Current machining technologies and practices have many inefficiencies. Numerous unpredictable machining variables often cause overload and unstable conditions and catastrophic damage to the machine tool system. In addition, this results in frequent disruptions in production that can often be excessive, leading to considerable losses in productivity, capital and energy resources. In an effort to prevent these occurrences, process planners, programmers and operators are forced to adopt a conservative approach and they program for the “worst case” scenarios - resulting in considerable inefficiency in machine tool utilization.
The objective of the project is to develop active, self-optimizing “intelligent” adaptive control systems which will continuously analyse a wide range of monitored parameters of the machining process and automatically adapt the machine operation in real-time to its optimal performance in order to account for continuously varying machining conditions, production disruptions and anomalies, plant performance variations and random changes in production plans. AIMACS will develop reliable techniques for monitoring the most critical machining parameters such as cutting load, vibrations and energy consumption. Based on this information and taking into account the costs for tools machining time, maintenance time, energy, etc. AIMACS will optimise in real time the overall production process based on productivity/cost criteria in order to ensure effective adaptive and sustainable machining
As a plug-and-produce system, AIMACS will be applicable to newly built machines and also for retrofit to the installed base of existing machines in the European manufacturing industry. Since the installed base of machines in Europe is estimated to be more than 1,000,000 machines, the impact of AIMACS on the efficiency, productivity and competitiveness of the European domestic manufacturing industry should be very substantial.
Field of science
- /social sciences/economics and business/economics/production economics/productivity
Call for proposal
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