Development of sustainable material selection for automotive bumper fascia using analytical hierarchy proses (AHP)
Selection of sustainable material is very essential for the development process of a new product. Therefore, the right decision on selection of the appropriate material is necessary in order to support sustainable development requirements. The main objective this study is to propose a sustainable m...
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| Format: | Thesis |
| Language: | English English |
| Published: |
2013
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| Subjects: | |
| Online Access: | http://eprints.utem.edu.my/id/eprint/14970/1/Development%20of%20sustainable%20material%20selection%20for%20automotive%20bumper%20fascia%20using%20analytical%20hierarchy%20proses%20%28AHP%29.pdf http://eprints.utem.edu.my/id/eprint/14970/2/Development%20of%20a%20sustainable%20material%20selection%20for%20automotive%20bumper%20fascia%20using%20Analytical%20Hierarchy%20Process.pdf |
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| Summary: | Selection of sustainable material is very essential for the development process of a new product. Therefore, the right decision on selection of the appropriate material is necessary
in order to support sustainable development requirements. The main objective this study is to propose a sustainable material selection framework for automotive bumper fascia using
analytical hierarchy process (AHP). AHP method helps to perform decision-making process to summarize all the importance of each criterion into one prioritized value.
Various factors and sub-factors that influence the selection process were considered. To demonstrate the proposed sustainable material selection framework, six different types of
materials were considered. The results revealed that Polyamides, P A6 with 30% GFR is the most appropriate sustainable material for automotive bumper fascia because it has the highest percentage of priority value of 19% compared to the other material. The final judgement of the material is gained by performing 4 scenarios of the sensitivity analysis and the analysis showed that it is proven that P A6 with 30% GFR is the most optimum decision. |
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