A cost model for the economic evaluation of in-situ monitoring tools in metal additive manufacturing

The paper presents a cost model to evaluate the economic impact of defects and process instability in metal Additive Manufacturing (AM). The proposed model formulation adopts the main framework of previous seminal studies and extends it by considering the contribution of scrap fractions and in-situ monitoring performances on process and material costs, including pre- and post-processing operations. Three real industrial case studies (from dental, aerospace, and machinery sectors) were assessed to determine how the model can be used in the real industrial practice to (i) enhance the economic advantages of metal AM technologies by tackling process instability issues, (ii) assess the effectiveness of in-situ monitoring in the development of next generation metal AM systems, and (iii) define the performance specifications of in-situ monitoring solutions that yield sustainable cost savings in specific industrial applications. A further experimentation is presented to validate the cost model with respect to a benchmark reference.