Final Report Summary - HYMM (Advanced Hybrid Mechatronic Materials for ultra precise and high performance machining systems design)
Research was focused on new materials for macroscale applications in machine tools area to reach a full and deep integration between structural and mechatronic parts of the machines in order to get an 'unicum' solution able to achieve all the required performances.
Therefore, the primary goal was to achieve cost-effective structural solutions consisting of a new class of 'hybrid mechatronic material' based on smart and multifunctional composite materials and capable of performing a wide set of multiple functions ranging from high and adaptable damping and stiffness characteristics to more demanded new requirements (such as structural and measuring / active-control function), in order to achieve extremely high dynamic / thermal stability required in extremely fast and high precision machining.
Among the many achievements, four which stand out include:
-development of integrated mechatronic simulation techniques to evaluate performances of above mentioned smart concept solutions (to be used as selection and driving criteria of proposed solutions);
- development of new Hw&Sw architecture (low-cost) for smart control of mechatronic structures (smart platform) and algorithms for real-time compensation of thermal errors based on FBGs;
- concept study, analysis and fabrication of cellular periodic materials (corrugated core) and CFRP to design the selected structure (Ram) of Fidia machine: weight reduction of 50 % and damping increasing have been achieved;
- design, mnfg and validation of final HyMM demonstrator.
The HYMM demonstrator consists of an innovative smart / adaptive part prototype (of a milling machine) based on integration of FBG optical fibers in a CFRP composite matrix, for real-time thermo-structural deformation measuring and compensation.
As part of the final results a novel smart structure (HYMM demonstrator) of a machine tool which integrates optical FBG displacement sensors has been designed and manufactured for testing. The selected part is a ram (Z-axis of a HSC milling machines), made of CFRP material.
Secondly , the model for tool tip drift prediction based on multiple regression techniques has been implemented. This prediction model correlates the real-time FBG sensor measurements with the actual displacement at tool tip due to random load conditions (static and thermal).
Therefore, the primary goal was to achieve cost-effective structural solutions consisting of a new class of 'hybrid mechatronic material' based on smart and multifunctional composite materials and capable of performing a wide set of multiple functions ranging from high and adaptable damping and stiffness characteristics to more demanded new requirements (such as structural and measuring / active-control function), in order to achieve extremely high dynamic / thermal stability required in extremely fast and high precision machining.
Among the many achievements, four which stand out include:
-development of integrated mechatronic simulation techniques to evaluate performances of above mentioned smart concept solutions (to be used as selection and driving criteria of proposed solutions);
- development of new Hw&Sw architecture (low-cost) for smart control of mechatronic structures (smart platform) and algorithms for real-time compensation of thermal errors based on FBGs;
- concept study, analysis and fabrication of cellular periodic materials (corrugated core) and CFRP to design the selected structure (Ram) of Fidia machine: weight reduction of 50 % and damping increasing have been achieved;
- design, mnfg and validation of final HyMM demonstrator.
The HYMM demonstrator consists of an innovative smart / adaptive part prototype (of a milling machine) based on integration of FBG optical fibers in a CFRP composite matrix, for real-time thermo-structural deformation measuring and compensation.
As part of the final results a novel smart structure (HYMM demonstrator) of a machine tool which integrates optical FBG displacement sensors has been designed and manufactured for testing. The selected part is a ram (Z-axis of a HSC milling machines), made of CFRP material.
Secondly , the model for tool tip drift prediction based on multiple regression techniques has been implemented. This prediction model correlates the real-time FBG sensor measurements with the actual displacement at tool tip due to random load conditions (static and thermal).
