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https://doi.org/10.3...arrow_drop_down
https://doi.org/10.31399/asm.t...
Part of book or chapter of book . 2009 . Peer-reviewed
Data sources: Crossref
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Design of Experiments

Design of Experiments

Abstract

Abstract After the failure analysis team hypothesizes failure causes, prepares a failure mode assessment and assignment, and evaluates all potential failure causes, it may find in some cases that several causes are still suspect but cannot be confirmed. In this situation, an experiment is necessary to confirm or rule out suspected causes. This chapter discusses two predominant methods for doing this, namely analysis of variance (ANOVA) and Taguchi methods (a more powerful technique based on ANOVA).

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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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