In industrial manufacturing, fuzzy logic-based risk assessment methods are increasingly adopted to manage uncertainties of experts knowledge in complex systems. These methods use traditional risk assessment techniques by incorporating human expertise and handling imprecise data. This paper discusses the application of fuzzy logic methods in industrial risk assessment, especially in the manufacturing sector. It highlights how fuzzy systems can help manage uncertainty and improve the accuracy of expert evaluations. A special focus is placed on the fuzzy version of the Failure Mode and Effects Analysis (FMEA) method, which uses linguistic variables and membership functions to better reflect real-world conditions. The paper also presents a practical case study of fuzzy FMEA used in the welding process. The results show that fuzzy logic improves the flexibility and reliability of traditional risk assessment techniques. In the analyzed case, the most critical risks identified were damage to protective clothing (R5), contamination of welding material (R6), and short circuit in welding equipment (R10), which should be addressed with priority in safety planning.