Decision support system for front-end product development

• Main Author: Zhai, Lianyin
• Other Authors: Khoo Li Pheng
• Format: Theses and Dissertations
• Language: English
• Published: 2010
• Subjects: DRNTU::Engineering::Manufacturing::Production management
• Online Access: https://hdl.handle.net/10356/38583
• Institution: Nanyang Technological University

In the highly competitive global market, manufacturers are facing ever increasing challenges in improving customer satisfaction and perceptions of their products while reducing product development time and cost. In such a context, efficient analysis of various design information and effective decision-making play a critical role in tackling such challenges and determining the success of a product development process. However, decision-making in product development is never an easy task due to the complexity of design problems, ambiguity of design information, subjectivity in judgments and contradiction of objectives. In order to address the above mentioned issues in a product design decision-making process, during the front-end product development process in particular, this work establishes a prototype decision support system composed of a potpourri of decision support tools for product planning and design concept evaluation. A design knowledge representation platform to handle various uncertainties inherent in the design information is first proposed. Two novel concepts known as rough number and rough boundary interval which form the backbone of this work are then derived based on the basic notions of rough set theory and interval mathematics. Subsequently, the proposed new concepts are embedded into Quality Function Deployment (QFD) analysis and a rough number enabled QFD decision support tool is realized to translate customer needs into product design requirements. To further improve customer satisfaction, the affective satisfaction aspect in particular, a dominance-based rough set approach to affective design decision support tool has been developed to uncover latent affective design rules from uncertain and nonlinear design information. On the other hand, in order to facilitate decision-making in the design concept selection process, a rough number enabled grey relation analysis decision support tool has been proposed and realized to deal with multi-objective design concept evaluation. Finally, an integrated prototype decision support system composed of the aforementioned three decision support tools has been implemented and demonstrated using a case study. The results of the case study have shown that the decision support system developed is able to facilitate decision-making activities in the front-end product development process by handling the uncertainty, nonlinearity, subjectivity and contradictive objectives in a systematic and effective way, and provide more insights into the analyzed results, which will benefit a product development process in many aspects including improved product quality, more satisfied customers, and reduced product development cost and time.