Integrating FRAM and fuzzy logic for the analysis of critical functions and human reliability in loading operations in underground mining

Abstract

This study applied both the Functional Resonance Analysis Method (FRAM) and Fuzzy Cognitive Reliability and Error Analysis Method (CREAM) to identify and analyze critical functions involved in loading operations at an underground mine located in Minas Gerais, Brazil. Data collection was conducted through direct observations of operational tasks to capture performance variability and assess the impact of environmental conditions on operator health and safety. The FRAM analysis mapped interactions between operators and equipment, emphasizing the critical role of ergonomic practices in preventing injuries and maintaining operational productivity. In parallel, the Fuzzy CREAM method quantified the probability of human error under various performance conditions, revealing a high likelihood of error (7.74) under conditions of high workload, fatigue, and low organizational support. This result highlights how human performance variability directly affects operational risk and underscores the importance of ergonomic interventions, such as monitoring operator health and adjusting workloads, to enhance safety and efficiency. The study's main limitation lies in its focus on a specific set of functions, suggesting the need for future research to include a broader range of dynamic operational and environmental variables.