A Multiphase Decision Model for System Reliability Growth With Latent Failures

Abstract

Reliability growth testing becomes difficult to implement as the product development cycle continues to shrink. As a result, the new design is prone to latent failures due to design immaturity and uncertain operating condition. Reliability growth planning emerged as a new methodology to drive the reliability across the product lifetime. We propose a multiphase reliability growth model that sequentially determines and implements corrective actions (CAs) against surfaced and latent failure modes. Such a holistic approach enables the manufacturer to attain the reliability goal while ensuring the product time to market. We devise a CA effectiveness function to assess the tradeoff between the failure removal rate and the required resources. Rosen's gradient projection algorithm is used to determine the optimal resource allocation in each phase. The applicability and performance of the reliability growth model are demonstrated on a fleet of semiconductor testing equipment.Index Terms-Capital equipment, corrective action (CA) effectiveness, latent failure, power law model, reliability growth planning (RGP). NOMENCLATURE mNumber of surfaced failure modes by time t c . kNumber of latent failure modes that will occur between t c and t. t 1 , t c , and t Previous time, current time, and future time, respectively. μ i (t)

An Approach for Reliability Demonstration Test Based on Power‐Law Growth Model

“…The discrimination ratio is d ¼ θm θc ¼ 1:5. Meanwhile, when n is preset at 23, then S~Γ(23, 1) , Z~Γ (22,1), it can be calculated that ZS 1Àα ZS β ¼ 2:15:…”

“…Following the development of the growth stage in a complex repairable system, failures may occur in a series manner, while the degradation tests are not available. Ellner and Hall, Hall and Mosleh, Hall et al , Jin et al and Gaver and Jacobs have studied the modeling of the reliability growth stage in such a situation or growth mode. Likewise, Guo and Pan and Guo et al have proposed a series of RDT methods based on the reliability growth stage.…”

A Markov Chain-Based Testability Growth Model With a Cost-Benefit Function

“…Coit [17] presented a method to allocate test time to maximize the system's mean time between failures. Jin et al [18] presented a multiphase decision model for system reliability growth with latent failures. The above models assume resources to be continuous variables, whereas the resource allocation problem in TGT is an integer programming problem involving a discrete number of fix stages allocated to each failure mode.…”