Risk Methodology for Failed Hardware

Abstract

This paper deals with the development of a risk methodology of failed hardware components. This is important because it is not prudent to use hardware (that did not perform per specification) without failure analysis or corrective action. The subject of this article arose from the need to provide a detailed probabilistic analysis to calculate the change in probability of failures with respect to the base or non-failed hardware. The risk methodology used for the analysis is primarily based on principles of Monte Carlo simulation. The random variables in the analysis are: maximum time of operation (MTO) and operation time of each unit (OTU). The failure of a unit is considered to happen if OTU is less than MTO for the normal operational period (NOP) in which this unit is used. NOP as a whole uses a total of four units. Two cases are considered. In the first specialized scenario, any operation or system failure is considered to fail if any of the units used during the NOP fails. In the second specialized scenario, any operation or system failure is considered to fail only if any two of the units used during the NOP fail together. The reason for using the second scenario is that it is critical for both units to function for the redundant system. The probability of failure of the units and the system as a whole is determined for three kinds of systems: perfect system, imperfect system 1, and imperfect system 2. In a perfect system, the operation time of the failed unit is the same as that of the MTO. In an imperfect system 1, the operation time of the failed unit is assumed as 1% of MTO. In an imperfect system 2, the operation time of the failed unit is assumed as zero. In addition, simulated operation time of failed units is assumed as 10% of the corresponding units before zero value. Monte Carlo simulation analysis is used for this study. The necessary software has been developed as part of this study to perform the reliability calculations. The results of the analysis showed that the predicted change in failure probability (PF) for the previously failed units is as high as 49% above the baseline (perfect system) for the worst case. The predicted change in system PF for the previously failed units is as high as 36% for single-unit failure without any redundancy. For redundant systems, with dual unit failure, the predicted change in PF for the previously units is as high as 16%. These results will help management to make decisions regarding the consequences of using previously failed units without adequate failure analysis or corrective action.