A Risk Assessment Model for Supply Chain Using a Hybrid Fault Tree Analysis and Analytic Hierarchy Process

The development of Supply Chain Risk Management (SCRM) models needs to be enhanced to reduce subjectivity in determining weights and parameters, address the need for extensive data, and minimize computational complexity. This research aims to develop an SCRM model using the Fault Tree Analysis (FTA) and Analytic Hierarchy Process (AHP) methods, implemented as an algorithm in small to medium-sized metal manufacturing enterprises in Indonesia. The research proceeded through two main stages: risk identification and risk assessment. Based on the literature review and expert group discussions, eleven relevant supply chain risks were identified. These risks were then classified into three categories: supply risks (S), manufacturing risks (M), and distribution risks (D). Implementing the model in the manufacturing company revealed that errors in product handling during the production process (M<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">11</inf>) had the highest risk value. This assessment was based on predetermined probability and impact scores. Such critical risks require immediate mitigation measures. Based on these findings, the FTA and AHP model, in its algorithmic form, has proven effective as a risk assessment technique and can be replicated by practitioners in other manufacturing industries.