method to identify the right projects in the "Define" stage and to sustain the improvement in the "Control" stage. The integration of Six Sigma and Business Process Management(BPM) seems to be a promising way to overcome the shortcomings of Six Sigma. This paper first reviews the existing efforts on this issue, and then proposes a framework for an effective integration of Six Sigma and BPM. The framework consists of five phases - DEFINE, EXECUTE, MONITOR, ANALYZE, and IMPROVE(DEMAI). A detailed description on the procedural model is also presented.
  • 이명수, 김광재, "통계적 공정 관리(SPC)와 엔지니어링 공정 관리(EPC)의 비교 조사: 통합 방안을 중심으로," 품질경영학회지, Vol. 33, No. 1, 22-31, 2005.

    Abstract

    With the common objective to improve process productivity and product quality, statistical process control (SPC) and engineering process control (EPC) have been widely used in the discrete-parts industry and the process industry, respectively. The major focus of SPC is on process monitoring, while that of EPC is on process adjustment. The emergence of the hybrid industry necessitates a synergistic combination of the two methods for an effective process control. This paper investigates the existing studies on SPC, EPC, and the integration of the two methods. This paper also presents future research issues in this field.
  • 권준범, 이종석, 이상호, 전치혁, 김광재, "공정변수 변동을 고려한 호감도 함수를 통한 다중반응표면 최적화," 한국경영과학회지, Vol. 30, No. 1, 95-104, 2005.

    Abstract

    A desirability function approach to a multiresponse problem is proposed considering process parameter fluctuation which may amplify the variance of response. It is called POE(propagation of error), which is defined as the standard deviation of the transmitted variability in the response as a function of process parameters. In order to obtain more robust process parameter setting, a new desirability function is proposed by considering POE as well as distance-to-target of response and response variance. The proposed method is illustrated using a rubber product case in Ribeiro et al. (2000).
  • 권준범, 이종석, 이상호, 전치혁, 김광재, "공정변수의 변동을 고려한 만족도 함수를 통한 다중반응표면 최적화," 대한산업공학회지, Vol. 31, No. 2, 164-172, 2005.

    Abstract

    A desirability function approach to a multiresponse problem is proposed considering process parameter fluctuation as well as distance-to-target of response and response variance. The variation of process parameters amplifies the variance of responses. It is called POE (propagation of error), which is defined as the standard deviation of the transmitted variability in the response as a function of process parameters. In order to obtain more robust process parameters, this variability should be considered in the optimization problem. The proposed method is illustrated using a rubber product case.
  • 김광재, 민대기, 김덕환, 최봉, 이팔훈, 이승현, "DFSS/C의 CTQ 후보 체계적인 도출을 위한 체계적 방법론 연구," 품질경영학회지, Vol. 33, No. 2, 74-86, 2005.

    Abstract

    The project objectives, called critical-to-quality (CTQs) in six sigma, should be defined to faithfully reflect the customer requirements. The identification of such a set of CTQs, which is currently done using brainstorming in practice, is a challenging task. Notwithstanding the rapid growth of the six sigma literature, development of a systematic procedure for identifying CTQs has scarcely been addressed. This paper proposes a systematic method for generating CTQ candidates based on the given voice of the customer in the DFSS/C (Design for Six Sigma / Commercial) context. By providing a stepby- step procedure, the proposed method ensures that all the important CTQ candidates are identified and subjective judgments are minimally required. Hence, the shortcomings associated with the existing practice based on brainstorming can be effectively overcome. The unique characteristics of the proposed method are also demonstrated via a case study.
  • 류태범, 오경희, 유희천, 윤명환, 김광재, "설계변수의 통계적, 기술적, 실질적 측면을 고려한 자동차 내장 재질의 만족도 모형의 개발," IE Interfaces, Vol. 17, No. 4, 482-489, 2004.

    Abstract

    As the functional characteristics of passenger cars have reached to a satisfactory level, customers place more concerns with the aesthetic aspects of interior designs. The present study developed satisfaction models of passenger car interior materials for six parts including crash pad, steering wheel, transmission gearshift knob, audio panel, metal grain, and wooden grain. Eight to fifteen material design variables such as color, embossing, and smoothness were defined for the six interior parts based on literature survey, customer reviews, and expert opinions. A satisfaction survey was conducted for 30 vehicles with 30 participants (mean+-SD of age=28.7+-6.6) by using a modified magnitude estimation scale. Based on the survey results, the material design variables were screened from statistical, technical, and practical aspects. With the screened variables, satisfaction models were developed by using the quantification I method for the six interior parts, indicating the importance of material design variables and preferred material properties.
  • 류태범, 정인준, 유희천, 김광재, "가상 환경상의 인간공학적 제품설계를 위한 인체모델군 생성기법 개발 및 적용," IE Interface, Vol. 16, No. 5, 144-148, 2003.

    Abstract

    A group of digital human models with various sizes which properly represents a population under consideration is needed in the design process of an ergonomic product in virtual environment. The present study proposes a two-step method which produces a representative group of human models in terms of stature and weight. The proposed method first generates a designated number of pairs of stature and weight within an accommodation range from the bivariate normal distribution of stature and weight of the target population. Then, from each pair of stature and weight, the method determines the sizes of body segments by using 'hierarchical' regression models and corresponding prediction distributions of individual values. The suggested method was applied to the 1988 US Army anthropometric survey data and implemented to a web-based system which generates a representative group of human models for the following parameters: nationality, gender, accommodation percentage, and number of human models.
  • 임정훈, 민대기, 김광재, "Kano 모형에 기반한 소비자 요구사항 분류: 퍼지 접근방법," 품질경영학회지, Vol. 31, No. 3, 98-113, 2003.

    Abstract

    Kano model distinguishes three types of customer requirements, namely, one-dimensional quality, must-be quality, and attractive quality. There are a few methods for classifying a given customer requirement into one of the Kane's quality elements. However, the existing methods have a common limitation in that they are based on Kano evaluation table. Kano evaluation table is not always effective for the classification task, and suffers from a significant information loss. This paper proposes an alternative to Kano's evaluation table and a new classification scheme based on fuzzy set concept. The proposed method is illustrated using a case study on the ADSL service.
  • 김광재, 조현우, 이승식, 안혜린, 이동욱, 정인준, "e-business 시대의 품질공학," 대한산업공학회지, Vol. 31, No. 3, 98-113, 2001.

    Abstract

    The research in the field of quality engineering has mainly focused on the manufactured products. The philosophy and concept of the existing quality engineering should be equally applicable in the coming e-Business era. However, there would be numerous new quality-related issues in the e-Business environment, due to the fundamental change in the business processes, which did not exist in the past. This paper first proposes a framework for quality engineering research suited for the e-Business environment, and then identifies major quality-related issues that should be resolved in the near future. It also evaluates the potential usefulness and limitations of the existing quality engineering tools in resolving such issues.
  • 권혁무, 김광재, "짝이 되는 두 부품의 경제적 선택조립 절차," 한국경영과학회지, Vol. 24, No. 1, 39-48, 1999.

    Abstract

    An economic procedure of selective assembly is proposed when a product is composed of two mating components. The major quality characteristic of the product is the clearance between the two components . The components are divided into several classes prior to assembly. The component characteristics are assumed to be independently and normally distributed with equal variance. The procedure is des igned so that the proportions of both components in their corresponding classes are the same. A cost model is developed based on a quadratic loss function and methods of obtaining the optimal class limits as well as the optimal number of classes are provided. Formulas for obtaining the proportion of rejection and the unavailability of mating components are also provided. The proposed model is compared with the equal width and the equal area partitioning methods us ing a numerical example.
  • 변재현, 김광재, "호감도함수 접근법을 이용한 다수품질특성치의 강건설계," 대한산업공학회지, Vol. 24, No. 2, 287-296, 1998.

    Abstract

    We often have multiple quality characteristics to develop, improve and optimize industrial processes and products. It is not easy to find optimal control factor setting when there are multiple quality characteristics, since there will be conflict among the selected levels of the control factors for each individual quality characteristic. In this paper we propose a desirability function approach and devise a scheme which gives a systematic way of solving multiple quality characteristic problems. A numerical example is provided.