Please use this identifier to cite or link to this item: https://doi.org/10.1108/02656719910218238
Title: A quality monitoring and decision-making scheme for automated production processes
Authors: Xie, M. 
Lu, X.S.
Goh, T.N. 
Chan, L.Y.
Keywords: Attribute control charts
Automated operations
Process improvement
Statistical process control
Issue Date: 1999
Source: Xie, M.,Lu, X.S.,Goh, T.N.,Chan, L.Y. (1999). A quality monitoring and decision-making scheme for automated production processes. International Journal of Quality and Reliability Management 16 (2) : 148-157. ScholarBank@NUS Repository. https://doi.org/10.1108/02656719910218238
Abstract: Traditional attribute control charts are based on the monitoring of the number of nonconforming items in a sample of fixed size. In modern manufacturing processes, since items can be checked automatically, use of samples of a fixed subjective size with traditional charts is not suitable for on-line continuous inspection. Furthermore, the sample size usually has to be large when the process fraction nonconforming is not reasonably high. If a decision is to be made only when a sufficient number of items are manufactured and inspected, many nonconforming items might have been produced. In this paper, a control scheme is presented based on the monitoring of cumulative counts of items inspected. This procedure will limit the number of consecutive nonconforming items to a small value when the process has suddenly deteriorated, can detect a sudden process shift quickly and is suitable for continuous inspection processes. The exact probability control limits are derived and the implementation procedure is described. © MCB UP Ltd.
Source Title: International Journal of Quality and Reliability Management
URI: http://scholarbank.nus.edu.sg/handle/10635/54749
ISSN: 0265671X
DOI: 10.1108/02656719910218238
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

38
checked on Dec 12, 2017

Page view(s)

19
checked on Dec 15, 2017

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.