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Management Science Letters

ISSN 1923-9343 (Online) - ISSN 1923-9335 (Print)
Quarterly Publication
Volume 6 Issue 3 pp. 213-224 , 2016

A QFD-based decision making model for computer-aided design software selection Pages 213-224 Right click to download the paper Download PDF

Authors: Kanika Prasad, Shankar Chakraborty

DOI: 10.5267/j.msl.2016.1.006

Keywords: CAD software, Decision making, QFD technique, Selection

Abstract: With the progress in technology and innovation in product development, the contribution of computer- aided design (CAD) software in the design and manufacture of parts/products is growing on significantly. Selection of an appropriate CAD software is not a trifling task as it involves analyzing the appositeness of the available software packages to the unique requirements of the organization. Existence of a large number of CAD software vendors, presence of discordance among different hardware and software systems, and dearth of technical knowledge and experience of the decision makers further complicate the selection procedure. Moreover, there are very few published research papers related to CAD software selection, and majority of them have either employed criteria weights computed utilizing subjective judgements of the end users or floundered to incorporate the voice of customers in the decision making process. Quality function deployment (QFD) is a well-known technique for determining the relative importance of customers’ defined criteria for selection of any product or service. Therefore, this paper deals with design and development of a QFD-based decision making model in Visual BASIC 6.0 for selection of CAD software for manufacturing organizations. In order to demonstrate the applicability and potentiality of the developed model in the form of a software prototype, two illustrative examples are also provided.

How to cite this paper
Prasad, K & Chakraborty, S. (2016). A QFD-based decision making model for computer-aided design software selection.Management Science Letters , 6(3), 213-224.

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Journal: Management Science Letters | Year: 2016 | Volume: 6 | Issue: 3 | Views: 3473 | Reviews: 0

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