What is it about?
A process may have constant work-content (repetitive process), random one (semi-repetitive) or no typical work-content at all (non-repetitive process). We denote these identity-full, random-identity and identity-less processes, respectively. In this article, we model in a single unified platform the statistical distribution of process time for all three categories of processes, becoming normal/lognormal for identity-full processes and exponential for identity-less processes. The distribution of the sample average is derived, and a Repetitive Measure (RM) suggested. Changes in distribution shape resulting from instability of work-content are thoroughly studied.
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Why is it important?
"Process identity" is a new term, introduced in this article, which links shape characteristics of process-time distribution to variability in process work-content. This paves the way to implement SPC to monitor work-process repetitiveness.
Perspectives
Article authored following a comprehensive analysis of surgery times (based on real data).
Professor Emeritus Haim Shore
Ben-Gurion University of the Negev
Read the Original
This page is a summary of: A novel approach to modeling steady‐state process‐time with smooth transition from repetitive to semi‐repetitive to non‐repetitive (memoryless) processes, Quality and Reliability Engineering International, June 2023, Wiley,
DOI: 10.1002/qre.3386.
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