Optimizing energy modeling in PBF-LB/M metal additive manufacturing: a detailed analysis of resource and energy demand based on standard tensile test specimen

Abstract

AbstractAdditive manufacturing is an essential tool in modern production processes. Competitive quality and the increasing importance of local manufacturing have allowed companies to maintain their production despite supply chains disrupted by the pandemic. However, the rising awareness of society towards environmental and climate protection, the increasing demand for resource-efficient products, and recent developments in energy costs are leading to a rethink in manufacturing processes. Additive manufacturing offers great potential for resource saving components. This study uses standard tensile test specimens to analyze AM processes regarding energy and material flows. The results show a high dependence of energy demand on process time and are transformed into a data-based energy model. Compared to previous energy models, the accuracy can be significantly improved using model data in combination with specific and system-oriented approaches. In addition to system-related saving potentials, design-related optimization potentials can be identified. Innovative and highly resource-saving components can be designed with a design methodology adapted to the extended degrees of freedom of AM. Further saving and recycling potentials can be identified along the material flows. A long-term goal is optimizing and predicting of resource demand in additive manufacturing with a view to the entire product lifecycle.