Pugh matrix and aggregated by extent analysis using trapezoidal fuzzy number for assessing conceptual designs

Abstract

Deciding conceptual stage of engineering design to identify an optimal design concept from a set of alternatives is a task of great interest for manufacturers because it has an impact on profitability of the manufacturing firms in terms of extending product demand life cycle and gaining more market share. To achieve this task, design concepts encompassing all required attributes are developed and the decision is made on the optimal design concept. This article proposes the modeling of decision making in the conceptual design stage of a product as a multicriteria decision making analysis. The proposition is based on the fact that the design concepts can be decided based on considering the available design features and various sub-features under each design feature. Pairwise comparison matrix of fuzzy analytic hierarchy process is applied to determine the weights for all design features and their sub-features depending on the importance to the design features to the optimal design and contributions of the sub-features to the performance of the main design features. Fuzzified Pugh matrices are developed for assessing the availability of the sub-features in the design concept. The cumulative from the Pugh matrices produced a pairwise comparison matrix for the design features from which the design concepts are ranked using a minimum degree of possibility. The result obtained show that the decision process did not arbitrarily apportion weights to the design concepts because of the moderate differences in the final weights. .

Design concept evaluation technique via functional link matrix and fuzzy VIKOR based on left and right scores

“…Contrary to this approach, determination of weights of design features have been achieved through Fuzzified Pairwise Comparison Matrix (FPCM). This usually occurs whenever the fuzzy AHP approached is applied (Olabanji & Mpofu, 2020b;Renzi et al, 2015) or when it is hybridized with other MCDM models (Olabanji & Mpofu, 2020c). The FPCM are solved by determining the Fuzzy Synthetic Extent values of the design features (Güngör et al, 2011).…”

“…In view of this, design engineers need to undergo a design concept evaluation process to select the optimal design from available alternative designs (Olabanji, 2018;Renzi & Leali, 2016). Evaluation of alternative design concepts is an important task in the design process because it provides insight to prediction of design performance aside assisting in the identification of optimal design (Olabanji & Mpofu, 2020b;Song et al, 2013). Hence, there is a need to evaluate the design solutions because at early design phase the manufacturers are interested in producing a product with optimal performance before fabrication.…”

“…These sub features describe the relative performance and importance of the design features (Olabanji & Mpofu, 2019;Renzi et al, 2017). Analyzing the design features into sub features will also assist in establishing a decision matrix for the design concepts because it will aid the determination of availability of the design features present in the design concepts (Olabanji & Mpofu, 2020b;Yeo et al, 2004). In practice, weights of design features are usually obtained by evaluation of design requirements from end user's needs.…”

“…The evaluation is usually done by decision makers and design experts in order to ensure that all the features are appropriately evaluated following the design requirements. There still exists a trace of bias judgement in apportioning weights to the design features because the decision makers tend to overrate one design requirement than others (Olabanji, 2018;Olabanji & Mpofu, 2020b). Efforts made to eliminate bias judgement in apportioning of weights is the use of more decision makers and design teams (Tiwari et al, 2016).…”

Design Sustainability of Reconfigurable Machines

“…The centroids of the orthocentres (C 1 , C 2 , C 3 ) of the membership function are obtainable from ( 12), ( 13) and ( 14), as presented in Figure 4 [25]. The left (L S ) and right (R S ) scores of these centroids is determinable from the centroids.…”