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Sustainable Manufacturing Evaluation Based on Enterprise Industry 4.0 Technologies

Author

Listed:
  • Khalid A. Eldrandaly

    (Faculty of Computers and Informatics, Zagazig University, Zagazig 44519, Egypt)

  • Nissreen El Saber

    (Faculty of Computers and Informatics, Zagazig University, Zagazig 44519, Egypt)

  • Mona Mohamed

    (Higher Technological Institute, 10th of Ramadan City 44629, Egypt)

  • Mohamed Abdel-Basset

    (Faculty of Computers and Informatics, Zagazig University, Zagazig 44519, Egypt)

Abstract

Most studies in recent decades focused on transforming linear economics into circular through recovering and remanufacturing the products. Circular Economies (CE) aim to minimize the usage of resources by utilizing the waste in production as new or raw materials. Interconnectivity between parties in the industrial system provides decision-makers with rich information and anticipation of failure. Industry 4.0 technologies (I4.0) allow for handling such issues, protecting the environment by utilizing resources efficiently, and restructuring the industry to be smarter as well. This paper contributes to achieving cleaner production (CP), CE, and social for manufacturers through the linkage between 6R methodology with new technologies of I4.0 such as Blockchain technology (BCT) and big data analytical technology (BDA). In this paper, the authors proposed a Multi-criteria decision-making (MCDM) decision framework based on the best-worst method (BWM), Decision-Making trial and evaluation laboratory (DEMATEL), Technique for order of preference by similarity to ideal solution (TOPSIS), and Complex Proportional Assessment (COPRAS). The authors contributed to addressing the weaknesses and problems of these subjective MCDM methods through the cooperation of the neutrosophic theory with the usage of MCDM methods in this work. In the first stage, all criteria that influence sustainable manufacturer selection are specified using literature research on this topic. BWM-based neutrosophic theory was combined to get the criteria’s weights with the aid of DEMATEL-based neutrosophic to obtain the least and best criteria used in BWM in the second stage. The optimal sustainable manufacturer was selected based on TOPSIS and COPRAS under neutrosophic theory in the third and fourth stages, respectively. Furthermore, a case study performed indicated manufacturer 2 (A 2 ) is an optimal sustainable manufacturer in two ranking methods otherwise, manufacturer 4 (A 4 ) is the worst sustainable manufacturer. The contribution of this work is to propose a hybrid MCDM with an uncertainty theory of neutrosophic for sustainable manufacturer selection based BDA-BCT with 6R. Sensitivity analyses were carried out to show the decision’s flexibility in various scenarios. Finally, the consequences for management viewpoints were considered.

Suggested Citation

  • Khalid A. Eldrandaly & Nissreen El Saber & Mona Mohamed & Mohamed Abdel-Basset, 2022. "Sustainable Manufacturing Evaluation Based on Enterprise Industry 4.0 Technologies," Sustainability, MDPI, vol. 14(12), pages 1-22, June.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:12:p:7376-:d:840443
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    References listed on IDEAS

    as
    1. Chris Turner & Mariale Moreno & Luigi Mondini & Konstantinos Salonitis & Fiona Charnley & Ashutosh Tiwari & Windo Hutabarat, 2019. "Sustainable Production in a Circular Economy: A Business Model for Re-Distributed Manufacturing," Sustainability, MDPI, vol. 11(16), pages 1-19, August.
    2. Sundarakani, Balan & Ajaykumar, Aneesh & Gunasekaran, Angappa, 2021. "Big data driven supply chain design and applications for blockchain: An action research using case study approach," Omega, Elsevier, vol. 102(C).
    3. Edvard Tijan & Saša Aksentijević & Katarina Ivanić & Mladen Jardas, 2019. "Blockchain Technology Implementation in Logistics," Sustainability, MDPI, vol. 11(4), pages 1-13, February.
    4. Yildizbasi, Abdullah, 2021. "Blockchain and renewable energy: Integration challenges in circular economy era," Renewable Energy, Elsevier, vol. 176(C), pages 183-197.
    5. Konrad Zimmer & Magnus Fröhling & Frank Schultmann, 2016. "Sustainable supplier management -- a review of models supporting sustainable supplier selection, monitoring and development," International Journal of Production Research, Taylor & Francis Journals, vol. 54(5), pages 1412-1442, March.
    6. Mahtab Kouhizadeh & Joseph Sarkis, 2018. "Blockchain Practices, Potentials, and Perspectives in Greening Supply Chains," Sustainability, MDPI, vol. 10(10), pages 1-16, October.
    7. Dragan Pamučar & Fatih Ecer & Goran Cirovic & Melfi A. Arlasheedi, 2020. "Application of Improved Best Worst Method (BWM) in Real-World Problems," Mathematics, MDPI, vol. 8(8), pages 1-19, August.
    8. Rezaei, Jafar, 2016. "Best-worst multi-criteria decision-making method: Some properties and a linear model," Omega, Elsevier, vol. 64(C), pages 126-130.
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    1. Walter Cardoso Satyro & Jose Celso Contador & Sonia Francisca de Paula Monken & Anderson Ferreira de Lima & Gilberto Gomes Soares Junior & Jansen Anderson Gomes & João Victor Silva Neves & José Robert, 2023. "Industry 4.0 Implementation Projects: The Cleaner Production Strategy—A Literature Review," Sustainability, MDPI, vol. 15(3), pages 1-18, January.

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