* Corresponding author. E-mail address: obayinclox@gmail.com (O. Olabanji) © 2020 by the authors; licensee Growing Science, Canada. doi: 10.5267/j.dsl.2019.9.001 Decision Science Letters 9 (2020) 21–36 Contents lists available at GrowingScience Decision Science Letters homepage: www.GrowingScience.com/dsl Pugh matrix and aggregated by extent analysis using trapezoidal fuzzy number for assessing conceptual designs Olayinka Olabanji a* and Khumbulani Mpofu a a Tshwane University of Technology Pretoria West South Africa, South Africa C H R O N I C L E A B S T R A C T Article history: Received May 7, 2019 Received in revised format: August 25, 2019 Accepted August 25, 2019 Available online August 25, 2019 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 multi- criteria 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. . by the authors; licensee Growing Science, Canada 20 20 © Keywords: Conceptual design Multicriteria Decision-making Fuzzified Pugh Matrix Synthetic Extent Evaluation Trapezoidal fuzzy number 1. Introduction Decision making in engineering design towards selection of optimal design of a product or equipment still remains a major concern for manufacturers because they are usually interested in versatile designs that can be easily fabricated and gain market acceptance with a prolonged design life cycle before phasing out (Renzi et al., 2017; Olabanji, 2018). However, these designs cannot be totally achieved from the desk of conceptual designer alone but rather from collaboration with design experts’ and decision-making team on conceptual design. An excellent strategy to achieve optimal conceptual design is usually to identify the design requirements from the users or market demand and also from the manufacturing point of view (Sa'Ed & Al-Harris, 2014). The identified requirements are matched with design features, and various sub-features that can be used to characterize the design as described by the decision-making process in engineering design (Fig. 1). In actual fact, having an all- encompassing design that satisfies all design requirements or features is a goal that seems not achievable because of the dynamic nature of the market that is swamped with diverse design due to customers’ requirements (Olabanji & Mpofu, 2014; Renzi et al., 2015; Toh & Miller, 2015). Given