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Predictive maintenance methodology in sheet metal progressive tooling: a case study

Author

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  • Ashutosh Kolhatkar

    (Symbiosis Institute of Technology, SIU)

  • Anand Pandey

    (Symbiosis Institute of Technology, SIU)

Abstract

Condition based Maintenance helps in predicting the condition of machines well in advance to take the decision for most cost optimized maintenance activity. By various developments in identifying the condition of machines, the concept of predictive maintenance is getting well established now. The industry has also begun to apply the lessons learned in sheet metal tooling. A number of studies have shown the methodology for tracking the condition of tooling. Unlike machine tools, sheet metal tooling poses a lot of technical as well as economic challenges in preparing a realistic model to demonstrate the application of condition-based monitoring for predictive maintenance. Selecting the tooling, identification of marginal elements, data capturing and synthesis, establishing a threshold limit for the condition selected, and developing the mathematical model to give an effective solution to the user are major steps in the process. A case of high-speed progressive tooling is depicted here to clarify the systematic methodology to be followed in implementing predictive maintenance and to provide a user-friendly solution. A case study illustrates the method for providing a cost optimized trigger for maintenance.

Suggested Citation

  • Ashutosh Kolhatkar & Anand Pandey, 2023. "Predictive maintenance methodology in sheet metal progressive tooling: a case study," 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 980-989, December.
    • Handle: RePEc:spr:ijsaem:v:14:y:2023:i:4:d:10.1007_s13198-021-01564-3
    DOI: 10.1007/s13198-021-01564-3
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