Fuzzy methodology appears to be one of the most promising tools for managing the ambiguity and indetermination that characterize the evaluation of suppliers' contribution to product development. This kind of evaluation, in fact, is particularly complex, given the difficulty in identifying, circumscribing and quantifying the supplier's co-design performance. Moreover, this evaluation is mainly perceptive and strongly influenced by subjective judgements, being linked to the experience and common sense of decision-makers (purchasers, designers, etc). In this paper we present a fuzzy expert system prototype able to manage the evaluation process and to offer a reliable measurement of the contribution of the suppliers in new product development (NPD). The objectives of this study are the following: (a) to develop a vendor rating tool based on fuzzy logic; (b) to refine it using a neural application; and (c) to compare it with an ordinary least squares (OLS) regression, which reproduces the traditional method of evaluation. The evaluation tool was tested in a company where co-design is a critical factor for success and the tool's potentials and limits are pointed out.
Evaluation of supplier contribution to product development: Fuzzy and neuro-fuzzy based approaches
Reprints and Corporate Permissions
Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?
To request a reprint or corporate permissions for this article, please click on the relevant link below:
Academic Permissions
Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?
Obtain permissions instantly via Rightslink by clicking on the button below:
If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.
Related Research Data
Related research
People also read lists articles that other readers of this article have read.
Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.
Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.