Enhancing qualification via the use of diagnostics and prognostics techniques
Abstract Qualification is a process that demonstrates whether a product meets or exceeds specified requirements. Testing and data analysis performed within a qualification procedure should verify that products satisfy those requirements, including reliability requirements. Most of the electronics industry qualifies products using procedures dictated within qualification standards. A review of common qualification standards reveals that those standards do not consider customer requirements or the product physics‐of‐failure in that intended application. As a result, qualification, as represented in the reviewed qualification standards, would not meet our definition of qualification for reliability assessment. This paper introduces the application of diagnostics and prognostics techniques to analyze real‐time data trends while conducting qualification tests. Diagnostics techniques identify anomalous behavior exhibited by the product, and prognostics techniques forecast how the product will behave during the remainder of the qualification test and how the product would have behaved if the test continued. As a result, combining diagnostics and prognostics techniques can enable the prediction of the remaining time‐to‐failure for the product undergoing qualification. Several ancillary benefits related to an improved testing strategy, parts selection and management, and support of a prognostics and health management system in operation also arise from applying prognostics and diagnostics techniques to qualification.
Authors
- Diganta Das (ORCID: https://orcid.org/0000-0001-9097-2118)
- A. Raghu Ram (ORCID: https://orcid.org/0000-0001-8003-7492)
Institutions
- Life Cycle Engineering (United States) (US)
- University of Maryland, College Park (US)
Publication Details
- Journal
- Quality and Reliability Engineering International
- Published
- 2024-08-05
- DOI
- https://doi.org/10.1002/qre.3634
- Citations
- 1
- Primary Topic
- Silicon Carbide Semiconductor Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.21