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An expert system for life cycle assessment of casting process

Author

Listed:
  • Karmjit Singh

    (Federation University)

  • Prince Pal Singh

    (I.K. Gujral Punjab Technical University)

  • Gopinath Chattopadhyay

    (Federation University)

  • Ibrahim A. Sultan

    (Federation University)

Abstract

This paper presents an expert system for the life cycle assessment of die-casting process. The system is built around a robust database of the die-casting process parameters. The sustainability of die-casting is measured using performance indicators, namely investment cost of machines and equipment, operating cost of machines, and energy-related carbon emissions. The methodology of developing an expert system first uses MATLAB function (combivec) to generate alternate process plans thereafter it uses a multi-criteria decision-making method as technique for order of preference by similarity to ideal solution (TOPSIS) for selecting the best feasible process plan. Results show that the proposed approach can compare alternate process plans using sustainability performance indicators for selecting the best feasible option. An illustrative example is presented in this paper for demonstrating how to implement the proposed expert system.

Suggested Citation

  • Karmjit Singh & Prince Pal Singh & Gopinath Chattopadhyay & Ibrahim A. Sultan, 2023. "An expert system for life cycle assessment of casting process," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(4), pages 930-937, December.
    • Handle: RePEc:spr:ijsaem:v:14:y:2023:i:4:d:10.1007_s13198-021-01301-w
    DOI: 10.1007/s13198-021-01301-w
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    References listed on IDEAS

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    1. Tharumarajah, A., 2008. "Benchmarking aluminium die casting operations," Resources, Conservation & Recycling, Elsevier, vol. 52(10), pages 1185-1189.
    2. Faycal A. Touzout & Lyes Benyoucef, 2019. "Multi-objective sustainable process plan generation in a reconfigurable manufacturing environment: exact and adapted evolutionary approaches," International Journal of Production Research, Taylor & Francis Journals, vol. 57(8), pages 2531-2547, April.
    3. Zhanguo Zhu & Feng Chu & Alexandre Dolgui & Chengbin Chu & Wei Zhou & Selwyn Piramuthu, 2018. "Recent advances and opportunities in sustainable food supply chain: a model-oriented review," International Journal of Production Research, Taylor & Francis Journals, vol. 56(17), pages 5700-5722, September.
    4. Burak Sen & Murat Kucukvar & Nuri C. Onat & Omer Tatari, 2020. "Life cycle sustainability assessment of autonomous heavy‐duty trucks," Journal of Industrial Ecology, Yale University, vol. 24(1), pages 149-164, February.
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