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Prediction of production facility priorities using Back Propagation Neural Network for bus body building industries: a post pandemic research article

Author

Listed:
  • A. Sivakumar

    (Kongu Engineering College)

  • N. Bagath Singh

    (Kurinji College of Engineering and Technology)

  • D. Arulkirubakaran

    (Karunya Institute of Technology and Sciences, Karunya Nagar)

  • P. Praveen Vijaya Raj

    (Indian Institute of Management Raipur)

Abstract

The pandemic recession has caused enormous disturbances in many industrialized countries. The massive disruption of the supply chain of production is affecting manufacturing companies operating in and around India. Particularly the medium-sized bus body building works have been reduced, due to its compound anomalies. The integrated view of the production facility priorities is not an easy task. Since it is difficult for available labour to conduct an entire project, the completion of a production process is delayed. But still, the dilemma remains as to how production managers can correctly interpret the priorities of the facility. Indeed, this is a problem missing from the previous study. Fortunately, in the current competitive environment, it is essentially needed. This study has been used Back Propagation Neural Network (BPNN) approach for predicting production facility priorities. The experimental results confirm the suitability of the model for predicting priorities. A real-world problem is taken into account in making use of the model output. In this sense, this total solution facilitates production managers in assessing and enhancing the production facilities. The findings emphasize the priority of “equipment effectiveness, labour scheduling and communication” in order to strengthen the post-pandemic production facility.

Suggested Citation

  • A. Sivakumar & N. Bagath Singh & D. Arulkirubakaran & P. Praveen Vijaya Raj, 2023. "Prediction of production facility priorities using Back Propagation Neural Network for bus body building industries: a post pandemic research article," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(1), pages 561-585, February.
  • Handle: RePEc:spr:qualqt:v:57:y:2023:i:1:d:10.1007_s11135-022-01365-1
    DOI: 10.1007/s11135-022-01365-1
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    References listed on IDEAS

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    1. Andrew Dainty & Stephen Ison & Geoffrey Briscoe, 2005. "The construction labour market skills crisis: the perspective of small-medium-sized firms," Construction Management and Economics, Taylor & Francis Journals, vol. 23(4), pages 387-398.
    2. S. G. Deshmukh & Abid Haleem, 2020. "Framework for Manufacturing in Post-COVID-19 World Order: An Indian Perspective," International Journal of Global Business and Competitiveness, Springer, vol. 15(1), pages 49-60, June.
    3. Varun Goel & Rajat Agrawal & Vinay Sharma, 2017. "Factors affecting labour productivity: an integrative synthesis and productivity modelling," Global Business and Economics Review, Inderscience Enterprises Ltd, vol. 19(3), pages 299-322.
    4. Bernolak, Imre, 1997. "Effective measurement and successful elements of company productivity: The basis of competitiveness and world prosperity," International Journal of Production Economics, Elsevier, vol. 52(1-2), pages 203-213, October.
    5. Junxi Zhang & Shiru Qu & Zhihan Lv, 2021. "Optimization of Backpropagation Neural Network under the Adaptive Genetic Algorithm," Complexity, Hindawi, vol. 2021, pages 1-9, July.
    6. Calcagnini, Giorgio & Travaglini, Giuseppe, 2014. "A time series analysis of labor productivity. Italy versus the European countries and the U.S," Economic Modelling, Elsevier, vol. 36(C), pages 622-628.
    7. Rami As'ad & Kudret Demirli & Suresh K. Goyal, 2015. "Coping with uncertainties in production planning through fuzzy mathematical programming: application to steel rolling industry," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 22(1), pages 1-30.
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