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SOMMACT develops and validates an innovative production hardware and control system founded on understanding, evaluating and controlling production system performances. This approach is based on detection (in-process traceable measurement embedded capabilities) and compensation (adaptive control and self-learning capabilities) of geometrical effects of varying external and internal quantities, such as temperature gradients and workpiece mass. Knowledge accumulated by SOMMACT approach is available for the higher level of a production system management, supporting self-optimisation and decision making, including the implementation of predictive/virtual metrology methods. The SOMMACT vision is based on three pillars:
1. A new metrological concept to enhance the measuring capability of machine tools, to monitor the machine geometrical deformation reliably and to inspect machined part characteristics traceably;
2. Enhanced sensor systems, measuring the 6 degrees of freedom of each machine component, and a control system integrating machine and workpiece data with environmental and load conditions, and adapting machining accordingly;
3. A self-learning model of the system performance, accumulating knowledge on the machine performance, based on calibration and real-time measurement data, and on their relationship with workpiece characteristics and the environment.
The advantages are an improved product quality at competitive costs, and a prediction capability of the system performances based on a increasingly reliable model. The SOMMACT units can either stand alone, or be integrated into production systems as basic building blocks, enabling flexibility and easy reconfiguration under contingent conditions. Furthermore, the MT measuring capabilities are enhanced to the point that it can be used as a CMM. This (i) avoids QC production loops, (ii) provides workpiece traceable measurement results, and (iii) inputs valuable data into the self learning core.

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EU contribution
€ 970 088,00
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Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
Total cost
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Participants (11)