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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| Format: | Conference Paper |
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Institute of Applied Statistics, Sri Lanka
2011
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| Online Access: | http://hdl.handle.net/20.500.11937/5018 |
| _version_ | 1848744678030049280 |
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| author | Sokkalingam, Rajalingam |
| author2 | Shelton Peiris |
| author_facet | Shelton Peiris Sokkalingam, Rajalingam |
| author_sort | Sokkalingam, Rajalingam |
| 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 | 2025-11-14T06:05:16Z |
| format | Conference Paper |
| id | curtin-20.500.11937-5018 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T06:05:16Z |
| publishDate | 2011 |
| publisher | Institute of Applied Statistics, Sri Lanka |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-50182023-01-18T08:46:46Z Determining Optimal Moulding Process Parameters by Two Level Factorial Design with Center Points Sokkalingam, Rajalingam Shelton Peiris Chandima Tilakaratne 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. 2011 Conference Paper http://hdl.handle.net/20.500.11937/5018 Institute of Applied Statistics, Sri Lanka restricted |
| spellingShingle | Parameters ANOVA Factors Target Values Process Response Moulding Sokkalingam, Rajalingam 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/20.500.11937/5018 |