A non-linear possibilistic regression approach to model functional relationships in product planning

被引：0
|
作者：
Chen, Yizeng [1 ]
Chen, Li [1 ]
机构：
[1] Department of Precision Mechanical Engineering, School of Mechatronics Engineering and Automation, Shanghai University, China
来源：
International Journal of Advanced Manufacturing Technology | 2006年 / 28卷 / 11-12期
关键词：
Product planning is one of four important processes in new product development (NPD) using quality function deployment (QFD). In order to model the process of product planning; the first problem to be solved is how to incorporate both qualitative and quantitative information regarding relationships between customer requirements and engineering characteristics; as well as among engineering characteristics; into the problem formulation. The inherent fuzziness of functional relationships in product planning makes the use of possibilistic regression justifiable. However; when linear programming in possibilistic regression analysis is used; some coefficients tend to become crisp because of the characteristic of linear programming. To tackle the problem; a non-linear programming based possibilistic regression approach is proposed; by which more diverse spread coefficients can be obtained than from a linear programming approach. An emulsification dynamite packing-machine design is used to illustrate the performance of the proposed approach;
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摘要：
Journal article (JA)
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页码：1175 / 1181
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