Data Acquisition: a Key Challenge for Quality and Reliability Improvement

Necip Doganaksoy & Gerald Hahn


Statistical analyses for quality and reliability improvement are only as good as the data upon which they are based. In this Webinar we urge careful consideration be given up front to procuring the right data and provide guidelines for meaningful data acquisition. Most quality and reliability training programs focus on methods for analysis and just presume that the right data are available. Unfortunately, this is infrequently the case. The consequence is limited evaluations at the best and flawed conclusions at the worst. We briefly describe some common data gathering scenarios and comment on often encountered obstacles in using observational (i.e., happen to be available) data. We then provide some hints for effective data acquisition. We conclude by proposing a disciplined step-by-step approach for data gathering, illustrating this with a study to assess the reliability of a newly designed washing machine. This Webinar is based upon Chapter 11 of the presenters� A Career in Statistics: Beyond the Numbers, published by Wiley in 2011 and their article on �Getting Good Data Up Front: A Key Challenge� in Quality Engineering (2012) Vol. 24, No. 4, 446-459. The objective of this Webinar is to impart to participants the criticality in quality and reliability assessment and improvement programs of planning to get the right data and to provide guidance in so doing. The objective of this Webinar is to impart to participants the criticality in quality improvement programs of getting the right data up front and to provide guidance in so doing.

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