DECISION SUPPORT MODEL BASED ON AHP-GAUSSIAN AND BOW-TIE FOR MITIGATING FAILURES IN SUPPLY CHAIN PROJECTS

The increase in industrial productivity depends on the continuous improvement of internal processes. In this context, efficient project management plays a key role in reducing costs and preventing operational bottlenecks. This article was developed in a Brazilian energy company located in the southeast region and aims to support decision-making in the definition of actions to mitigate failure risks and increase operational productivity. The methodology adopted has an applied, exploratory and quantitative approach, integrating the FMEA, AHP-Gaussian, Heat Map and Bow-tie methods for risk analysis. In the identification phase, five main risks were mapped by stakeholders. Through the Failure Modes Analysis and Effects  (FMEA) method, it was identified that the risk of low adherence and engagement of the areas involved obtained the highest criticality with a risk priority number (NPR) of 630, followed by the risk of transition and outdated systems with an NPR of 480. In parallel, the Gaussian Analytic Hierarchy Process (AHP-Gaussian ) method was applied to classify the criteria of occurrence, detection, and severity of the risk, reducing the cognitive effort in decision making. The statistical ranking of the AHP-Gaussian confirmed that the risk of low adherence and engagement as the most critical risk. Finally, the Heat Map Matrix visually validated that this same risk had a high impact and a high probability of occurrence. Due to its criticality, the risk of low adherence and engagement of the areas involved was defined as the key problem in the analysis of the Bow-tie method