Monitoring profile based on a linear regression model with correlated errors. Issue 3 (4th May 2018)

• Record Type: Journal Article
• Authors: Cheng, Tsung-Chi; Yang, Su-Fen
• Is Part Of: Quality technology & quantitative management. Volume 15:Issue 3(2018)
• Page Start: 393
• Page End: 412
• Publication Date: 2018-05-04
• Subjects: Correlated errors -- Hotelling's T2 statistic -- statistical process control; Quality control -- Periodicals; Quality control -- Statistical methods -- Periodicals; Industrial management -- Periodicals; Industrial management; Management -- Research -- Methodology -- Periodicals; Qualitative research -- Periodicals; Management; Quality control; Quality control -- Statistical methods; Periodicals; 658.00721
• DOI: 10.1080/16843703.2016.1226595
• Languages: English
• ISSNs: 1684-3703

Abstract

Abstract: Profile monitoring is becoming popular in the area of quality control. It is used when the process is characterized by the relationship between a response variable and some explanatory variables at each time period. This paper considers the situation where profiles are modeled parametrically using a multiple linear regression with random errors following an autoregressive moving-average process. Diagnostic schemes to find out-of-control samples are developed for this purpose. A simulation study examines the performance of the proposed approach based on the average run length criterion. Lastly, a real example illustrates the results, after considering both Phase I and Phase II schemes.