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An Empirical Investigation of the Relationship between Overall Equipment Efficiency (OEE) and Manufacturing Sustainability in Industry 4.0 with Time Study Approach

Author

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  • Poorya Ghafoorpoor Yazdi

    (Department of Mechanical Engineering, Eastern Mediterranean University, Famagusta 99628, Northern Cyprus)

  • Aydin Azizi

    (Engineering Department, German University of Technology, Muscat 130, Oman)

  • Majid Hashemipour

    (Faculty of Engineering, Cyprus International University, Nicosia 99258, Northern Cyprus)

Abstract

Nowadays, small and medium sized enterprises (SMEs) are becoming increasingly competitive. In order to fulfill the rapidly changing market and diversified demands of customers, the SMEs need to achieve and maintain high productivity and quality, with fast response, sufficient flexibility, and short lead times. Therefore, Industry 4.0 offers various manufacturing paradigms that might be a solution in order to increase the productivity of SMEs such as intelligent and flexible manufacturing. Furthermore, in the last decade, the emphasis on adopting eco-friendly practices, implementing sustainability measures, and protecting the environment has continued to grow, to gain traction across SMEs. In fact, because of this need, many SMEs are now adopting sustainable manufacturing practices in response to this increased focus on sustainability and environmental stewardship. The main purpose of this paper is to design and study the implementation of a sustainable, intelligent material handling system for material distribution with utilizing an agent-based algorithm as control architecture. A time study-based methodology has been implemented to evaluate the overall equipment effectiveness (OEE) to identify the matters that need to be resolved and optimized to increase the OEE percentage with consideration of the sustainability of the system. An exhaustive analytical trend applied to the generated time study data. Accordingly, further hardware, software, and layout design limitation and problems detected, and the proper solutions were anticipated. The observed time study results were presented, a fundamental set of analytical observation and information with associated histograms was reviewed. In addition, the study aims to recognize and analyze effective factors on the sustainability of improved processes, using a simple model. To do this, using experts’ viewpoints, affective factors on the sustainability of process improvement activities are determined.

Suggested Citation

  • Poorya Ghafoorpoor Yazdi & Aydin Azizi & Majid Hashemipour, 2018. "An Empirical Investigation of the Relationship between Overall Equipment Efficiency (OEE) and Manufacturing Sustainability in Industry 4.0 with Time Study Approach," Sustainability, MDPI, vol. 10(9), pages 1-28, August.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:9:p:3031-:d:165904
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    References listed on IDEAS

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    1. Torbjörn Ylipää & Anders Skoogh & Jon Bokrantz & Maheshwaran Gopalakrishnan, 2017. "Identification of maintenance improvement potential using OEE assessment," International Journal of Productivity and Performance Management, Emerald Group Publishing Limited, vol. 66(1), pages 126-143, January.
    2. Maria Elena Nenni & Raffaele Iannone, 2013. "Managing OEE to Optimize Factory Performance," Chapters, in: Massimiliano M. Schiraldi (ed.), Operations Management, IntechOpen.
    3. Gérard P. Cachon & Marshall Fisher, 2000. "Supply Chain Inventory Management and the Value of Shared Information," Management Science, INFORMS, vol. 46(8), pages 1032-1048, August.
    4. Maria Lai‐Ling Lam, 2011. "Challenges of sustainable environmental programs of foreign multinational enterprises in China," Management Research Review, Emerald Group Publishing Limited, vol. 34(11), pages 1153-1168, October.
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    14. Shouyao Xiong & Yuanyuan Feng & Kai Huang, 2020. "Optimal MTS and MTO Hybrid Production System for a Single Product Under the Cap-And-Trade Environment," Sustainability, MDPI, vol. 12(6), pages 1-16, March.
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