Determining optimal moulding process parameters by two level factorial design with center points

Determining optimal process parameter setting critically influences productivity, quality and cost of production in the injection moulding industry. Previously production engineers used trial and error method to determine optimal process parameter setting. Inappropriate machine parameter settings ca...

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Main Authors: S Rajalingam, Awang Bono, Jumat Sulaiman
Format: Article
Language:English
Published: Institute of Applied Statistics, Sri Lanka (IASSL) 2011
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Online Access:https://eprints.ums.edu.my/id/eprint/19354/1/Determining%20optimal%20moulding.pdf
https://eprints.ums.edu.my/id/eprint/19354/
https://www.iappstat.lk/journal/ojs_old/index.php/sljap/article/view/10
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spelling my.ums.eprints.193542018-03-22T02:16:36Z https://eprints.ums.edu.my/id/eprint/19354/ Determining optimal moulding process parameters by two level factorial design with center points S Rajalingam Awang Bono Jumat Sulaiman TP Chemical technology Determining optimal process parameter setting critically influences productivity, quality and cost of production in the injection moulding industry. Previously production engineers used trial and error method to determine optimal process parameter setting. Inappropriate machine parameter settings can cause production and quality problems. In this paper the authors used a case study to investigate the moulding machine parameters which will affect the dimensions (length and width) in a plastic component. The machine process setting in use currently caused variations in the dimensions exceeding the specification limit. Therefore the experiment is needed to identify the optimal machine parameter setting which could be set to maintain the dimensions closest to the target value with smallest possible variation. A design of experiments (two level factorial design with centerpoints) was conducted to study the effect of three injection moulding process parameters (mould temperature, injection speed and injection pressure) versus dimensions (length and width). Finally, the optimal process parameters to maintain the dimensions closest to the target values were identified. Statistical results and analysis are used to provide better interpretation of the experiment. The models are form from ANOVA and the models passed the tests for normality and independence assumptions. Institute of Applied Statistics, Sri Lanka (IASSL) 2011 Article PeerReviewed text en https://eprints.ums.edu.my/id/eprint/19354/1/Determining%20optimal%20moulding.pdf S Rajalingam and Awang Bono and Jumat Sulaiman (2011) Determining optimal moulding process parameters by two level factorial design with center points. Sri Lankan Journal of Applied Statistics, 12. pp. 63-82. ISSN 2424-6271 https://www.iappstat.lk/journal/ojs_old/index.php/sljap/article/view/10
institution Universiti Malaysia Sabah
building UMS Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sabah
content_source UMS Institutional Repository
url_provider http://eprints.ums.edu.my/
language English
topic TP Chemical technology
spellingShingle TP Chemical technology
S Rajalingam
Awang Bono
Jumat Sulaiman
Determining optimal moulding process parameters by two level factorial design with center points
description Determining optimal process parameter setting critically influences productivity, quality and cost of production in the injection moulding industry. Previously production engineers used trial and error method to determine optimal process parameter setting. Inappropriate machine parameter settings can cause production and quality problems. In this paper the authors used a case study to investigate the moulding machine parameters which will affect the dimensions (length and width) in a plastic component. The machine process setting in use currently caused variations in the dimensions exceeding the specification limit. Therefore the experiment is needed to identify the optimal machine parameter setting which could be set to maintain the dimensions closest to the target value with smallest possible variation. A design of experiments (two level factorial design with centerpoints) was conducted to study the effect of three injection moulding process parameters (mould temperature, injection speed and injection pressure) versus dimensions (length and width). Finally, the optimal process parameters to maintain the dimensions closest to the target values were identified. Statistical results and analysis are used to provide better interpretation of the experiment. The models are form from ANOVA and the models passed the tests for normality and independence assumptions.
format Article
author S Rajalingam
Awang Bono
Jumat Sulaiman
author_facet S Rajalingam
Awang Bono
Jumat Sulaiman
author_sort S Rajalingam
title Determining optimal moulding process parameters by two level factorial design with center points
title_short Determining optimal moulding process parameters by two level factorial design with center points
title_full Determining optimal moulding process parameters by two level factorial design with center points
title_fullStr Determining optimal moulding process parameters by two level factorial design with center points
title_full_unstemmed Determining optimal moulding process parameters by two level factorial design with center points
title_sort determining optimal moulding process parameters by two level factorial design with center points
publisher Institute of Applied Statistics, Sri Lanka (IASSL)
publishDate 2011
url https://eprints.ums.edu.my/id/eprint/19354/1/Determining%20optimal%20moulding.pdf
https://eprints.ums.edu.my/id/eprint/19354/
https://www.iappstat.lk/journal/ojs_old/index.php/sljap/article/view/10
_version_ 1760229569598586880
score 13.18916