A heuristic threshold policy for fault detection and diagnosis in multivariate statistical quality control environments
- 19 October 2012
- journal article
- research article
- Published by Springer Science and Business Media LLC in The International Journal of Advanced Manufacturing Technology
- Vol. 67 (5-8), 1231-1243
- https://doi.org/10.1007/s00170-012-4561-x
Abstract
No abstract availableKeywords
This publication has 13 references indexed in Scilit:
- A Multi-Stage Two-Machines Replacement Strategy Using Mixture Models, Bayesian Inference, and Stochastic Dynamic ProgrammingCommunications in Statistics - Theory and Methods, 2011
- A Bayesian Inference and Stochastic Dynamic Programming Approach to Determine the Best Binomial DistributionCommunications in Statistics - Theory and Methods, 2009
- Multivariate Bayesian process control for a finite production runEuropean Journal of Operational Research, 2009
- A new statistical process control method to monitor and diagnose bivariate normal mean vectors and covariance matrices simultaneouslyThe International Journal of Advanced Manufacturing Technology, 2008
- Decision-making in detecting and diagnosing faults of multivariate statistical quality control systemsThe International Journal of Advanced Manufacturing Technology, 2008
- Multivariate statistical process control charts: an overviewQuality and Reliability Engineering International, 2006
- Optimal adaptive control policy for joint machine maintenance and product quality controlEuropean Journal of Operational Research, 2006
- Fault Diagnosis in Multivariate Control Charts Using Artificial Neural NetworksQuality and Reliability Engineering International, 2005
- A multivariate exponentially weighted moving average control chart for monitoring process variabilityJournal of Applied Statistics, 2003
- A Multivariate Exponentially Weighted Moving Average Control ChartTechnometrics, 1992