IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i12p7452-d841949.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/12/7452/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/12/7452/
    Download Restriction: no
    ---><---

    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.
    Full references (including those not matched with items on IDEAS)

    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. Mitsuhiro Fukuzawa & Ryosuke Sugie & Youngwon Park & Jin Shi, 2022. "An Exploratory Case Study on the Metrics and Performance of IoT Investment in Japanese Manufacturing Firms," Sustainability, MDPI, vol. 14(5), pages 1-21, February.
    2. Yang Qianqiu & Song Baoli, 2024. "Research on the impact and mechanisms of lean management on the green development of traditional small and micro manufacturing enterprises," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 31(5), pages 4956-4979, September.
    3. Satish Kumar & Filomena Maggino & Raj V. Mahto & Riya Sureka & Leonardo Salvatore Alaimo & Weng Marc Lim, 2022. "Social Indicators Research: A Retrospective Using Bibliometric Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 162(1), pages 413-448, July.
    4. Xiangang Cao & Pengfei Li & Song Ming, 2021. "Remaining Useful Life Prediction-Based Maintenance Decision Model for Stochastic Deterioration Equipment under Data-Driven," Sustainability, MDPI, vol. 13(15), pages 1-19, July.
    5. Björn Häckel & Florian Hänsch & Michael Hertel & Jochen Übelhör, 2019. "Assessing IT availability risks in smart factory networks," Business Research, Springer;German Academic Association for Business Research, vol. 12(2), pages 523-558, December.
    6. Ndubisi, Nelson Oly & Zhai, Xin (Amy) & Lai, Kee-hung, 2021. "Small and medium manufacturing enterprises and Asia's sustainable economic development," International Journal of Production Economics, Elsevier, vol. 233(C).
    7. Özköse, Hakan & Güney, Gül, 2023. "The effects of industry 4.0 on productivity: A scientific mapping study," Technology in Society, Elsevier, vol. 75(C).
    8. Magdalena Mucowska, 2021. "Trends of Environmentally Sustainable Solutions of Urban Last-Mile Deliveries on the E-Commerce Market—A Literature Review," Sustainability, MDPI, vol. 13(11), pages 1-26, May.
    9. Peerally, Jahan Ara & Santiago, Fernando & De Fuentes, Claudia & Moghavvemi, Sedigheh, 2022. "Towards a firm-level technological capability framework to endorse and actualize the Fourth Industrial Revolution in developing countries," Research Policy, Elsevier, vol. 51(10).
    10. Manu Sharma & Deepak Kaushal & Sudhanshu Joshi, 2023. "Strategic measures for enhancing resiliency in knowledge base supply chains: an emerging economy perspective," Operations Management Research, Springer, vol. 16(3), pages 1185-1205, September.
    11. Katarzyna Grzybowska, 2021. "Identification and Classification of Global Theoretical Trends and Supply Chain Development Directions," Energies, MDPI, vol. 14(15), pages 1-19, July.
    12. Hao Yu & Jiaqi Yang & Xipei Kang & Zhe Cong & Siwei Yao, 2022. "Empty Pallet Allocation Optimization in Shipbuilding Using a Pallet Pool System," Sustainability, MDPI, vol. 14(9), pages 1-21, May.
    13. Sun, Jing & Yamamoto, Hisashi & Matsui, Masayuki, 2020. "Horizontal integration management: An optimal switching model for parallel production system with multiple periods in smart supply chain environment," International Journal of Production Economics, Elsevier, vol. 221(C).
    14. Wu, Wei & Hayashi, Takito & Haruyasu, Kato & Tang, Liang, 2023. "Exact algorithms based on a constrained shortest path model for robust serial-batch and parallel-batch scheduling problems," European Journal of Operational Research, Elsevier, vol. 307(1), pages 82-102.
    15. 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).
    16. Zhitao Xu & Adel Elomri & Roberto Baldacci & Laoucine Kerbache & Zhenyong Wu, 2024. "Frontiers and trends of supply chain optimization in the age of industry 4.0: an operations research perspective," Annals of Operations Research, Springer, vol. 338(2), pages 1359-1401, July.
    17. Aswathy Sreenivasan & M. Suresh, 2024. "Enabling technologies influencing the start-up operations 5.0," Operations Management Research, Springer, vol. 17(3), pages 869-890, September.
    18. Fuping Bai & Donghui Liu & Kaiyun Dong & Mengting Shang & Aiguo Yan, 2023. "Research on How Executive Connections Affect Enterprise Digital Transformation: Empirical Evidence from China," Sustainability, MDPI, vol. 15(3), pages 1-17, January.
    19. Jae Hong Park & Phil Goo Kang & Eunseok Kim & Tae Woo Kim & Gahee Kim & Heejeong Seok & Jinwon Seo, 2021. "Introduction of IoT-Based Surrogate Parameters in the Ex-Post Countermeasure of Industrial Sectors in Integrated Permit Policy," Sustainability, MDPI, vol. 13(23), pages 1-22, December.
    20. Lemstra, Mary Anny Moraes Silva & de Mesquita, Marco Aurélio, 2023. "Industry 4.0: a tertiary literature review," Technological Forecasting and Social Change, Elsevier, vol. 186(PB).

    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:14:y:2022:i:12:p:7452-:d:841949. 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.