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MIL-HDBK-338 15 OCTOBER 1984 (2) The proper assignment of priority and the decision for failure analysis must be made with the aid of cognizant design engineers and systems engineers. (3) The status of all failure analyses must be known. It is of prime importance that failure analyses be expedited as priority demands and that corrective action be implemented as soon as possible. (4) The root cause of every failure must be understood. Without this understanding, no logically derived corrective actions can follow. (5) There must be a means of tabulating failure information for determining failure trends and the mean times between failures of system elements. There should also be a means for management visibility into the status of failure report dispositions and corrective actions. (6) The system must provide for a high level technical management approval; concurring in the results of failure analysis, the soundness of corrective action, and the completion of formal actions in the correction and recurrence prevention loop. (7) An extremely valuable assurance mechanism is to have active Government involvement in the surveillance of the adequacy of the failure reporting, analysis, and corrective action effort. In addition to MIL-HDBK-338-2, References 1 and 2 provide additional details on FRACAS systems. Also, relative to failure analysis of integrated circuits - by far the largest part population of electronic systems - Ref. 3, Microelectronics Failure Analysis Techniques, A Procedural Guide, is the most recent and comprehensive document available. 8.3 RELIABILITY DATA ANALYSIS From a reliability assessment viewpoint, failure data is used to: (1) determine the underlying probability distribution of time to failure and estimate its parameters (if not already known). (2) determine a point estimate of a specific reliability parameter, e.g., MTBF (3) determine a confidence interval that is believed to contain the true value of the parameter. Two methods are used to analyze failure data: (1) graphical methods (2) statistical analysis In many practical cases, graphical methods are simple to apply and produce adequate results for estimating the underlying distribution. They are 8-5

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