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Failure Analysis

Identification and correction of the underlying problem Understanding why a part failed is vital to prevent future failures. When parts fail, it can have an effect on the delivery of goods and the safety of the resources as well as result in costly repairs and downtime. Typical examples of systems/equipment that can be analyzed are electrical generators, heat exchangers, valves, control systems, pumps, components of gas turbines and compressors.

Failure Analysis will disclose:
Why the event, failure or breakdown occurred. How future failures can be controlled or eliminated Statistical Models to Identify the Causes of Failure / Breakdown

  • Failure analysis and reliability models of the repairable systems, focus on the model capability to identify, control and eliminate future failures, for a system. The core is the forecasting, using the appropriate time series method, taking into account different maintenance strategies, spare parts and manpower policies, skills in operation and external stress factors.
  • Root Cause Analysis and Fishbone Diagram for Cause and Effect
  • Pareto Analysis
  • Monte Carlo Simulation for Forecasting Failures and Failure Cause
  • Analyzing Failure data with Competing Risks using survival Analysis
  • Forecasting Number of Failures and Time Between Failures
  • Forecasting Number of Failures Using Time Series Method
  • Monitoring Number of Failures using Control Chart
  • Prioritization of FMEA
  • Breakdown Analysis
  • Reliability and Availability of Asset

Benefits

  • Servers are an indispensible component of proactive and reliability centered maintenance
  • Uses advanced investigative techniques
  • Identifies early (unlikely) life failures
  • Extends equipment lifetime
  • Reduced cost of maintenance
  • Improves availability “up-time” and increased production
  • Increases safety
  • Easy to identify for potential losses where risk is included