The priorities criteria of product design toward affective quality using technique for order preference by similarity to ideal solution (TOPSIS) and fuzzy TOPSIS : case study (toothbrush)

Kudsi, Muhamad Hanafi (2014) The priorities criteria of product design toward affective quality using technique for order preference by similarity to ideal solution (TOPSIS) and fuzzy TOPSIS : case study (toothbrush). Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)

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Abstract

This project carries the analysis about the importance of personality variables as implicit relationship to the design of products based on an integration of engineering decisions to customer needs, especially since the functional and affective needs are no longer empower a competitive edge and as the only determinant to match customers needs. There were 2 surveys methods are used for this study which is interview and questionnaire. There were 500 respondents were involved to answer the questionnaires developed contains of 8 design of tooth brush and 6 of Kansei Words. The Kansei Words is ‘Stylish’ (ST), ‘Durable’ (DU), ‘Unique’ (UN), ‘Simple’ (SI), ‘Up to Date’ (UP) and ‘Rare’ (RA). Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Fuzzy Criteria (Multi-Attribute) Decision Making (FCDM) are used In order to determine and analyze the level of customer satisfaction or customer preferences, to evaluate the results, this project employ statistical approach using software SPSS. The purpose of the Post test is to decide the accuracy pertinent to the rank obtained. 30 post test questionnaire had been distribute at the same respondent including the new design had been propose. To evaluate the post test data, it uses the same method to evaluate 500 respondents. The last part, every objective defined is answered based on survey and analysis conducted. The main objective of this study is to analyze the customer preference towards the design of the products and characteristic based on parts or components using Technique for Order Preference by Similarity to Ideal Solution and Fuzzy Multi-Attribute Decision Making (MCDM) in the product development towards Kansei Engineering.

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