Application of Grey Relational Analysis to Decision-Making during Product Development

Autor/inn/en	Hsiao, Shih-Wen; Lin, Hsin-Hung; Ko, Ya-Chuan
Titel	Application of Grey Relational Analysis to Decision-Making during Product Development
Quelle	In: EURASIA Journal of Mathematics, Science & Technology Education, 13 (2017) 6, S.2581-2600 (20 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1305-8223
Schlagwörter	Decision Making; Prediction; Design; Production Techniques; Focus Groups; Evaluation Criteria; Case Studies + Suchen Sie Ihr Suchwort? Decision-making; Entscheidungsfindung; Vorhersage; Production engineering; Produktionstechnik; Case study; Fallstudie; Case Study
Abstract	A multi-attribute decision-making (MADM) approach was proposed in this study as a prediction method that differs from the conventional production and design methods for a product. When a client has different dimensional requirements, this approach can quickly provide a company with design decisions for each product. The production factors of a product are usually complex and difficult to predict. A focus group that comprises seven professional product designers was formed in this study to determine those exact assessment criteria based on their practical experiences of pneumatic door closer designs. These criteria include operability, manufacturability, style, creativity, and cost. We recommend using grey-level designs to assess and resolve the product design and production planning problems. A case study on pneumatic door closers was conducted and a weighted value was assigned to each of the assessment criteria. New product series were created for the verification of the proposed design approach. In a grey-level design assessment, the design ideas of clients and designers are represented by grey levels. After that, a grey relational analysis is used to determine those factors that are valued by clients for predicting the priority of each of the design elements for a product series. The proposed approach can assist designers in predicting a product's design quality and recommend the optimal alternative within a product series. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01