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This study aims to propose a facilitating methodology for the application of Fuzzy FMEA (Failure Mode and Effect Analysis), comparing the traditional approach with fuzzy variations, supported by a case application in the aeronautical sector.

Based on experts' opinions in risk analysis within the aeronautical sector, rules governing the relationship between severity, occurrence, detection and risk factor were defined. This served as input for developing a fuzzyfied FMEA tool using the Matlab Fuzzy Logic Toolbox. The tool was applied to the sealing process in a company within the aeronautical sector, using triangular and trapezoidal membership functions, and the results were compared with the traditional FMEA approach.

The results of the comparative application of traditional FMEA and fuzzyfied FMEA using triangular and trapezoidal functions have yielded valuable insights into risk analysis. The findings indicated that fuzzyfied FMEA maintained coherence with the traditional analysis in identifying higher-risk effects, aligning with the prioritization of critical failure modes. Additionally, fuzzyfied FMEA allowed for a more refined prioritization by accounting for variations in each variable through fuzzy rules, thereby improving the accuracy of risk analysis and providing a more realistic representation of potential hazards. The application of the developed fuzzyfied FMEA approach showed promise in enhancing risk assessment in the aeronautical sector by considering uncertainties and offering a more detailed and context-specific analysis compared to conventional FMEA.

This study emphasizes the potential of fuzzyfied FMEA in enhancing risk assessment by accurately identifying critical failure modes and providing a more realistic representation of potential hazards. The application case reveals that the proposed tool can be integrated with expert knowledge to improve decision-making processes and risk mitigation strategies within the aeronautical industry. Due to its straightforward approach, this facilitating methodology could also prove beneficial in other industrial sectors.

This paper presents the development and application of a facilitating methodology for implementing Fuzzy FMEA, comparing it with the traditional approach and incorporating variations using triangular and trapezoidal functions. This proposed methodology uses the Toolbox Fuzzy Logic of Matlab to create a fuzzyfied FMEA tool, enabling a more nuanced and context-specific risk analysis by considering uncertainties.

Innovation enables growth and helps address social challenges. This research aims to identify evidence that can characterize an innovative university based on its university management. Thus, the authors define the following research problem: How to measure innovation in a Higher Education Institution (HEI) that intends to be innovative based on its university management?

To this end, the authors conducted a literature review, with a qualitative approach, as well as a case study with data collection through the documental analysis of research that was carried out with the community, namely: Undergraduate Students Profile survey, Reputation of the Institution and Innovation Octagon.

The authors noticed that the results presented by Innovation Octagon show an increase in most indexes, mainly Processes and People, followed by Leadership, Strategy, Relationships and Funding. However, there was a reduction in Structure and Culture.

The results point to the relevance of measuring innovation in the institution, mainly through the use of the Innovation Octagon. The longitudinal measurement of innovation in the institution enables the management of the HEI to constantly progress and develop in favor of the society’s demands for the training of competent professionals for their future professional reality.