Abstract: A method and a system for controlling the operation of a CNC machine for machining a workpiece. In a learning stage, the workpiece is machined without adaptive control under regular cutting conditions, to learn power and vibration patterns of the workpiece for different tools for building power consumption and surface roughness models for each cutting operation. Based on the models and a predefined optimization strategy, objective function values and constraints to be implemented by an adaptive control function are calculated. In operation stage, the workpiece is machined with the adaptive control function thereby modifying the cutting conditions, such as cutting feed and spindle speed, in real time to achieve the calculated objective function values while maintaining the constraints. After each workpiece the power consumption and surface roughness models objective function values are corrected based on collected data.

Abstract: Briefly, embodiments of the invention provide, for example, devices, systems and methods for accelerated modeling. A method may include, for example, defining a domain-specific language (100) usable in a modeling environment (700) and having a dynamic component and a static component, the dynamic component able to affect a behavior of the static component.

Abstract: Briefly, embodiments of the invention provide, for example, devices, systems and methods for accelerated modeling. A method may include, for example, defining a domain-specific language (100) usable in a modeling environment (700) and having a dynamic component and a static component, the dynamic component able to affect a behavior of the static component.