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Multivariate process parameter change identification by neural network
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Mathematical Science.
2013 (English)In: The International Journal of Advanced Manufacturing Technology, ISSN 0268-3768, E-ISSN 1433-3015, Vol. 69, no 9-12, p. 2261-2268Article in journal (Refereed) Published
Abstract [en]

Whenever there is an out-of-control signal in process parameter control charts, maintenance engineers try to diagnose the cause near the time of the signal which is not always lead to prompt identification of the source(s) of the out-of-control condition and this in some cases yields to extremely high monetary loses for manufacture owner. This paper applies multivariate exponentially weighted moving average (MEWMA) control charts and neural networks to make the signal identification more effective. The simulation of this procedure shows that this new control chart can be very effective in detecting the actual change point for all process dimension and all shift magnitudes considered. This methodology can be used in manufacturing and process industries to predict change points and expedite the search for failure causing parameters, resulting in improved quality at reduced overall cost. This research shows development of MEWMA by usage of neural network for identifying the step change point and the variable responsible for the change in the process mean vector.

Place, publisher, year, edition, pages
2013. Vol. 69, no 9-12, p. 2261-2268
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
URN: urn:nbn:se:ltu:diva-12696DOI: 10.1007/s00170-013-5200-xISI: 000327095900030Scopus ID: 2-s2.0-84892371787Local ID: bdbcaab3-37f3-415c-9607-e6abe6dde418OAI: oai:DiVA.org:ltu-12696DiVA, id: diva2:985647
Note
Validerad; 2013; 20130708 (farahm)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-07-10Bibliographically approved

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Ahmadzadeh, FarzanehLundberg, JanStrömberg, Thomas

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