Enhancing risk assessment of manufacturing production process integrating failure modes and sequential fuzzy cognitive map

When a risk occurs in a stage of the production process, it can be due to the risks of the previous stages, or it is effective in causing the risks in the later stages. The current paper proposes an intelligent approach based on cause-and-effect relationships to assess and prioritize a manufacturing unit’s risks. Sequential multi-stage fuzzy cognitive maps (MSFCMs) are used for drawing the map of risks. Then, the learning algorithm is implemented for learning the MSFCM and finalizing the risks score. A case study on an auto-parts manufacturing unit is applied to demonstrate the capabilities of the proposed approach.