IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i6p3452-d520924.html
   My bibliography  Save this article

Implementation of POLCA Integrated QRM Framework for Optimized Production Performance—A Case Study

Author

Listed:
  • Wanzhu Wang

    (School of Economics and Finance, Xi’an Jiaotong University, Xi’an 710061, China)

  • Qazi Salman Khalid

    (Department of Industrial Engineering, University of Engineering and Technology, Peshawar 25000, Pakistan)

  • Muhammad Abas

    (Department of Industrial Engineering, University of Engineering and Technology, Peshawar 25000, Pakistan)

  • Hao Li

    (Guanghua School of Management, Peking University, Beijing 100000, China)

  • Shakir Azim

    (Department of Industrial Engineering, University of Engineering and Technology, Peshawar 25000, Pakistan)

  • Abdur Rehman Babar

    (Department of Industrial Engineering, University of Engineering and Technology, Peshawar 25000, Pakistan)

  • Waqas Saleem

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

  • Razaullah Khan

    (Department of Mechanical Engineering Technology, University of Technology, Nowshera 24100, Pakistan
    Department of Engineering Management, University of Engineering and Technology, 19060 Swat, Pakistan)

Abstract

Quick response manufacturing (QRM) is a relatively new concept that enfolds all the preceding approaches, namely, just in time (JIT), flexible manufacturing, agile manufacturing, and lean production. QRM is compatible with existing materials requirement planning (MRP) systems and can be implemented efficiently. The ideas from QRM have been highly influential in custom-made engineer-to-order and make-to-order (ETO/MTO) high-mix and low-volume production environments. This study investigates the effectiveness of the POLCA (paired cell overlapping loops of cards) integrated QRM framework for reducing lead time. The POLCA integrated QRM approach was implemented in a precise product manufacturing industry. The industry was facing high penalties due to improper planning and uncontrolled lead times. The implementation of QRM with the POLCA framework indicated optimized production scheduling and significant improvement in lead time and work in process (WIP). After implementing the new manufacturing strategy, the performance parameters showed significant improvement in terms of reducing the percentage loss of profit.

Suggested Citation

  • Wanzhu Wang & Qazi Salman Khalid & Muhammad Abas & Hao Li & Shakir Azim & Abdur Rehman Babar & Waqas Saleem & Razaullah Khan, 2021. "Implementation of POLCA Integrated QRM Framework for Optimized Production Performance—A Case Study," Sustainability, MDPI, vol. 13(6), pages 1-22, March.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:6:p:3452-:d:520924
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/6/3452/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/6/3452/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Nico Vandaele & Inneke Van Nieuwenhuyse & Diederik Claerhout & Rony Cremmery, 2008. "Load-Based POLCA: An Integrated Material Control System for Multiproduct, Multimachine Job Shops," Manufacturing & Service Operations Management, INFORMS, vol. 10(2), pages 181-197, September.
    2. Bortolotti, Thomas & Boscari, Stefania & Danese, Pamela, 2015. "Successful lean implementation: Organizational culture and soft lean practices," International Journal of Production Economics, Elsevier, vol. 160(C), pages 182-201.
    3. Godinho Filho, Moacir & Marchesini, Antonio Gilberto & Riezebos, Jan & Vandaele, Nico & Ganga, Gilberto Miller Devós, 2017. "The application of Quick Response Manufacturing practices in Brazil, Europe, and the USA: An exploratory study," International Journal of Production Economics, Elsevier, vol. 193(C), pages 437-448.
    4. Alireza Farnoush & Magnus Wiktorsson, 2013. "POLCA and CONWIP performance in a divergent production line: an automotive case study," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 24(2), pages 159-186, July.
    5. Chavez, Roberto & Yu, Wantao & Jacobs, Mark & Fynes, Brian & Wiengarten, Frank & Lecuna, Antonio, 2015. "Internal lean practices and performance: The role of technological turbulence," International Journal of Production Economics, Elsevier, vol. 160(C), pages 157-171.
    6. Mark L. Spearman & Michael A. Zazanis, 1992. "Push and Pull Production Systems: Issues and Comparisons," Operations Research, INFORMS, vol. 40(3), pages 521-532, June.
    7. Thawatchai Jitpaiboon & Qiannong Gu & Dothang Truong, 2016. "Evolution of competitive priorities towards performance improvement: a meta-analysis," International Journal of Production Research, Taylor & Francis Journals, vol. 54(24), pages 7400-7420, December.
    8. Moacir Godinho Filho & Gilberto Miller Devós Ganga & Angappa Gunasekaran, 2016. "Lean manufacturing in Brazilian small and medium enterprises: implementation and effect on performance," International Journal of Production Research, Taylor & Francis Journals, vol. 54(24), pages 7523-7545, December.
    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. Godinho Filho, Moacir & Marchesini, Antonio Gilberto & Riezebos, Jan & Vandaele, Nico & Ganga, Gilberto Miller Devós, 2017. "The application of Quick Response Manufacturing practices in Brazil, Europe, and the USA: An exploratory study," International Journal of Production Economics, Elsevier, vol. 193(C), pages 437-448.
    2. Matthias Thürer & Nuno O. Fernandes & Mark Stevenson & Cristovao Silva & Silvio Carmo-Silva, 2019. "POLC-A: an assessment of POLCA’s authorization element," Journal of Intelligent Manufacturing, Springer, vol. 30(6), pages 2435-2447, August.
    3. Soliman, Marlon & Saurin, Tarcisio Abreu & Anzanello, Michel Jose, 2018. "The impacts of lean production on the complexity of socio-technical systems," International Journal of Production Economics, Elsevier, vol. 197(C), pages 342-357.
    4. Bortolotti, Thomas & Romano, Pietro & Martínez-Jurado, Pedro José & Moyano-Fuentes, José, 2016. "Towards a theory for lean implementation in supply networks," International Journal of Production Economics, Elsevier, vol. 175(C), pages 182-196.
    5. Marodin, Giuliano & Frank, Alejandro Germán & Tortorella, Guilherme Luz & Netland, Torbjørn, 2018. "Lean product development and lean manufacturing: Testing moderation effects," International Journal of Production Economics, Elsevier, vol. 203(C), pages 301-310.
    6. Matthias Thürer & Nuno O. Fernandes & Mark Stevenson, 2020. "Material Flow Control in High‐Variety Make‐to‐Order Shops: Combining COBACABANA and POLCA," Production and Operations Management, Production and Operations Management Society, vol. 29(9), pages 2138-2152, September.
    7. Kasper, T.A. Arno & Land, Martin J. & Teunter, Ruud H., 2023. "Non-hierarchical work-in-progress control in manufacturing," International Journal of Production Economics, Elsevier, vol. 257(C).
    8. Roberto Chavez & Wantao Yu & Muhammad Shakeel Sadiq Jajja & Antonio Lecuna & Brian Fynes, 2020. "Can entrepreneurial orientation improve sustainable development through leveraging internal lean practices?," Business Strategy and the Environment, Wiley Blackwell, vol. 29(6), pages 2211-2225, September.
    9. Minshull, Lauren Kate & Dehe, Benjamin & Kotcharin, Suntichai, 2022. "Exploring the impact of a sequential lean implementation within a micro-firm – A socio-technical perspective," Journal of Business Research, Elsevier, vol. 151(C), pages 156-169.
    10. Kroes, James R. & Manikas, Andrew S. & Gattiker, Thomas F., 2018. "Operational leanness and retail firm performance since 1980," International Journal of Production Economics, Elsevier, vol. 197(C), pages 262-274.
    11. Catherine Maware & David M. Parsley, 2022. "The Challenges of Lean Transformation and Implementation in the Manufacturing Sector," Sustainability, MDPI, vol. 14(10), pages 1-24, May.
    12. da Silva, Agostinho & Almeida, Isabel, 2020. "Towards INDUSTRY 4.0 | a case STUDY in ornamental stone sector," Resources Policy, Elsevier, vol. 67(C).
    13. Jalali, Hamed & Carmen, Raïsa & Van Nieuwenhuyse, Inneke & Boute, Robert, 2019. "Quality and pricing decisions in production/inventory systems," European Journal of Operational Research, Elsevier, vol. 272(1), pages 195-206.
    14. Hoogstra-Klein, Marjanke A. & Meijboom, Kars, 2021. "A qualitative exploration of the wood product supply chain – investigating the possibilities and desirability of an increased demand orientation," Forest Policy and Economics, Elsevier, vol. 133(C).
    15. Maico Roris Severino & Moacir Godinho Filho, 2019. "POLCA system for supply chain management: simulation in the automotive industry," Journal of Intelligent Manufacturing, Springer, vol. 30(3), pages 1271-1289, March.
    16. Wilhelm, W. E. & Som, Pradip, 1998. "Analysis of a single-stage, single-product, stochastic, MRP-controlled assembly system," European Journal of Operational Research, Elsevier, vol. 108(1), pages 74-93, July.
    17. Tortorella, Guilherme Luz & Narayanamurthy, Gopalakrishnan & Thurer, Matthias, 2021. "Identifying pathways to a high-performing lean automation implementation: An empirical study in the manufacturing industry," International Journal of Production Economics, Elsevier, vol. 231(C).
    18. Queiroz, Maciel M. & Fosso Wamba, Samuel, 2019. "Blockchain adoption challenges in supply chain: An empirical investigation of the main drivers in India and the USA," International Journal of Information Management, Elsevier, vol. 46(C), pages 70-82.
    19. Bendig, David & Brettel, Malte & Downar, Benedikt, 2018. "Inventory component volatility and its relation to returns," International Journal of Production Economics, Elsevier, vol. 200(C), pages 37-49.
    20. Falah Abu & Hamed Gholami & Norhayati Zakuan & Muhamad Zameri Mat Saman & Dalia Streimikiene & Justas Streimikis, 2020. "The Influence of Contextual Factors on the Implementation of Lean Practices: An Analysis of Furniture Industries," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 22(55), pages 867-867, August.

    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:13:y:2021:i:6:p:3452-:d:520924. 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.