Fuzzified synthetic extent weighted average for appraisal of design concepts

Abstract

Decision-making models such as Analytical Hierarchy Process (AHP), Weighted Decision Matrix (WDM), Pugh Matrix and the likes have been able to assist in the decision process considering the objectives of each evaluation criteria in the alternatives. However, these models need to consider the qualitative and subjective nature of the design features. In order to reduce the unbalanced scale of judgment and the uncertainty associated with the crisp information in the decision process, fuzzified and hybridized models are necessary. Existing hybridized decision models applied for machine concept selection deploy several design features and sub-features at the conceptual product design, which thus make the decision making process to be tedious. In light of this, this article presents a hybridized decision-making model, which harness the comparative strength and computational integrity of fuzzy pairwise comparison matrix and fuzzy weighted average, to numerically analyse a reasonable amount of machine design features, thereby making decision making process less tedious. Design for reconfigurability and functionality which are peculiar to reconfigurable machines was introduced using a Reconfigurable Assembly Fixture (RAF) as a case study while other design features related to design concept evaluation were grouped under design for X. The result of the hybridized model shows that, concept three is the optimal design from four sets of designs. This is compared to previous publication using the RAF design concepts with different design features and sub-features. The comparison indicates that there is a close range in the final values of the designs due to the inclusion of several sub-features in the decision process which were not used in the previous study.