SOMMACT Self Optimising Measuring Machine Tools
The objective of SOMMACT (EU NMP FP7 - SMALL 2009 - 2011) is promoting the development and validation of innovative production hardware and control system founded on understanding, evaluating and controlling production system performances of small and single batch production of particularly for large, heavy and complex work pieces.
SOMMACT Self Optimising Measuring Machine Tools


SOMMACT approach is based on detection (in-process embedded traceable measurement) and compensation (adaptive control and self-learning) of geometrical effects of varying external and internal quantities, such as temperature gradients and work piece mass. Knowledge accumulated by the SOMMACT approach is available for a higher level of production system management, supporting self-optimization 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 work piece data with environmental and load conditions, and adapting machining accordingly
3. A self-learning model of the system performance, accumulating knowledge on the machine behavior, based on calibration and real-time measurement data, and on their relationship with work piece characteristics (e.g. mass) and with the environment (e.g. temperature)

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 Coordinate Measuring Machine (CMM). This (i) avoids or reduces QC-production loops, (ii) provides work piece traceable measurement results, and (iii) inputs valuable data into the self-learning