Abstract
Defining properly the time distribution of a steady-state process is crucial to its management. A common practice is to assume that process-time is normally distributed for repetitive processes (process has constant work-content), and exponentially for non-repetitive processes (memoryless; no characteristic work-content). This dichotomous distinction ignores the majority of processes, residing in between the two extreme scenarios, the semi-repetitive ones. These processes own a characteristic duration time (as reflected in the mode), yet part of work-content (“process identity”) randomly varies between cycles. In this paper, we develop a unified platform to model process-time, comprising all three types of processes. The effects of work-content instability on shape characteristics of process-time distribution are studied, and process repetitiveness measure, possibly to be used to monitor work-content instability, is defined. The generalized gamma distribution is employed to approximate the (unknown) distribution of process-time sample mean, becoming exact for the two extreme scenarios (repetitive and non-repetitive processes).
Original language | English |
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Pages (from-to) | 220-235 |
Number of pages | 16 |
Journal | Quality and Reliability Engineering International |
Volume | 40 |
Issue number | 1 |
DOIs | |
State | Published - 1 Feb 2024 |
Keywords
- generalized gamma distribution
- generalized memoryless property
- identity-full/less distributions
- modeling process-time
- process repetitiveness measure
- process work-content instability
ASJC Scopus subject areas
- Safety, Risk, Reliability and Quality
- Management Science and Operations Research