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...
| Main Authors: | , , |
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| Format: | Journal Article |
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Srilankan Journal of Applied Statistics
2012
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| Online Access: | http://hdl.handle.net/20.500.11937/24316 |
| _version_ | 1848751394027208704 |
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| author | Rajalingam, Sokkalingam Bono, A. Sulaiman, J. |
| author_facet | Rajalingam, Sokkalingam Bono, A. Sulaiman, J. |
| author_sort | Rajalingam, Sokkalingam |
| building | Curtin Institutional Repository |
| collection | Online Access |
| 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 center points) 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. |
| first_indexed | 2025-11-14T07:52:01Z |
| format | Journal Article |
| id | curtin-20.500.11937-24316 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T07:52:01Z |
| publishDate | 2012 |
| publisher | Srilankan Journal of Applied Statistics |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-243162017-01-30T12:42:11Z Determining optimal moulding process parameters by two level factorial design with center points Rajalingam, Sokkalingam Bono, A. Sulaiman, J. Parameters ANOVA Factors Target Values Process Response Moulding 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 center points) 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. 2012 Journal Article http://hdl.handle.net/20.500.11937/24316 Srilankan Journal of Applied Statistics fulltext |
| spellingShingle | Parameters ANOVA Factors Target Values Process Response Moulding Rajalingam, Sokkalingam Bono, A. Sulaiman, J. Determining optimal moulding process parameters by two level factorial design with center points |
| title | 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_short | 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 |
| topic | Parameters ANOVA Factors Target Values Process Response Moulding |
| url | http://hdl.handle.net/20.500.11937/24316 |