Additive Manufacturing Adaptiveness Analysis Using Fuzzy Bayesian Network

Additive manufacturing (AM) is a revolutionary manufacturing technology that can produce products in a layer by layer manner. Because of its significant merits in complex geometry and fast fabrication, AM has received worldwide attentions from both industries and academia. Although extensive studies have been conducted on the aspects of process design, prototyping, quality control and reliability, the study of adopting AM in the application is still not fully investigated, which motives this study. In order to close this gap, this study proposes a fuzzy Bayesian Network based approach to discover the applicability of AM. Twelve features of AM applicability obtained from existing literature have been considered in the analysis; fuzzy linguistic description was used to capture the users’ perception; fuzzy Bayesian Network based causation model was developed to study the AM’s adaptiveness. The jet engine blade case study was applied to demonstrate the applicability of the proposed approach. The results showed that fuzzy Bayesian Network based causation approach is able to provide the robust and reliable results of applicability analysis and could also be extended to other risk assessment related design decision making process.