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Design of informatics-based services in manufacturing industries: case studies using large vehicle-related databases

Author

Listed:
  • Chie-Hyeon Lim

    (Pohang University of Science and Technology)

  • Min-Jun Kim

    (Pohang University of Science and Technology)

  • Jun-Yeon Heo

    (Pohang University of Science and Technology)

  • Kwang-Jae Kim

    (Pohang University of Science and Technology)

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.

Suggested Citation

  • Chie-Hyeon Lim & Min-Jun Kim & Jun-Yeon Heo & Kwang-Jae Kim, 2018. "Design of informatics-based services in manufacturing industries: case studies using large vehicle-related databases," Journal of Intelligent Manufacturing, Springer, vol. 29(3), pages 497-508, March.
    • Handle: RePEc:spr:joinma:v:29:y:2018:i:3:d:10.1007_s10845-015-1123-8
    DOI: 10.1007/s10845-015-1123-8
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    References listed on IDEAS

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    1. Arnold Tukker, 2004. "Eight types of product–service system: eight ways to sustainability? Experiences from SusProNet," Business Strategy and the Environment, Wiley Blackwell, vol. 13(4), pages 246-260, July.
    2. Ladhari, Riadh, 2010. "Developing e-service quality scales: A literature review," Journal of Retailing and Consumer Services, Elsevier, vol. 17(6), pages 464-477.
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    Cited by:

    1. Kung-Jeng Wang & Diwanda Ageng Rizqi & Hong-Phuc Nguyen, 2021. "Skill transfer support model based on deep learning," Journal of Intelligent Manufacturing, Springer, vol. 32(4), pages 1129-1146, April.
    2. Lena Ries & Markus Beckmann & Peter Wehnert, 2023. "Sustainable smart product-service systems: a causal logic framework for impact design," Journal of Business Economics, Springer, vol. 93(4), pages 667-706, May.
    3. Lee, Changhun & Lim, Chiehyeon, 2021. "From technological development to social advance: A review of Industry 4.0 through machine learning," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    4. Pai Zheng & Xun Xu & Chun-Hsien Chen, 2020. "A data-driven cyber-physical approach for personalised smart, connected product co-development in a cloud-based environment," Journal of Intelligent Manufacturing, Springer, vol. 31(1), pages 3-18, January.
    5. Till Blüher & Theresa Riedelsheimer & Sonika Gogineni & Antje Klemichen & Rainer Stark, 2020. "Systematic Literature Review—Effects of PSS on Sustainability Based on Use Case Assessments," Sustainability, MDPI, vol. 12(17), pages 1-26, August.
    6. Liang Hou & Roger J. Jiao, 2020. "Data-informed inverse design by product usage information: a review, framework and outlook," Journal of Intelligent Manufacturing, Springer, vol. 31(3), pages 529-552, March.

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