Controlling non-conventional machining
Removing material from a work piece using high-energy fluid jets is a fast-emerging non-conventional machining technology. Its applications range from machining difficult-to-cut materials to ultra-precision polishing of optical lenses. However, until now, this machining technique was still at the 'craftsmanship' level because of the complexity of the procedure. Its use to make freeform parts from advanced materials for high-value added products was limited by lack of control strategies. The 'Self-learning control system for freeform milling with high energy fluid jets' (CONFORM-JET) project solved this important problem. CONFORM-JET developed and demonstrated a novel control system for high-energy jet milling to produce multi-gradient surfaces. Such freeform surfaces are widely used in computer-aided design systems to define the surfaces of machined parts. Scientists integrated models of high-energy fluid jets and other process parameters into the multi-sensors monitoring the solutions being applied. This enabled the project team to predict and control the geometry of the abraded footprint. This combination was then used to develop a radically new control strategy for high-energy jet milling that boasts novel capabilities. They demonstrated for the first time a self-learning control system for high-energy fluid jet processing to generate freeform parts. When the system encounters a new scenario, updated models are used by the model predictive controller. Self-adaptive process control uses sensory signals to respond to process variations based on training from data in the database. The technology reduced required machine supervision by nearly 80 % and development times by around 20 %, which translates to important time and cost benefits. Successful CONFORM-JET outcomes extend the benefits of the process to production of advanced freeform parts from hard-to-cut materials for the aerospace, medical and optical communities. Capabilities far exceed those of foreign competitors, which should boost productivity, growth and jobs across Europe.
Keywords
Machining, control system, fluid jets, freeform, self-learning, freeform milling, jet milling, multi-sensors
