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Articles

Using a QCAC–Entropy–TOPSIS approach to measure quality characteristics and rank improvement priorities for all substandard quality characteristics

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Pages 3110-3124 | Received 22 May 2013, Accepted 30 Oct 2013, Published online: 06 Dec 2013
 

Abstract

A key issue faced within the manufacturing industry is determining how to measure quality characteristics and prioritise improvements to be made to all substandard quality characteristics of a product with respect to resource requirements and performance improvement potential. This study proposes a QCAC–Entropy–TOPSIS approach in order to address this issue. It combines the Quality Characteristic Analysis Chart (QCAC), entropy method and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The proposed method is not only helpful to measure and determine whether the quality characteristics meet 6σ, 5σ, 4σ or 3σ but also to rank improvements in all substandard quality characteristics of a product in light of resource requirements and potential for performance improvements simultaneously, making it suitable to all manufacturing industries. Moreover, it also can be a powerful tool for analysing the problems that lead to substandard quality characteristics due to poor accuracy and/or precision. Firstly, using the QCAC, the substandard quality characteristics of the product can be determined and the corresponding values of the Discrimination Distance (DD) can then be computed. Subsequently, all the substandard quality characteristics can be regarded as alternatives when conducting entropy and TOPSIS analyses. Secondly, the weights of the evaluation criteria can be calculated by using the entropy method. Lastly, the weights of the evaluation criteria and the values of DD can be substituted into the TOPSIS method. The manufacturer can then categorically prioritise improvement options for all substandard quality characteristics with respect to resource requirements, and consider potential for performance improvements simultaneously. An example is provided for a bicycle quick release manufacturer to illustrate in detail the calculation process of the developed approach. Finally, the advantages of the proposed method are also given through comparisons with Process Capability Analysis Chart and TOPSIS methods.

Acknowledgements

We are thankful to anonymous referees and the editor for their valuable comments and suggestions.

Funding

This work was supported by the National Science Council of Taiwan [grant number NSC 102-2221-E-468-008].

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