Towards integration of hybrid models for optimized machining performance in intelligent manufacturing systems

This paper discusses integration issues involved in comprehensive evaluation of optimized machining performance for intelligent manufacturing systems. Machining performance is evaluated by major measures such as cutting forces/power/torque, tool-wear/tool-life, chip-form/chip breakability, surface roughness/surface integrity and part accuracy. The machining performance is discussed from a systems framework comprising three primary elements that constitute a machining system; the machine tool, cutting tool and work material. Hybrid methodologies, comprising suitable blends of different modeling techniques are emphasized in this paper. These models can be supplemented by sensory data which defines the unique characteristics of a specific machining system. The modeling of machining performance using traditional techniques, hybrid methodologies and sensor-based information is followed by optimization methods to obtain the optimized machining performance for the specific machining system. The presented methodology provides an effective means for developing intelligent, integrated models and optimization modules within modern machine tools to enable instantaneous assessment of machining performance with suitable on-line process and control strategies.