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Multivariate proces...
Multivariate process parameter change identification by neural network
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- Ahmadzadeh, Farzaneh (author)
- Luleå tekniska universitet,Drift, underhåll och akustik,Luleå University of Technology, Luleå, Sweden
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- Lundberg, Jan (author)
- Luleå tekniska universitet,Drift, underhåll och akustik,Luleå University of Technology, Luleå, Sweden
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- Strömberg, Thomas (author)
- Luleå tekniska universitet,Matematiska vetenskaper,Luleå University of Technology, Luleå, Sweden
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(creator_code:org_t)
- 2013-08-02
- 2013
- English.
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In: The International Journal of Advanced Manufacturing Technology. - : Springer Science and Business Media LLC. - 0268-3768 .- 1433-3015. ; 69:9-12, s. 2261-2268
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https://urn.kb.se/re...
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Abstract
Subject headings
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- 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.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Samhällsbyggnadsteknik -- Annan samhällsbyggnadsteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Civil Engineering -- Other Civil Engineering (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering (hsv//eng)
Keyword
- Drift och underhållsteknik
- Operation and Maintenance
Publication and Content Type
- ref (subject category)
- art (subject category)
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