A risk-based approach to forecasting component obsolescence

• Published in: Microelectronics and reliability Vol. 127; p. 114330
• Main Authors: Mastrangelo, Christina M., Olson, Kara A., Summers, Dennis M.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.12.2021
• Subjects: Conditional Weibull probability distribution; Diminishing manufacturing sources and materials shortages (DMSMS); Electronic component obsolescence; Risk-based obsolescence management; Risk-based obsolescence management; Diminishing manufacturing sources and materials shortages (DMSMS); Electronic component obsolescence; Conditional Weibull probability distribution
• ISSN: 0026-2714; 1872-941X
• DOI: 10.1016/j.microrel.2021.114330

Prediction of electronic component obsolescence is a critical aspect of managing diminishing manufacturing sources and materials shortages (DMSMS). Systems with intended long operating lifetimes combined with shorter market-driven lifetimes of components therein drive the need for obsolescence management. This work defines and describes a Weibull-based conditional probability method, a risk-based approach to predicting microelectronic component obsolescence. The conditional probability method is used to determine the likelihood of a component becoming obsolete within a specified forecast horizon given that the component is still procurable at the time of analysis. The method is compared to a mean time to failure (MTTF)-based approach with a case study using a ten-year retrospective analysis. The case study demonstrates the viability of the conditional probability method and shows overall improved accuracy especially for more recent analysis periods. A risk-based approach also better enables component-to-component comparison which can help prioritize DMSMS efforts. •A Weibull-based conditional probability method is defined and described.•The method is a risk-based approach to predicting electronic component obsolescence.•A case study is presented using linear regulators.•Results are comparable or better than a mean time to failure-based approach.