Anomaly Detec­tion in Quality Testing


End-of-Line testing and quality secur­ance of tech­nical compo­nents is often char­ac­ter­ized with uncer­tain­ties about the detec­tion of quality and perfor­mance deficits 


Unsu­per­vised Clus­tering Analysis detect anom­alies and outlier using testing and statis­tical distri­b­u­tion data and can iden­tify roots for high percentage of return



  • Root cause iden­ti­fi­ca­tion to cut prob­lems
  • Reduced return rate
  • Prevents the delivery of compo­nents below quality stan­dards

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