Self-optimized Metal Cutting ProcessesCopyright: Image: Thilo Vogel
Cutting processes are one of the key technologies used in many industries to manufacture products for the global market. The processes include, inter alia, five axis milling and gun drilling operations which are used in industries with automotive, aeronautical or medical technology. For production in high-wage earning countries like Germany, it is of key importance that these cutting processes be controllable. This becomes increasingly difficult as increasing demand for quality, higher degrees of individualization, and shorter product life cycles require more flexible cutting processes which can be operated safely at their technological limit. Furthermore, the economic and ecological aspects will be more and more in focus. Reasons for this include the increasingly competitive pressure from manufacturers in low-wage earning countries, the global shortage of resources, or legal requirements. The result is in an urgent need to continue the progress of controllability in cutting processes while taking the global scope of action into account.
Practical IssuesCopyright: Cluster of Excellence Integrated Production Technology for High-Wage Countries
Due to the manufacturing task, the cutting process has to meet different demands, which include not only product specific quality aspects, but also economic targets. In order to adjust the cutting process to these respective
requirements, the process is nowadays designed in advance. For this purpose, extensive resources and technological knowledge are required which depend upon the complexity of the manufacturing task. Furthermore, cutting processes have to deal with a multitude of variations and disturbances, which can only be partially considered during the design phase. So that, during production the demanded process stability is not always maintained resulting in a quality below pre-defined tolerances. This may lead to scrap or re-machining operations which creates immense additional costs and has a negative long-term effect on the manufacturer. Nowadays, feedback from process disturbances which affords appropriate countermeasures is mainly dependent upon the experience of the operator. The ability to respond by the manufacturing company is often limited.
ApproachCopyright: Cluster of Excellence Integrated Production Technology for High-Wage Countries
To increase controllability, the idea of self-optimization is therefore transferred to metal cutting processes. For demonstration purposes, monitoring and control strategies are developed for the 5-axis milling process and the gun drilling process. Process stability is ensured by strategies for detecting disturbances, and their subsequent compensation by closed control loops. Furthermore, planning aspects are integrated into the control loops to
achieve an optimum concerning external target values of the production plant. An important requirement is the development of new or adaption of existing technological models that are used as a basis for decision-making in
self-optimization. For the implementation, sensor systems are developed, empirical and simulative investigations performed, process information extracted and transferred to knowledge in machine-readable models. Further tasks
are the cross-linking of single components of the overall system to ensure a consistent data exchange. Concerning
this latter, a special task is the linkage between CAM and physical process monitoring that is established by a position related monitoring and simulation strategy.
Technical ChallengesCopyright: Cluster of Excellence Integrated Production Technology for High-Wage Countries
The challenge of introducing self-optimization to metal cutting processes is caused by the complexity of the processes. The abstraction of process coherences and the reproduction in technical models are probably the most challenging tasks today. For modelling the 5-axis milling process and the gun drilling process, transfer functions
are used and implemented to black box models. The extension by physical descriptions of phenomena and cause- effect relationships transfers the models to the class of grey box models. For the development of suitable models, the interconnection of virtual and real world is necessary. This includes the joining of experimental results and simulations. For example, the position-correlated forces of the 5-axis milling process are measured and connected to engagement conditions of the simulation. By this, first optimizations can be done in the CAM system. On the other hand the information about engagement conditions can be used for the continuous identification of important parameters for the control loop and the more detailed processing of monitoring data. Another task is the development of robust process control strategies. Process control is used to compensate disturbances to ensure a safer process. To achieve this, control strategies have to be implemented that adapt their control behaviour depending upon the actual process state. Furthermore, the developed process models must be integrated into the control concept. Therefore, interfaces have to be established that enable a smooth communication within the control system.