SIMULATED SHEWHART CONTROL CHART FOR MONITORING VARIANCE COMPONENTS

Tzong‐Ru Tsai · Yi-Wei Hsieh

5 citations0/0 files storedInternational Journal of Reliability Quality and Safety Engineering

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Advanced Statistical Process Monitoring Fault Detection and Control Systems Optimal Experimental Design Methods

Abstract

Shewhart control charts based on the simulation method are proposed for monitoring separate variance components of the single-factor random effect model. Monte Carlo simulation results show that the proposed control charts have competitive performance relative to the approximate Shewhart regression control charts (ARSCCs) proposed by Chang and Gan2 in terms of the average run length (ARL). Compared with the ARSCCs, our control charts can be constructed easily with less sample resources. The application of our proposed method is illustrated with two examples.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 5 citations exist upstream.

References

2006Design and Analysis of Experiments 1995Statistical process control with several components of common cause variability 1995Shewhart-Type Charts in Nonstandard Situations 1994Monitoring Variance Components 2004Shewhart Charts for Monitoring the Variance Components 1999Control charts for random and fixed components of variation in the case of fixed wafer locations and measurement positions

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

Imported from OpenAlex (CC0) — nothing here is generated.