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Integrated Kinematic Machining Error Compensation for Impeller Rough Tool Paths Programming in a Step-Nc Format Using Neural Network Approach Prediction

Citation:

H. Ameddah, “Integrated Kinematic Machining Error Compensation for Impeller Rough Tool Paths Programming in a Step-Nc Format Using Neural Network Approach Prediction,” in Artificial Neural Network Applications in Business and Engineering, vol. 7, 2021, pp. 144-170.
Integrated Kinematic Machining Error Compensation for Impeller Rough Tool Paths Programming in a Step-Nc Format Using Neural Network Approach Prediction

Abstract:

The most important components used in aerospace, ships, and automobiles are designed with free form surfaces. An impeller is one of the most important components that are difficult to machine because of its twisted blades. This research book is based on the premise that a STEP-NC program can document “generic” manufacturing information for an impeller. This way, a STEP-NC program can be made machine-independent and has an advantage over the conventional G-code-based NC program that is always generated for a specific CNC machine. Rough machining is recognized as the most crucial procedure influencing machining efficiency and is critical for the finishing process. The research work reported in this chapter focuses on introduces a fully STEP-compliant CNC by putting forward an interpolation algorithm for non uniform rational basic spline (NURBS) curve system for rough milling tool paths with an aim to solve the problems of kinematic errors solutions in five axis machine by neural network implementation.

See also: Ouvrages, Equipe 5
Last updated on 09/22/2022