IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v10y2018i9p3031-d165904.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/10/9/3031/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/10/9/3031/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. Maria Elena Nenni & Raffaele Iannone, 2013. "Managing OEE to Optimize Factory Performance," Chapters, in: Massimiliano M. Schiraldi (ed.), Operations Management, IntechOpen.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Orlando Durán & Paulo Andrés Durán, 2019. "Prioritization of Physical Assets for Maintenance and Production Sustainability," Sustainability, MDPI, vol. 11(16), pages 1-17, August.
    2. Amber Iqbal & M. Nasir Bashir & Asna Alam & M. Bilal Asif & Iqra Arshad, 2020. "Implementation of Lean Methodology on the Main Assembly Line of an Automotive Plant to Enhance Productivity," Journal of ICT, Design, Engineering and Technological Science, Juhriyansyah Dalle, vol. 4(1), pages 16-22.
    3. Poorya Ghafoorpoor Yazdi & Aydin Azizi & Majid Hashemipour, 2019. "A Hybrid Methodology for Validation of Optimization Solutions Effects on Manufacturing Sustainability with Time Study and Simulation Approach for SMEs," Sustainability, MDPI, vol. 11(5), pages 1-26, March.
    4. Roland Zs. Szabo & Iva Vuksanović Herceg & Robert Hanák & Lilla Hortovanyi & Anita Romanová & Marian Mocan & Dragan Djuričin, 2020. "Industry 4.0 Implementation in B2B Companies: Cross-Country Empirical Evidence on Digital Transformation in the CEE Region," Sustainability, MDPI, vol. 12(22), pages 1-20, November.
    5. Jorge Luis García-Alcaraz & José Roberto Díaz Reza & Cuauhtémoc Sánchez Ramírez & Jorge Limón Romero & Emilio Jiménez Macías & Carlos Javierre Lardies & Manuel Arnoldo Rodríguez Medina, 2021. "Lean Manufacturing Tools Applied to Material Flow and Their Impact on Economic Sustainability," Sustainability, MDPI, vol. 13(19), pages 1-18, September.
    6. Jakob Trauer & Simon Pfingstl & Markus Finsterer & Markus Zimmermann, 2021. "Improving Production Efficiency with a Digital Twin Based on Anomaly Detection," Sustainability, MDPI, vol. 13(18), pages 1-21, September.
    7. Matthias Seitz & Felix Gehlhoff & Luis Alberto Cruz Salazar & Alexander Fay & Birgit Vogel-Heuser, 2021. "Automation platform independent multi-agent system for robust networks of production resources in industry 4.0," Journal of Intelligent Manufacturing, Springer, vol. 32(7), pages 2023-2041, October.
    8. Piccarozzi, Michela & Silvestri, Cecilia & Aquilani, Barbara & Silvestri, Luca, 2022. "Is this a new story of the ‘Two Giants’? A systematic literature review of the relationship between industry 4.0, sustainability and its pillars," Technological Forecasting and Social Change, Elsevier, vol. 177(C).
    9. Jaroslav Vrchota & Martin Pech & Ladislav Rolínek & Jiří Bednář, 2020. "Sustainability Outcomes of Green Processes in Relation to Industry 4.0 in Manufacturing: Systematic Review," Sustainability, MDPI, vol. 12(15), pages 1-47, July.
    10. Héctor Cañas & Josefa Mula & Francisco Campuzano-Bolarín, 2020. "A General Outline of a Sustainable Supply Chain 4.0," Sustainability, MDPI, vol. 12(19), pages 1-17, September.
    11. 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.
    12. Oliver Kovacs, 2019. "Big IFs in Productivity-Enhancing Industry 4.0," Social Sciences, MDPI, vol. 8(2), pages 1-17, January.
    13. José Salvador da Motta Reis & Maximilian Espuny & Thaís Vieira Nunhes & Nilo Antonio de Souza Sampaio & Raine Isaksson & Fernando Celso de Campos & Otávio José de Oliveira, 2021. "Striding towards Sustainability: A Framework to Overcome Challenges and Explore Opportunities through Industry 4.0," Sustainability, MDPI, vol. 13(9), pages 1-28, May.
    14. Xiaoxia Chen & Mélanie Despeisse & Björn Johansson, 2020. "Environmental Sustainability of Digitalization in Manufacturing: A Review," Sustainability, MDPI, vol. 12(24), pages 1-31, December.
    15. Giancarlo Nota & Francesco David Nota & Domenico Peluso & Alonso Toro Lazo, 2020. "Energy Efficiency in Industry 4.0: The Case of Batch Production Processes," Sustainability, MDPI, vol. 12(16), pages 1-28, August.
    16. Jorge Luis García Alcaraz & Adrián Salvador Morales García & José Roberto Díaz Reza & Julio Blanco Fernández & Emilio Jiménez Macías & Rita Puig i Vidal, 2022. "Machinery Lean Manufacturing Tools for Improved Sustainability: The Mexican Maquiladora Industry Experience," Mathematics, MDPI, vol. 10(9), pages 1-18, April.

    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. Poorya Ghafoorpoor Yazdi & Aydin Azizi & Majid Hashemipour, 2019. "A Hybrid Methodology for Validation of Optimization Solutions Effects on Manufacturing Sustainability with Time Study and Simulation Approach for SMEs," Sustainability, MDPI, vol. 11(5), pages 1-26, March.
    2. Xiaoyi Liu & Jonghyun Lee & Peter Kitanidis & Jack Parker & Ungtae Kim, 2012. "Value of Information as a Context-Specific Measure of Uncertainty in Groundwater Remediation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(6), pages 1513-1535, April.
    3. Ming Yuan & Jingya Dang & Yujie Hong & Di Gao & Ziyi Xu, 2024. "The Impact of Supply Chain Network Centrality on Sustainable Mergers and Acquisitions: Evidence from China," Sustainability, MDPI, vol. 16(19), pages 1-24, September.
    4. McKelvey, Bill & Wycisk, Christine & Hülsmann, Michael, 2009. "Designing an electronic auction market for complex 'smart parts' logistics: Options based on LeBaron's computational stock market," International Journal of Production Economics, Elsevier, vol. 120(2), pages 476-494, August.
    5. Sohn, So Young & Lim, Michael, 2008. "The effect of forecasting and information sharing in SCM for multi-generation products," European Journal of Operational Research, Elsevier, vol. 186(1), pages 276-287, April.
    6. WANG Jifu & GUPTA Vipin & LYBOLT Liza & WANG Xiuli, 2022. "Corrected Game Model In Csr: Mnc Strategies And Chinese Practice," Studies in Business and Economics, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 17(3), pages 269-287, December.
    7. Jessica L. Darby & David J. Ketchen & Brent D. Williams & Travis Tokar, 2020. "The Implications of Firm‐Specific Policy Risk, Policy Uncertainty, and Industry Factors for Inventory: A Resource Dependence Perspective," Journal of Supply Chain Management, Institute for Supply Management, vol. 56(4), pages 3-24, October.
    8. Brian Mittendorf & Jiwoong Shin & Dae-Hee Yoon, 2013. "Manufacturer marketing initiatives and retailer information sharing," Quantitative Marketing and Economics (QME), Springer, vol. 11(2), pages 263-287, June.
    9. Yu, Yanan & He, Yong & Zhao, Xuan, 2021. "Impact of demand information sharing on organic farming adoption: An evolutionary game approach," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
    10. Juha Lukkarinen & Jukka Majava, 2020. "Supplies Inventory Management in a Corporation Context: A Case Study," International Journal of Management, Knowledge and Learning, International School for Social and Business Studies, Celje, Slovenia, vol. 9(2), pages 169-184.
    11. Ramanathan, Usha & Muyldermans, Luc, 2010. "Identifying demand factors for promotional planning and forecasting: A case of a soft drink company in the UK," International Journal of Production Economics, Elsevier, vol. 128(2), pages 538-545, December.
    12. Dara G. Schniederjans & Mehrnaz Khalajhedayati, 2021. "Competitive sustainability and stakeholder engagement: Exploring awareness, motivation, and capability," Business Strategy and the Environment, Wiley Blackwell, vol. 30(2), pages 808-824, February.
    13. Lee, Jongkuk & Palekar, Udatta S. & Qualls, William, 2011. "Supply chain efficiency and security: Coordination for collaborative investment in technology," European Journal of Operational Research, Elsevier, vol. 210(3), pages 568-578, May.
    14. Susan A. Kayser & John W. Maxwell & Michael W. Toffel, 2014. "Supply chain screening without certification: The critical role of stakeholder pressure," Working Papers 2014-08, Indiana University, Kelley School of Business, Department of Business Economics and Public Policy.
    15. Kaijie Zhu & Ulrich W. Thonemann, 2004. "Modeling the Benefits of Sharing Future Demand Information," Operations Research, INFORMS, vol. 52(1), pages 136-147, February.
    16. Kevin H. Shang & Sean X. Zhou & Geert-Jan van Houtum, 2010. "Improving Supply Chain Performance: Real-Time Demand Information and Flexible Deliveries," Manufacturing & Service Operations Management, INFORMS, vol. 12(3), pages 430-448, May.
    17. Sven Axsäter & Johan Marklund, 2008. "Optimal Position-Based Warehouse Ordering in Divergent Two-Echelon Inventory Systems," Operations Research, INFORMS, vol. 56(4), pages 976-991, August.
    18. Rakesh Niraj & Chakravarthi Narasimhan, 2017. "Examining Incentives to Share Demand Information with your Channel Partner," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(04), pages 961-980, July.
    19. Ketzenberg, M.E. & van der Laan, E.A. & Teunter, R.H., 2004. "The Value of Information in Reverse Logistics," ERIM Report Series Research in Management ERS-2004-053-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    20. Yue, Xiaohang & Liu, John, 2006. "Demand forecast sharing in a dual-channel supply chain," European Journal of Operational Research, Elsevier, vol. 174(1), pages 646-667, October.

    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:gam:jsusta:v:10:y:2018:i:9:p:3031-:d:165904. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.