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Directed Energy Deposition (DED) is a highly localized process in which metal powders are added to a laser-induced molten pool. The shape and size of the melt pool ultimately determine the local cooling/solidification rate and, thus, the material's microstructure and properties. To study melt pool shape, in situ X-ray imaging techniques have been used. However, the data afterwards typically are manually analysed, which creates a bottleneck in understanding fundamental phenomena in DED. Here, a promising method to automatically extract melt pool shape and dimensions from in situ X-ray DED melt pool images using templates and Bayesian reasoning is proposed.

Industrial robots, used for milling processes, have to execute highly dynamic and accurate movements. External static and dynamic process forces lead to static deflections and dynamic excitations. In this paper, we present a coupled offline simulation and planning strategy of the machine-process interaction with online adaptation mechanisms for increased system robustness. The process planning, optimization and milling force prediction are executed offline, while the online compensation and adaptation accounts for static deflections and unmodeled disturbances. The benefits of the combined offline and online approach are demonstrated by stabilizing machining processes and accurate deflection compensation with unmodeled changes in spindle speed and feed rate for the machining of aluminum workpieces.

A predictive simulation of the different damping effects in machine tools is required to optimize the dynamic behavior and thus increase their performance and working accuracy. Previously, holistic optimization based on damping was not possible due to non-predictive damping models and the lack of adequate modeling approaches. This paper presents a modeling approach, which allows the efficient simulation of the dynamic behavior. By applying this procedure and suitable damping and friction models, the dynamic behavior of a four-axes machining center was simulated with high accuracy – FRAC values above 95% were achieved.

In industrial applications, scanner systems are utilized for several operations, but do not always meet the desired dynamics. Various controller-based approaches, which concentrate on simple trajectories or changes in operation points, have been presented within the last years; however, these are not sufficient for many production processes. In this paper, adaptive inverse control is utilized to enhance the scanner’s dynamics. The influence of structural dynamics is compensated by taking the behavior of the galvanometers’ mirrors into account. The performance of the new approach is verified by experimental results, reducing the optical error by almost 95% compared to current scanner systems.

Material removal rates of machine tools are mainly limited by chatter, which is caused by the machine’s most flexible structural modes. Active damping of the structural modes requires the identification of a machine dynamics model used in tuning the active controller. This complex process has to consider uncertainties, actuator saturation, and the stability of the controller. This paper presents an automated identification of machine dynamics and auto-tuning of the controller using the same actuator and vibration sensor. The proposed method has been experimentally demonstrated with simple and advanced controllers which led to notable increases in chatter free material removal rates.

At the outer edge of highly stressed CFRP parts, critical stress peaks arise at notches. In fatigue testing of tensile specimens with a centred circular notch, an unpredictable fibre based breakage was observed for specimens manufactured by abrasive waterjet cutting. Using a remote laser cutting process changed the failure mode to well predictable matrix based. The finite element simulation shows that the peak stress on the loaded fibres within the heat affected zone was reduced to a noncritical value based on the elimination of the material’s shear force capacity. Consequently, laser cutting demonstrates significant potential for lightweight construction with CFRP.

By using additive manufacturing processes various powder materials can be melted and geometrically complex parts can be built. There is a need for high energy density to melt a metal powder layer locally. Therefore a laser beam is used to induce the required temperature level. To attain a more homogeneous temperature distribution a heating unit is integrated. To identify the thermal influences a model has been developed and validated by using tungsten carbide. To evaluate the achieved results different quality criteria have been determined. However, both process stability and part quality can be increased by minimizing temperature gradient mechanisms.

Machine tools need to work accurately and highly dynamically to keep up with the requirements of modern machining processes. Besides the technical issues, time to market is too short to build a real prototype in future. This leads to the necessity for a method which enables the forecast of the future machine performance. To predict the machining results exactly, large movements on flexible structures have to be calculated. With the specific integration of FEA and MBS for the domain of machine tools it is possible to predict the dynamic machine behaviour. The simulation system is based on the relative nodal method for large deformation problems. A model of a machine tool with all relevant components was simulated and matched with experiments to demonstrate the approach.

It is difficult to develop PLC software for modern machine tools due to their increasing functionality and the resulting complexity. One approach to managing this is the model-based development and simulation-aided verification of control software. A suitable method for this is described in this paper. It focuses on a method for modeling the control functionality and a simulation system for commissioning the developed programs using a virtual model of the machine.

For full realization of the feasible drive performance on machine tools, the dynamic behaviour of the entire mechatronic system must be analysed and optimized integrally during design of the machine. To permit complete modelling of the machine tool frame structure with integral ball screw feed drive systems by means of the finite element method (FEM) a specific model approach for ball screw drives is presented, which is a prerequisite for the FEM modelling of a complete machine tool based on feed drives of this type. The feed axis of a feed drives test station serves here as an example for demonstration of the modelling of feed drives. The FEM model is integrated into a mechatronic model of the axis control system and the behaviour of the position and speed control loop is simulated.