[Home ] [Archive]    
:: Main :: About :: Current Issue :: Archive :: Search :: Submit :: Registration ::
:: Volume 2, Issue 1 (vol 2. No 1 2010) ::
IJOR 2010, 2(1): 1-16 Back to browse issues page
Monitoring and diagnosing a two-stage production process with attribute characteristics
Aghaie , Samimi , Asadzadeh
Abstract:   (16457 Views)

  Multistage process monitoring has recently attracted notable attention in that the statistical relationships between quality variables are taken into account. Here, we dealt with the problem of monitoring and diagnosing a two-stage production process with attribute characteristics in which the outgoing quality variable is impacted by the incoming quality variable from the first process stage. Based on a sampling procedure which inspects each produced items, these attribute characteristics are assumed to follow binomial and Poisson distributions. Several monitoring techniques including a new method based on the generalized Poisson distribution are presented and the comparison is made to evaluate the effectiveness of these procedures. Moreover, some fault diagnosis methods are fully explored in order to alleviate the identification of the process stage responsible for the out-of-control conditions. The results of the simulation based studies reveal that a combined approach consisting of a proportion defective control chart and an adjusted control chart is quite efficacious in addressing the problems with regard to both the detection power and the fault diagnosis.

Keywords: Multistage processes, Fault diagnosis, Dependent attribute quality characteristics, Generalized Poisson distribution.
Full-Text [PDF 603 kb]   (4161 Downloads)    
Type of Study: Original |
Received: 2011/04/20
Add your comments about this article
Your username or Email:

Write the security code in the box >


XML     Print



Volume 2, Issue 1 (vol 2. No 1 2010) Back to browse issues page
مجله انجمن ایرانی تحقیق در عملیات Iranian Journal of Operations Research
Persian site map - English site map - Created in 0.07 seconds with 30 queries by YEKTAWEB 3701