A, characterization of diagnosability conditions for variance components analysis in assembly operations

Variance component estimation algorithms, in conjunction with automated in-process measurement technology, can be effective tools for identifying and eliminating major sources of manufacturing variation in assembly processes. Whether a particular set of variation sources are diagnosable depends critically on how the sensor system is laid out. Diagnosability tests are mathematical in nature and provide little insight into why a particular sensor layout may be nondiagnosable or how to modify the layout to ensure diagnosability. This paper translates the mathematical diagnosability conditions into a set of more conceptually meaningful conditions that provide better insight into the reasons behind the nondiagnosability.