Development and validation of an acoustic emission based process monitoring technique for the milling of carbon fibre reinforced plastics

• Applicant: Professor Dr.-Ing. Eckart Uhlmann
• Subject Area: Metal-Cutting and Abrasive Manufacturing Engineering
• Term: from 2019 to 2022
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 420609123

Due to their high specific modulus of elasticity, fibre-reinforced plastics (FRP) are used as a material for lightweight components in automotive and aerospace industries. A special challenge for the economic and process-reliable production of FRP components is the machining by means of cutting processes such as milling. This is due to the abrasive glass or carbon fibres, which inevitably lead to wear on the milling tool in the form of increasing cutting edge rounding. The machining with worn milling tool leads to increasing process forces and unwanted component damages such as layer delaminations, which can make cost-intensive component inspections and costly reworking necessary.The implementation of online detection of tool and component damage during machining therefore has the potential to drastically reduce the manufacturing costs and processing times of FRP components. For this reason, the aim of this research project is the development and evaluation of an acoustic emission based online process monitoring technique for milling of FRP. This provides information on the wear progress of the coated and uncoated tool as well as on unwanted component damage and reduces the need for costly component inspections.Due to the high attenuation of acoustic emission in FRP and material anisotropy, the use of an acoustic emission sensor mounted on the workpiece side is not suitable for robust process monitoring during milling. This problem is to be solved in this research project for the first time by a tool-sided sensor coupling. The reduction of the thus recorded datasets by means of feature extraction and pattern recognition will enable an online process monitoring, which reliably detects both the tool condition and the undesired component damage.

• DFG Programme: Research Grants