Soft sensor technology for the process-integrated influence of the structural fatigue strength by turning of aluminium

• Applicants: Professor Dr.-Ing. Thomas Lampke; Professor Dr.-Ing. Andreas Schubert
• Subject Area: Metal-Cutting and Abrasive Manufacturing Engineering ; Mechanical Properties of Metallic Materials and their Microstructural Origins
• Term: since 2018
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 401805994

The rising need for resource efficiency and sustainability can be fulfilled by using high-strength aluminum alloys. In particular, when considering parts under dynamic load, the presence of compressive residual stresses and low roughness values is of great importance. In the first funding phase of the SPP 2086, a setup for the in-process measurement of temperatures and tool wear based on a tool–workpiece thermocouple and measurements of the process forces was established. Due to the high time resolution as well as the high accuracy, a real-time detection of local disturbances of the surface state is possible. The measured signals were applied for the modelling of the targeted variables. Based on this, the temperature and forces can be correlated with the process parameters as well as the wear state. Other relevant quantities, such as residual stresses, which cannot be measured in process, can be calculated as well. In-depth investigations of the relationships between process parameters, in-process data, and the surface properties allowed for the establishment of analytic equations for the soft sensor. In addition, a model that allows for the calculation of grain sizes in homogeneous samples was derived for the first time.The project’s aim during the second funding phase is the validation of the robustness of those model equations with regards to the influenceable process conditions (e.g. cooling lubrication) and hidden factors like tool wear during turning of the aluminium alloy EN AW-2017. The soft-sensor models will be carried over to another high-strength aluminium alloy (EN AW-7075) and face turning. Metal-cutting simulations on the micro- and macroscale will reveal the complex thermomechanical and thermoelectrical interactions in the contact zone of the tool and the workpiece. The related findings will allow for adaptations of the soft-sensor models, which provide the basis for an in-process control of the surface layer properties of the machined part, the development of control strategies and algorithms, and their implementation and validation in a lathe. This in-process control can be used to detect process disturbances, estimate their impact on the surface state, and adjust the process parameters of feed and cutting speed accordingly. Thus, within a predefined tolerance range, the surface layer properties can be controlled across the surface of the machined part as well as across different batches of parts, which ensures equal operating characteristics.

• DFG Programme: Priority Programmes
• Subproject of: SPP 2086: Surface Conditioning in Machining Processes