A new model to design a product under redundancy allocation problem and MCDM

A critical issue in product design is ensuring high system reliability while meeting significant criteria. Therefore, considering key factors is of vital importance in product design. Since product design involves multiple criteria, it is important to use multi-criteria decision-making (MCDM) techniques to make informed decisions. MCDM enables designers to select the best design for products. Additionally, product reliability must be considered a design factor in all industries. This paper utilizes the redundancy allocation problem (RAP) to optimize the system’s reliability and proposes a new model for improving product design. This approach applies the Best Worst Method to rank criteria and the Technique for Order of Preference by Similarity to Ideal Solution to rank the components of the product. The weights of the components are then applied as inputs to the proposed model. The objectives of this model are to maximize reliability using RAP and to maximize the weight value of components by considering their priorities. The goal is to determine the optimal number of components in each subsystem. Since RAP is an NP-hard class of optimization problem with no efficient classical algorithm to solve it in polynomial time, a genetic algorithm is used to solve the formulated problem. This study employs products from an aircraft parts design company as an empirical case. The results verify that the designed model significantly improves product design.