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A Sustainable Productive Method for Enhancing Operational Excellence in Shop Floor Management for Industry 4.0 Using Hybrid Integration of Lean and Smart Manufacturing: An Ingenious Case Study

Author

Listed:
  • Varun Tripathi

    (Department of Mechanical Engineering, Accurate Institute of Management Technology, Greater Noida 201306, India)

  • Somnath Chattopadhyaya

    (Department of Mechanical Engineering, Indian Institute of Technology (ISM), Dhanbad 826004, India)

  • Alok Kumar Mukhopadhyay

    (Department of Mining Machinery Engineering, Indian Institute of Technology (ISM), Dhanbad 826004, India)

  • Shubham Sharma

    (Department of Mechanical Engineering, IK Gujral Punjab Technical University, Main Campus, Kapurthala 144603, India
    Department of Mechanical Engineering, University Centre for Research and Development (UCRD), Chandigarh University, Mohali 140413, India)

  • Changhe Li

    (School of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao 266520, China)

  • Sunpreet Singh

    (Department of Mechanical Engineering, University Centre for Research and Development (UCRD), Chandigarh University, Mohali 140413, India
    Department of Mechanical Engineering, National University of Singapore, Singapore 119077, Singapore)

  • Waqas Ul Hussan

    (Department of Hydropower Engineering, University of Engineering and Applied Sciences, Swat 19060, Pakistan)

  • Bashir Salah

    (Industrial Engineering Department, College of Engineering, King Saud University, P.O. Box 800, Riyadh 11421, Saudi Arabia)

  • Waqas Saleem

    (Department of Mechanical and Manufacturing Engineering, Institute of Technology, F91 YW50 Sligo, Ireland)

  • Abdullah Mohamed

    (Research Center, Research Center, Future University in Egypt, New Cairo 11835, Egypt)

Abstract

In industry 4.0, industry individuals implement lean and smart manufacturing to improve shop floor management systems. Shop floor management is used to control operational performance and enhance production within limited constraints. Various shop floor management approaches are used in the present scenario of industry 4.0, and mainly include value stream mapping, total productive maintenance, Internet of Things, artificial intelligence, machine learning, and fuzzy logic. The present research aims to develop an open innovation method to achieve sustainability in shop floor management systems in industry 4.0 by using lean and smart manufacturing concepts. The proposed method has been validated by an enhancement obtained in a real case of the shop floor management system in industry 4.0. The authors are confident that the proposed method would provide sustainability in the shop floor management system within limited constraints in industry 4.0.

Suggested Citation

  • Varun Tripathi & Somnath Chattopadhyaya & Alok Kumar Mukhopadhyay & Shubham Sharma & Changhe Li & Sunpreet Singh & Waqas Ul Hussan & Bashir Salah & Waqas Saleem & Abdullah Mohamed, 2022. "A Sustainable Productive Method for Enhancing Operational Excellence in Shop Floor Management for Industry 4.0 Using Hybrid Integration of Lean and Smart Manufacturing: An Ingenious Case Study," Sustainability, MDPI, vol. 14(12), pages 1-21, June.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:12:p:7452-:d:841949
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    References listed on IDEAS

    as
    1. Fernanda Strozzi & Claudia Colicchia & Alessandro Creazza & Carlo Noè, 2017. "Literature review on the ‘Smart Factory’ concept using bibliometric tools," International Journal of Production Research, Taylor & Francis Journals, vol. 55(22), pages 6572-6591, November.
    2. Wenzhu Liao & Tong Wang, 2019. "A Novel Collaborative Optimization Model for Job Shop Production–Delivery Considering Time Window and Carbon Emission," Sustainability, MDPI, vol. 11(10), pages 1-27, May.
    3. Mohamed Abubakr & Adel T. Abbas & Italo Tomaz & Mahmoud S. Soliman & Monis Luqman & Hussien Hegab, 2020. "Sustainable and Smart Manufacturing: An Integrated Approach," Sustainability, MDPI, vol. 12(6), pages 1-19, March.
    4. Sameer Mittal & Muztoba Ahmad Khan & Jayant Kishor Purohit & Karan Menon & David Romero & Thorsten Wuest, 2020. "A smart manufacturing adoption framework for SMEs," International Journal of Production Research, Taylor & Francis Journals, vol. 58(5), pages 1555-1573, March.
    5. Varun Tripathi & Somnath Chattopadhyaya & Alok Bhadauria & Shubham Sharma & Changhe Li & Danil Yurievich Pimenov & Khaled Giasin & Sunpreet Singh & Girish Dutt Gautam, 2021. "An Agile System to Enhance Productivity through a Modified Value Stream Mapping Approach in Industry 4.0: A Novel Approach," Sustainability, MDPI, vol. 13(21), pages 1-31, October.
    6. X. Wang & A.W.W. Yew & S.K. Ong & A.Y.C. Nee, 2020. "Enhancing smart shop floor management with ubiquitous augmented reality," International Journal of Production Research, Taylor & Francis Journals, vol. 58(8), pages 2352-2367, April.
    7. Kamble, Sachin S. & Gunasekaran, Angappa & Ghadge, Abhijeet & Raut, Rakesh, 2020. "A performance measurement system for industry 4.0 enabled smart manufacturing system in SMMEs- A review and empirical investigation," International Journal of Production Economics, Elsevier, vol. 229(C).
    8. Varun Tripathi & Somnath Chattopadhyaya & Alok Kumar Mukhopadhyay & Shubham Sharma & Changhe Li & Gianpaolo Di Bona, 2022. "A Sustainable Methodology Using Lean and Smart Manufacturing for the Cleaner Production of Shop Floor Management in Industry 4.0," Mathematics, MDPI, vol. 10(3), pages 1-23, January.
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