Optimal Design of One-Sided Exponential Adaptive EWMA Scheme Based on Median Run Length

High-quality processes, characterized by low defect rates, typically exhibit an exponential distribution for time-between-events (TBE) data. To effectively monitor TBE data, one-sided exponential Adaptive Exponentially Weighted Moving Average (AEWMA) schemes are introduced. However, the run length (...

Full description

Saved in:
Bibliographic Details
Published in:Algorithms 2025-01, Vol.18 (1), p.5
Main Authors: Qiao, Yulong, Wu, Zixing, Zhang, Qian, Xu, Qin, Jin, Ge
Format: Article
Language:English
Subjects:
adaptive scheme
Business metrics
Design optimization
Earthquakes
EWMA
exponential distribution
Markov analysis
Markov chains
Mean
Median (statistics)
median run length
optimal design
Parameter estimation
Probability distribution functions
Random variables
Statistical process control
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:High-quality processes, characterized by low defect rates, typically exhibit an exponential distribution for time-between-events (TBE) data. To effectively monitor TBE data, one-sided exponential Adaptive Exponentially Weighted Moving Average (AEWMA) schemes are introduced. However, the run length (RL) distribution varies with the magnitude of the process mean shift, rendering the median run length (MRL) a more pertinent performance metric. This paper investigates the RL properties of one-sided exponential AEWMA schemes using a Markov chain method. An optimal design procedure based on MRL is developed to enhance the one-sided exponential AEWMA scheme. Comparative analyses reveal that the one-sided exponential AEWMA scheme provides better balanced protection against both minor and major shifts in the process mean compared to EWMA-type and Shewhart schemes. Finally, two practical case studies illustrate the application of AEWMA schemes in manufacturing.
ISSN:1999-4893
1999-4893
DOI:10.3390/a18010005