Data-based evaluation of the wire electrical discharge machining process
Companies & Partners
WBA Aachener Werkzeugbau Akademie GmbH, Makino Europe GmbH, WZL of RWTH Aachen University,
Automation requires stable and adaptive processes that no longer require manual intervention. One common manufacturing process that is commonly used in tool and mold making and is becoming increasingly important in the aerospace industry is wire electrical discharge machining. Today, it is not possible to evaluate the productivity and quality of the wire electrical discharge machining process online based on physical variables and other process data.
A suitable model for the given data is determined automatically by systematic data preparation and data reduction using machine learning. With data from variable process conditions, statistical models are trained. In addition, physical models for removal behavior and flushing will be developed for the studies. Merging these models will provide a digital representation of the workpiece to predict and optimize quality. With the help of this comprehensive model, both online process monitoring and data-based optimization of process parameters for a machining technology will be realized. Finally, the functions will be transferred to an industrial app to simplify the automation of the electrical discharge machining process.
Increased capability of the wire electrical discharge machining process