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A framework for multivariate process monitoring and diagnosis

Masood, Ibrahim and Hassan, Adnan (2013) A framework for multivariate process monitoring and diagnosis. Applied Mechanics and Materials , 315. pp. 374-379. ISSN 1660-9336


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Monitoring and diagnosis of mean shifts in manufacturing processes become more challenging when involving two or more correlated variables. Unfortunately, most of the existing statistical process control frameworks are only effective in shift detection but suffers high false alarm, that is, imbalanced performance monitoring. The problem becomes more complicated when dealing with small shift particularly in identifying the causable variables. In this research, a kamework to address balanced monitoring and accurate diagnosis was investigated. Design considerations involved extensive simulation experiments to select input representation based on raw data and statistical features, recognizer design structure based on synergistic model, and monitoring-diagnosis approach based on two stages technique. The study focuses on correlated process mean shifts for cross correlation function, p = 0.1 - 0.9 and mean shift, p = + 0.75 - 3.00 standard deviations. The proposed design, that is, an Integrated Multivariate Exponentially Weighted Moving Average with Artificial Neural Network gave superior performance, namely, average run length, ARLl = 3.18 - 16.75 (for out-of-control process), A& = 452.13 (for incontrol process) and recognition accuracy, RA = 89.5 - 98.5%. This research has provided a new perspective in realizing balanced monitoring and accurate diagnosis of multivariate correlated process mean shifts.

Item Type: Article
Uncontrolled Keywords: balanced monitoring and accurate diagnosis; integrated MEWMA-ANN; multivariate process; statistical features; synergistic-ANN
Subjects: T Technology > TS Manufactures > TS155-194 Production management. Operations management
Divisions: Faculty of Mechanical and Manufacturing Engineering > Department of Manufacturing and Industrial Engineering
Depositing User: Normajihan Abd. Rahman
Date Deposited: 24 Jul 2013 04:16
Last Modified: 24 Jul 2013 04:16
URI: http://eprints.uthm.edu.my/id/eprint/3975
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