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A Framework for Industry 4.0 Readiness and Maturity of Smart Manufacturing Enterprises: A Case Study

Author

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  • Zeki Murat Çınar

    (Department of Mechanical Engineering, Eastern Mediterranean University, Famagusta 99628, North Cyprus via Mersin, Turkey)

  • Qasim Zeeshan

    (Department of Mechanical Engineering, Eastern Mediterranean University, Famagusta 99628, North Cyprus via Mersin, Turkey)

  • Orhan Korhan

    (Department of Industrial Engineering, Eastern Mediterranean University, Famagusta 99628, North Cyprus via Mersin, Turkey)

Abstract

Recently, researchers have proposed various maturity models (MMs) for assessing Industry 4.0 (I4.0) adoption; however, few have proposed a readiness framework (F/W) integrated with technology forecasting (TF) to evaluate the growth of I4.0 adoption and consequently provide a roadmap for the implementation of I4.0 for smart manufacturing enterprises. The aims of this study were (1) to review the research related to existing I4.0 MMs and F/Ws; (2) to propose a modular MM with four dimensions, five levels, 60 second-level dimensions, and 246 sub-dimensions, and a generic F/W with four layers and seven hierarchy levels; and (3) to conduct a survey-based case study of an automobile parts manufacturing enterprise by applying the MM and F/W to assess the I4.0 adoption level and TF model to anticipate the growth of I4.0. MM and F/W integrated with TF provides insight into the current situation and growth of the enterprise regarding I4.0 adoption, by identifying the gap areas, and provide a foundation for I4.0 integration. Case study findings show that the enterprise’s overall maturity score is 2.73 out of 5.00, and the forecasted year of full integration of I4.0 is between 2031 and 2034 depending upon the policy decisions.

Suggested Citation

  • Zeki Murat Çınar & Qasim Zeeshan & Orhan Korhan, 2021. "A Framework for Industry 4.0 Readiness and Maturity of Smart Manufacturing Enterprises: A Case Study," Sustainability, MDPI, vol. 13(12), pages 1-32, June.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:12:p:6659-:d:573194
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    References listed on IDEAS

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    1. Alexandre Moeuf & Robert Pellerin & Samir Lamouri & Simon Tamayo-Giraldo & Rodolphe Barbaray, 2018. "The industrial management of SMEs in the era of Industry 4.0," International Journal of Production Research, Taylor & Francis Journals, vol. 56(3), pages 1118-1136, February.
    2. Zeki Murat Çınar & Abubakar Abdussalam Nuhu & Qasim Zeeshan & Orhan Korhan & Mohammed Asmael & Babak Safaei, 2020. "Machine Learning in Predictive Maintenance towards Sustainable Smart Manufacturing in Industry 4.0," Sustainability, MDPI, vol. 12(19), pages 1-42, October.
    3. Adamuthe, Amol C. & Thampi, Gopakumaran T., 2019. "Technology forecasting: A case study of computational technologies," Technological Forecasting and Social Change, Elsevier, vol. 143(C), pages 181-189.
    4. Meade, Nigel & Islam, Towhidul, 1995. "Forecasting with growth curves: An empirical comparison," International Journal of Forecasting, Elsevier, vol. 11(2), pages 199-215, June.
    5. Erwin Rauch & Marco Unterhofer & Rafael A. Rojas & Luca Gualtieri & Manuel Woschank & Dominik T. Matt, 2020. "A Maturity Level-Based Assessment Tool to Enhance the Implementation of Industry 4.0 in Small and Medium-Sized Enterprises," Sustainability, MDPI, vol. 12(9), pages 1-18, April.
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    1. Julio Henrique Costa Nobrega & Izabela Simon Rampasso & Vasco Sanchez-Rodrigues & Osvaldo Luiz Gonçalves Quelhas & Walter Leal Filho & Milena Pavan Serafim & Rosley Anholon, 2021. "Logistics 4.0 in Brazil: Critical Analysis and Relationships with SDG 9 Targets," Sustainability, MDPI, vol. 13(23), pages 1-17, November.
    2. Bhatia, Purvee & Diaz-Elsayed, Nancy, 2023. "Facilitating decision-making for the adoption of smart manufacturing technologies by SMEs via fuzzy TOPSIS," International Journal of Production Economics, Elsevier, vol. 257(C).
    3. Latino, Maria Elena, 2025. "A maturity model for assessing the implementation of Industry 5.0 in manufacturing SMEs: learning from theory and practice," Technological Forecasting and Social Change, Elsevier, vol. 214(C).
    4. Sarah Maggioli & Liliana Cunha, 2023. "A Systematic Review Discussing the Sustainability of Men and Women’s Work in Industry 4.0: Are Technologies Gender-Neutral?," Sustainability, MDPI, vol. 15(7), pages 1-17, March.
    5. Tobias Reisberger & Philip Reisberger & Lukáš Copuš & Peter Madzík & Lukáš Falát, 2025. "The Linkage Between Digital Transformation and Organizational Culture: Novel Machine Learning Literature Review Based on Latent Dirichlet Allocation," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 16(1), pages 2082-2118, March.
    6. Fawaz M. Abdullah & Abdulrahman M. Al-Ahmari & Saqib Anwar, 2023. "Analyzing Interdependencies among Influencing Factors in Smart Manufacturing," Sustainability, MDPI, vol. 15(4), pages 1-19, February.

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