S. Cox
Application of a Multivariate Process Control Technique for Set-Up Dominated Low Volume Operations
Cox, S.; Anderson, S.; Gray, N.; Vogt, O.; Kotsialos, A.; Goh, Yee Mey; Case, Keith
Authors
S. Anderson
N. Gray
O. Vogt
A. Kotsialos
Yee Mey Goh
Keith Case
Abstract
In traditional high-volume manufacturing applications, the timing of control adjustments to processes is based on parametric Statistical Process Control (SPC) methods, such as Shewhart X & R charts. In high-value, high-complexity and low-volume industries, where production runs are in the order of tens rather than thousands, traditional SPC approaches are not easily applicable. A manufactured component's complexity, with multiple critical features to monitor, increases the difficulty for a process operator to maintain all of them within their design tolerances. In response to this, this paper presents a framework of nonparametric SPC, called multivariate Set-Up Process Algorithm (mSUPA), for managing control adjustment when required. mSUPA uses a simple to interpret traffic light system for alerting process operators when an adjustment is required. mSUPA is underpinned by multivariate statistics and probability theory for validating a process set up. The case of mSUPA application to a real industry process is discussed.
Presentation Conference Type | Conference Paper (Published) |
---|---|
Conference Name | 14th International Conference on Manufacturing Research |
Start Date | Sep 6, 2016 |
End Date | Sep 8, 2016 |
Publication Date | Sep 1, 2016 |
Deposit Date | Feb 5, 2017 |
Publicly Available Date | Feb 6, 2017 |
Pages | 535-540 |
Series Title | Advances in transdisciplinary engineering |
Series Number | 3 |
Series ISSN | 2352-751X,2352-7528 |
Book Title | Advances in manufacturing technology XXX : proceedings of the 14th International Conference on Manufacturing Research, incorporating the 31st National Conference on Manufacturing Research, September 6-8, 2016, Loughborough University, UK. |
ISBN | 9781614996675 |
DOI | https://doi.org/10.3233/978-1-61499-668-2-535 |
Public URL | https://durham-repository.worktribe.com/output/1149127 |
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Copyright Statement
The final publication is available at IOS Press through https://doi.org/10.3233/978-1-61499-668-2-535
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