Evaluating The Reliability and Availability of A High-Pressure Die Casting System ‎Featuring Two Units and Cold Standby Redundancy

  • Authors

    • Ms. Navpreet Kaur Research Scholar, Department of Mathematics Maharaja Ranjit Singh Punjab Technical University Bathinda
    • Dr. Karanvir Singh Professor, Department of Mathematics Maharaja Ranjit Singh Punjab Technical University Bathinda
    • Dr. Vanita Garg Assistant Professor, Department of Mathematics Amity Institute of Applied Sciences Amity University, Noida, India
    https://doi.org/10.14419/gw4fgr39

    Received date: May 15, 2025

    Accepted date: June 6, 2025

    Published date: June 11, 2025

  • High Pressure Die Casting; RPGT; Failure Rate; Industrial Maintenance Strategies; System ‎Availability.
  • Abstract

    This study presents a behavioral and availability analysis of a high-pressure die casting plant ‎modelled as a two-unit system with cold standby redundancy. By investigating the effects of ‎varying repair rates (α) on system availability, we demonstrate that increased repair rates ‎correlate positively with availability, aligning with practical expectations in industrial ‎applications. Application of the regenerative graphical technique (based on the center of ‎pressure) allows for evaluating the parameters very quickly without involving the computation of ‎state equations or resultants. Our analysis highlights the potential inclusion of multi-unit ‎systems with perfect and imperfect switch-over devices to broaden the model’s applicability. ‎Additionally, insights are provided for conditions under which failure and repair rates may ‎vary, offering directions for future profit-and-loss analysis. We discuss how operational costs ‎can be minimized by leveraging expertise gained through repeated server visits, thereby ‎reducing the need for primary interventions. This study offers a flexible framework for ‎evaluating various system states and assessing key performance attributes, with implications ‎for cost-effective maintenance strategies in industrial settings‎.

  • References

    1. Abdul Jawwad, A. K., & AbuNaffa, I. (2022). Applying analytical hierarchy process (AHP) in selecting best maintenance strategies for newly es-tablished chemical fertilizers plants. Journal of Quality in Maintenance Engineering, 28(3), 545-566. https://doi.org/10.1108/JQME-06-2020-0056.
    2. Al Rahbi, Y., Rizwan, S. M., Alkali, B., Cowell, A. and Taneja, G. (2019). Reliability analysis of multiple units with multiple repairmen of rodding anode plant in aluminum industry. Advances and Applications in Statistics, 54(1), 151-178. https://doi.org/10.17654/AS054010151.
    3. A., & Khurana, P. (2022). Redundancy allocation problem: Jayfe cylinder Manufacturing Plant. International Journal of Engineering, Science & Mathematic, 11(1), 1-7.
    4. Kaur, N., Singh, K., & Garg, V. (2023). Modelling, Sensitivity Analysis and Optimization of System Parameters of Edible Oil Refin-ery. International Journal of Experimental Research Review, 35, 25-33. https://doi.org/10.52756/ijerr.2023.v35spl.003.
    5. Kumar, A., Garg, D., & Goel, P. (2019). Sensitivity analysis of a cold standby system with priority for preventive maintenance. Journal of Advance and Scholarly Research in Allied Education, 16(4), 253-258.
    6. Kumar, A., Pawar, D. and Malik, S.C. (2019). Profit analysis of a warm standby non-identical unit system with single server subject to preventive maintenance, International Journal of Agriculture and Statistical Science,15(1), 261-269
    7. Ma, X., Liu, B., Yang, L., Peng, R., & Zhang, X. (2020). Reliability analysis and condition-based maintenance optimization for a warm standby cooling system. Reliability Engineering & System Safety, 193, 106588. https://doi.org/10.1016/j.ress.2019.106588.
    8. Renu & Bhatia, P. (2019). Reliability analysis of two unit standby system for high pressure die casting machine. Aryabhatta Journal of Mathematics and informatics, 11(1), 19-28
    9. Sahu, D., Bahman, A., Bala Murugan, K. S., Dhurandher, B. K., Rai, A., Dwivedi, G., & Kesharvani, S. (2024). Risk analysis of urea manufactur-ing plant using fuzzy logic approach. Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering, https://doi.org/10.1177/09544089241281430.
    10. Banerjee, M., Garg, V. & Deep, K. Solving structural and reliability optimization problems using efficient mutation strategies embedded in sine co-sine algorithm. Int J Syst Assur Eng Manag 14 (Suppl 1), 307–327 (2023). https://doi.org/10.1007/s13198-023-01857-9.
    11. Garg, D., Garg, R., & Garg, V. (2022). Inspecting briquette machine with different faults. Recent Advances in Computer Science and Communica-tions (Formerly: Recent Patents on Computer Science), 15(4), 481-486. https://doi.org/10.2174/2666255813999200909110603.
  • Downloads

  • How to Cite

    Kaur, M. N. ., Singh , D. K. ., & Garg , D. V. . (2025). Evaluating The Reliability and Availability of A High-Pressure Die Casting System ‎Featuring Two Units and Cold Standby Redundancy. International Journal of Basic and Applied Sciences, 14(2), 202-210. https://doi.org/10.14419/gw4fgr39