Tool path pattern and feed direction selection in robotic milling for increased chatter-free material removal rate

Robotic milling becomes increasingly relevant to large-scale part manufacturing industries thanks to its cost-effective and portable manufacturing concept compared to large-scale CNC machine tools. Integration of milling processes with industrial robots is proposed to be well aligned with the aims and objective of the recent fourth industrial revolution. However, the industrial robots introduce position-dependent and asymmetrical dynamic flexibility, which may reflect to the tool tip dynamics under several conditions. Under such circumstances, the stability limits become dependent on the machining location and the feed direction. In this respect, selection of machining tool path patterns is crucial for increased chatter-free material removal rates (MRR). This paper proposes an approach to evaluate and select tool path patterns, offered by the existing CAM packages, for increased chatter-free MRR. The machining area is divided into number of machining locations. The optimal feed direction is decided based on the absolute stability at each region considering the asymmetrical and position-dependent tool tip dynamics. Then, the alternative tool path patterns are evaluated and the corresponding optimum feed direction is decided for increased chatter-free material removal. The application of the proposed approach is demonstrated through simulations and representative experiments

Processing Parameter Effects on Residual Stress and Mechanical Properties of Selective Laser Melted Ti6Al4V

Selective laser melting (SLM) process is characterized by large temperature gradients resulting in high levels of residual stress within the additively manufactured metallic structure. SLM-processed Ti6Al4V yields a martensitic microstructure due to the rapid solidification and results in a ductility generally lower than a hot working equivalent. Post-process heat treatments can be applied to SLM components to remove in-built residual stress and improve ductility. Residual stress buildup and the mechanical properties of SLM parts can be controlled by varying the SLM process parameters. This investigation studies the effect of layer thickness on residual stress and mechanical properties of SLM Ti6Al4V parts. This is the first-of-its kind study on the effect of varying power and exposure in conjunction with keeping the energy density constant on residual stress and mechanical properties of SLM Ti6Al4V components. It was found that decreasing power and increasing exposure for the same energy density lowered the residual stress and improved the % elongation of SLM Ti6Al4V parts. Increasing layer thickness resulted in lowering the residual stress at the detriment of mechanical properties. The study is based on detailed experimental analysis along with finite element simulation of the process using ABAQUS to understand the underlying physics of the process

Providing and Adapting Information Assistance for Smart Assembly Stations

Information assistance helps in many application domains to structure, guide and control human work processes. However, it lacks a formalisation and automated processing of background knowledge which vice versa is required to provide ad-hoc assistance. In this paper, we describe our conceptual and technical work to provide information assistance for smart assembly stations. Our contribution comprises a conceptual architecture which was implemented in an industrial prototype, the Plant@Hand smart assembly trolley. We describe three major aspects of our approach, the recognition of assembly tasks based on probabilistic models, decision making using a cognitive architecture, and strategies for dealing with sensor-based and knowledge-based errors. Finally, we present the industrial prototype setup