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Method to assess the adherence of internal logistics equipment to the concept of CPS for industry 4.0

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  • Matana, Gleison
  • Simon, Alexandre
  • Filho, Moacir Godinho
  • Helleno, André

Abstract

Industry 4.0 foresees benefits to companies and is supported by technologies such as Cyber-Physical Systems (CPS), Internet of Things (IoT), Internet of Services (IoS), among others. CPS, one of Industry 4.0's key technologies, can be applied in many areas including health, mobility, production and logistics. The partial or total incorporation of CPS technologies into internal logistics equipment can present such advantages to businesses as reductions in logistics operational costs and in production cycle times. Although this application is still under development, several manufacturers already offer to the market internal logistics equipment incorporating CPS technologies, presenting them as fully capable of operating in the Industry 4.0 environment. However, it is observed that there is no effective method of assessing whether these devices effectively integrate such technologies and at what level this integration occurs. This manuscript adopted the design science research methodology to propose a method for assessing the adherence of internal logistics equipment to the CPS concept for Industry 4.0. The method is based on a guide for collecting data with questions that identify information about the CPS technologies embedded in the internal logistics equipment, associated with a tool for processing this information. The tool is supported by a properly trained artificial neural network that measures the equipment's adherence to the CPS concept. The method has proved to be adequate because in its application it assessed fifteen equipment, from worldwide-renowned manufacturers, with an error of less than 2%.

Suggested Citation

  • Matana, Gleison & Simon, Alexandre & Filho, Moacir Godinho & Helleno, André, 2020. "Method to assess the adherence of internal logistics equipment to the concept of CPS for industry 4.0," International Journal of Production Economics, Elsevier, vol. 228(C).
    • Handle: RePEc:eee:proeco:v:228:y:2020:i:c:s0925527320302115
    DOI: 10.1016/j.ijpe.2020.107845
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    References listed on IDEAS

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    1. Yavas, Volkan & Ozkan-Ozen, Yesim Deniz, 2020. "Logistics centers in the new industrial era: A proposed framework for logistics center 4.0," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 135(C).
    2. Dalenogare, Lucas Santos & Benitez, Guilherme Brittes & Ayala, Néstor Fabián & Frank, Alejandro Germán, 2018. "The expected contribution of Industry 4.0 technologies for industrial performance," International Journal of Production Economics, Elsevier, vol. 204(C), pages 383-394.
    3. Frank, Alejandro Germán & Dalenogare, Lucas Santos & Ayala, Néstor Fabián, 2019. "Industry 4.0 technologies: Implementation patterns in manufacturing companies," International Journal of Production Economics, Elsevier, vol. 210(C), pages 15-26.
    4. Chen, Serena H. & Jakeman, Anthony J. & Norton, John P., 2008. "Artificial Intelligence techniques: An introduction to their use for modelling environmental systems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 78(2), pages 379-400.
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    Cited by:

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    2. Monshizadeh, Fatemeh & Sadeghi Moghadam, Mohammad Reza & Mansouri, Taha & Kumar, Maneesh, 2023. "Developing an industry 4.0 readiness model using fuzzy cognitive maps approach," International Journal of Production Economics, Elsevier, vol. 255(C).
    3. Caiming Zhang & Yong Chen & Hong Chen & Dazhi Chong, 2024. "Industry 4.0 and its Implementation: a Review," Information Systems Frontiers, Springer, vol. 26(5), pages 1773-1783, October.
    4. Burak Eldem & Aldona Kluczek & Jan Bagiński, 2022. "The COVID-19 Impact on Supply Chain Operations of Automotive Industry: A Case Study of Sustainability 4.0 Based on Sense–Adapt–Transform Framework," Sustainability, MDPI, vol. 14(10), pages 1-32, May.
    5. Biswas, Indranil & Singh, Gurmeet & Tiwari, Sunil & Choi, Tsan-Ming & Pethe, Shivanee, 2024. "Managing Industry 4.0 supply chains with innovative and traditional products: Contract cessation points and value of information," European Journal of Operational Research, Elsevier, vol. 316(2), pages 539-555.
    6. Usama Awan & Robert Sroufe & Karoly Bozan, 2022. "Designing Value Chains for Industry 4.0 and a Circular Economy: A Review of the Literature," Sustainability, MDPI, vol. 14(12), pages 1-20, June.
    7. Virmani, Naveen & Sharma, Shikha & Kumar, Anil & Luthra, Sunil, 2023. "Adoption of industry 4.0 evidence in emerging economy: Behavioral reasoning theory perspective," Technological Forecasting and Social Change, Elsevier, vol. 188(C).

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