IDEAS home Printed from https://ideas.repec.org/a/spr/joinma/v32y2021i4d10.1007_s10845-020-01604-y.html
   My bibliography  Save this article

A credit-based dynamical evaluation method for the smart configuration of manufacturing services under Industrial Internet of Things

Author

Listed:
  • Wang Shijie

    (Northwestern Polytechnical University)

  • Zhang Yingfeng

    (Northwestern Polytechnical University)

Abstract

Most scheduling problems are required to follow rigid metrics, such as the maximum completion time, earliest deadline first, etc., ignoring the flexibility of manufacturing services (MSs) and the effects of their historical data hidden in millions of manufacturing activities. The historical data serves as a powerful basis for describing the comprehensiveness or credibility of the MS itself with the help of Industrial IoT enabling all equipment to communicate and take preventive actions. Similar to the bank credit for individuals, MSs should also have their own referential credit values when choosing the most suitable service for a specific manufacturing task. This paper summarizes the MS attributes from six aspects with sufficient sub-attributes. The fuzzy Analytic Network Process combined with the Cross-Entropy method is employed to evaluate the credit of MSs in the complex manufacturing network system. Such service scoring mechanism (SSM) can personify a comprehensive credit evaluation of services, where, a smart service configuration mode based on credit is proposed for carrying out the supply–demand matching with the help of the data-security technology. Subsequently, a credit-based manufacturing mode is derived under SSM. Numerical examples are carried out to demonstrate the validity of the matching mode. The result may assist manufacturers to allocate their manufacturing tasks in real time in a “credit” way and make quicker decisions in exceptional circumstances, while making the chosen service truly competent enough to finish the work, so as to further improve the customer satisfaction.

Suggested Citation

  • Wang Shijie & Zhang Yingfeng, 2021. "A credit-based dynamical evaluation method for the smart configuration of manufacturing services under Industrial Internet of Things," Journal of Intelligent Manufacturing, Springer, vol. 32(4), pages 1091-1115, April.
    • Handle: RePEc:spr:joinma:v:32:y:2021:i:4:d:10.1007_s10845-020-01604-y
    DOI: 10.1007/s10845-020-01604-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10845-020-01604-y
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10845-020-01604-y?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Chan, Felix T.S. & Kumar, Niraj, 2007. "Global supplier development considering risk factors using fuzzy extended AHP-based approach," Omega, Elsevier, vol. 35(4), pages 417-431, August.
    2. Seong-Kyu Kim & Ung-Mo Kim & Jun-Ho Huh, 2019. "A Study on Improvement of Blockchain Application to Overcome Vulnerability of IoT Multiplatform Security," Energies, MDPI, vol. 12(3), pages 1-29, January.
    3. Yulin Wang & Yongping Zhang & Fei Tao & Tingyu Chen & Ying Cheng & Shunkun Yang, 2019. "Logistics-aware manufacturing service collaboration optimisation towards industrial internet platform," International Journal of Production Research, Taylor & Francis Journals, vol. 57(12), pages 4007-4026, June.
    4. Judd Cramer & Alan B. Krueger, 2016. "Disruptive Change in the Taxi Business: The Case of Uber," American Economic Review, American Economic Association, vol. 106(5), pages 177-182, May.
    5. Yang-Kuei Lin & Chin Soon Chong, 2017. "Fast GA-based project scheduling for computing resources allocation in a cloud manufacturing system," Journal of Intelligent Manufacturing, Springer, vol. 28(5), pages 1189-1201, June.
    6. Yongkui Liu & Lihui Wang & Xi Vincent Wang & Xun Xu & Lin Zhang, 2019. "Scheduling in cloud manufacturing: state-of-the-art and research challenges," International Journal of Production Research, Taylor & Francis Journals, vol. 57(15-16), pages 4854-4879, August.
    7. Jiewu Leng & Pingyu Jiang, 2019. "Dynamic scheduling in RFID-driven discrete manufacturing system by using multi-layer network metrics as heuristic information," Journal of Intelligent Manufacturing, Springer, vol. 30(3), pages 979-994, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Scott Duke Kominers & Alexander Teytelboym & Vincent P Crawford, 2017. "An invitation to market design," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 33(4), pages 541-571.
    2. Wang, Wei & Miao, Wei & Liu, Yongdong & Deng, Yiting & Cao, Yunfei, 2022. "The impact of COVID-19 on the ride-sharing industry and its recovery: Causal evidence from China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 155(C), pages 128-141.
    3. Tarduno, Matthew, 2021. "The congestion costs of Uber and Lyft," Journal of Urban Economics, Elsevier, vol. 122(C).
    4. Xu, Zhengtian & Yin, Yafeng & Zha, Liteng, 2017. "Optimal parking provision for ride-sourcing services," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 559-578.
    5. Adam Millard-Ball & Liwei Liu & Whitney Hansen & Drew Cooper & Joe Castiglione, 2023. "Where ridehail drivers go between trips," Transportation, Springer, vol. 50(5), pages 1959-1981, October.
    6. Berger, Thor & Chen, Chinchih & Frey, Carl Benedikt, 2018. "Drivers of disruption? Estimating the Uber effect," European Economic Review, Elsevier, vol. 110(C), pages 197-210.
    7. Kräussl, Roman & Kräussl, Zsofia & Pollet, Joshua & Rinne, Kalle, 2024. "The performance of marketplace lenders," Journal of Banking & Finance, Elsevier, vol. 162(C).
    8. Yue Guo & Fu Xin & Xiaotong Li, 2020. "The market impacts of sharing economy entrants: evidence from USA and China," Electronic Commerce Research, Springer, vol. 20(3), pages 629-649, September.
    9. Agam Gupta & Biswatosh Saha & Parthasarathi Banerjee, 2018. "Pricing decisions of car aggregation platforms in sharing economy: a developing economy perspective," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 17(5), pages 341-355, October.
    10. Ouyang, Yao & Pedrycz, Witold, 2016. "A new model for intuitionistic fuzzy multi-attributes decision making," European Journal of Operational Research, Elsevier, vol. 249(2), pages 677-682.
    11. Lupo, Toni, 2015. "Fuzzy ServPerf model combined with ELECTRE III to comparatively evaluate service quality of international airports in Sicily," Journal of Air Transport Management, Elsevier, vol. 42(C), pages 249-259.
    12. Yingjie Zhang & Beibei Li & Ramayya Krishnan, 2020. "Learning Individual Behavior Using Sensor Data: The Case of Global Positioning System Traces and Taxi Drivers," Information Systems Research, INFORMS, vol. 31(4), pages 1301-1321, December.
    13. Blume, Maximilian & Oberländer, Anna Maria & Röglinger, Maximilian & Rosemann, Michael & Wyrtki, Katrin, 2020. "Ex ante assessment of disruptive threats: Identifying relevant threats before one is disrupted," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    14. Maria Cesira Urzi Brancati & Annarosa Pesole & Enrique Fernandez Macias, 2019. "Digital Labour Platforms in Europe: Numbers, Profiles, and Employment Status of Platform Workers," JRC Research Reports JRC117330, Joint Research Centre.
    15. Lam, Chungsang Tom & Liu, Meng & Hui, Xiang, 2021. "The geography of ridesharing: A case study on New York City," Information Economics and Policy, Elsevier, vol. 57(C).
    16. Schaefers, Tobias & Leban, Marina & Vogt, Florian, 2022. "On-demand features: Consumer reactions to tangibility and pricing structure," Journal of Business Research, Elsevier, vol. 139(C), pages 751-761.
    17. Yujie Guo & Ying Chen & Yu Zhang, 2024. "Enhancing Demand Prediction: A Multi-Task Learning Approach for Taxis and TNCs," Sustainability, MDPI, vol. 16(5), pages 1-14, March.
    18. Lee, Junmin & Kim, Keungoui & Kim, Jiyong & Hwang, Junseok, 2022. "The relationship between shared mobility and regulation in South Korea: A system dynamics approach from the socio-technical transitions perspective," Technovation, Elsevier, vol. 109(C).
    19. Bauer, Johannes M., 2018. "The Internet and income inequality: Socio-economic challenges in a hyperconnected society," Telecommunications Policy, Elsevier, vol. 42(4), pages 333-343.
    20. Wang, Xiaojun & Chan, Hing Kai & Li, Dong, 2015. "A case study of an integrated fuzzy methodology for green product development," European Journal of Operational Research, Elsevier, vol. 241(1), pages 212-223.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:joinma:v:32:y:2021:i:4:d:10.1007_s10845-020-01604-y. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.