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Abstract:
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The reliability of product in service is very important to equipment manufacturers. Field repairs can be costly to both customers in lost productivity and to manufacturers who bear the expense of repairs. When field failures occur, it is critical to determine the root cause for rapid and effective corrective action. However, because of the continually increasing complexity of modern systems, identification of the source of the problem and resolution can be extremely challenging. We show how the application of statistical methods for the analysis and modeling of the reliability of repairable systems provided valuable insight into the origin of the failures. The consistency of the model predictions with field data lead to remediation and dramatically improved reliability. We'll review the model, assumptions, predictions, and agreement with field results.
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