Abstract
Additive Manufacturing (AM), an innovative technology, plays a pivotal role in localising supply chains, with the integration of digital technologies further enhancing production flexibility and system resilience. However, AM increases digitalisation in the supply chain, which brings a range of cybersecurity vulnerabilities. Consequently, a comprehensive risk assessment framework is necessary to assist decision-makers considering AM systems. Prior research has employed Composite Indicators (CIs) for risk evaluation, aggregating sub-indicators to assess risks. However, the approach to determining suitable weights for these sub-indicators presents notable limitations such as limited discriminant power, non-unique outcome, subjective assumption on weight preference. To solve the limitation in determining the weight, this paper introduces a multi-level (three-stage) risk assessment model based on the Multiplicative Non-Parametric Approach. This model provides a thorough evaluation of threats within AM systems, considers both individual and industrial perspectives, and determines the global weights of each sub-indicator. The empirical analysis demonstrates that the proposed multi-level model effectively identifies appropriate weights for the sub-indicators, resulting in outcomes that closely align with the original assessment results. The model's performance improves as the number of analysis stages increases, reaching its peak in the final stage of analysis. ARTICLE HISTORY