The Indian manufacturing sector depends heavily on the foundry industry’s performance, and the reliability of the casting process is crucial in ensuring product quality and maintaining operational efficiency. The present research provides a comprehensive evaluation of failure patterns in the selected unit of a steel casting manufacturing company using the Failure Mode, Effects and Criticality Analysis (FMECA). The case study employs a generic guideline for identifying and solving machinery maintenance-related issues in the selected firm. The analysis provides the management with a unified approach to identify failure patterns and their potential impact and take proactive steps to resolve the failure problems before they occur. The results of this research will provide the steel casting industry with a framework to capture important information, prioritize maintenance interventions and develop strategies to augment reliability, reduce costs and maintain product consistency across the system.

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Failure Mode Effects and Criticality Analysis of a Steel Casting Unit: A Case Study

  • Adharsh Gangan,
  • A. Akash Sasidharan,
  • M. Amal Krishna,
  • Sandra Koshy Vaidyan,
  • E. N. Anilkumar,
  • C. R. Vishnu

摘要

The Indian manufacturing sector depends heavily on the foundry industry’s performance, and the reliability of the casting process is crucial in ensuring product quality and maintaining operational efficiency. The present research provides a comprehensive evaluation of failure patterns in the selected unit of a steel casting manufacturing company using the Failure Mode, Effects and Criticality Analysis (FMECA). The case study employs a generic guideline for identifying and solving machinery maintenance-related issues in the selected firm. The analysis provides the management with a unified approach to identify failure patterns and their potential impact and take proactive steps to resolve the failure problems before they occur. The results of this research will provide the steel casting industry with a framework to capture important information, prioritize maintenance interventions and develop strategies to augment reliability, reduce costs and maintain product consistency across the system.