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Product Design (PD) currently faces challenges in new product development, since the industry is in a rush to introduce new products into the market, with customers demanding products that are faster, cheaper, and free from failure. In addition, global companies are trying to improve their product design risk assessment process to gain advantages over competitors, using proven tools like Failure Mode and Effect Analysis (FMEA) and mixing risk assessment methods. However, with current risks assessment tools and a combination of other methods, there is the opportunity to improve risk analysis. This document aims to reveal a novel integrated method, where FMEA, Pythagorean Fuzzy Sets (PFS), and Dimensional Analysis (DA) are cohesive in one model. The proposed method provides an effective technique to identify risks and remove uncertainty and vagueness of human intervention during risk assessment using the Failure Mode and Effect Analysis method. A real-life problem was carried out to illustrate the proposed method. Finally, the study was substantiated by using a correlation and sensitivity analysis, demonstrating the presented integrated method’s usefulness in decision-making and problem-solving.

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We present a multi-objective evolutionary algorithm to exploit a medium-sized fuzzy outranking relation to derive a partial order of classes of alternatives (we call it RP 2 -NSGA-II). To measure the performance of RP 2 -NSGA-II, we present an empirical study over a set of simulated multi-criteria ranking problems. The result of this study shows that RP 2 -NSGA-II can effectively exploit a medium-sized fuzzy outranking relation. Finally, we present a real-case study for ranking the municipalities of the state of Guanajuato, Mexico by their levels of marginalization.

Marginalization studies of a population are tools that enable the Mexican government to understand and compare the socio-demographic situation of different regions of the country. The goal is to implement effectively various programs of social or economic development whose aims are to fight against the population’s lag, which has affected the quality of life of Mexican citizens. In this paper, a multi-criteria approach for ranking the municipalities of the states of Mexico by their levels of marginalization is proposed, and the case of Jalisco, Mexico, is presented. The approach uses the ELECTRE III method to construct a medium-sized valued outranking relation and then employs a new multi-objective evolutionary algorithm (MOEA) based on the nondominated sorting genetic algorithm (NSGA) II to exploit the relation to obtain a recommendation. The results of this application can be useful for policymakers, planners, academics, investors, and business leaders. This study also contributes to an important, yet relatively new, body of application-based literature that investigates multi-criteria approaches to decision-making that use fuzzy theory and evolutionary multi-objective optimization methods. A comparison of the ranking obtained with the proposed methodology and the stratification created by the National Population Council of Mexico shows that the methodology presented is consistent and yields reliable results for this problem.

Product Design is getting nowadays new challenges on developing new products, since the industry is in a rush to introduce products into the marketplace, where customers demand products faster, cheaper, and free of failures. In the meantime, global companies are always trying to improve their Product Design process to get advantages over their competitors using proven tools like FEMA and mixing methodologies like Fuzzy theories with FMEA. Even today using all this tools and combination of methodologies there is a gap to address and it is required a robust risk analysis solving current issues in the electronic industry. This document aims to reveal a novel integrated method, where Failure Mode and Effect Analysis, Pythagorean Fuzzy Sets and Dimensional Analysis are cohesive into a model that minimize the uncertainty of the ranking and prioritization over the Failure Mode and Effect Analysis execution, helping to identify risks within an accurate grade over possible failures in the Product Design process. A real practical example is used to show the proposed method, where it is identified a robust methodology integration and solid and results using a sensitivity analysis.