Publication: Intelligent toolpath selection via multi-criteria optimization in complex sculptured surface milling
Program
KU-Authors
KU Authors
Co-Authors
Manav, C.
Advisor
Publication Date
Language
English
Type
Journal Title
Journal ISSN
Volume Title
Abstract
A new approach is presented the first time in the literature to generate multi-criteria optimized toolpaths for the complex sculptured surface machining. This is achieved by developing a mathematical solution that consists of the physical relationship between the mean resultant forces, cycle times and scallop heights. These three critical process outputs in machining are conflicting with each other. In other words, there are tradeoffs between cutting force magnitudes, cycle time and scallop height. This triple bounded problem in machining is solved in this article by using the objective weighting based algorithm. The multi-criteria toolpath optimization method introduced here for sculptured surface machining increases the controllability of the process with the specified criteria. The method also allows determining all pareto optimal solutions and all possible weights of each criteria. Moreover, the method eases to observe and analyze the trade-off between each criterion, facilitate the limitation and minimization of each criterion and determine corresponding toolpath for each solution. This solution produces optimized toolpaths according to preset constraints for mean cutting force, cycle time and scallop height. The method is a generalized solution for determining optimized toolpaths based on given constrains in free-form surface machining. In order to validate the multi-criteria toolpath optimization method, experiments at various conditions are performed on free-form machining and an example is presented in this article.
Source:
Journal of Intelligent Manufacturing
Publisher:
Springer
Keywords:
Subject
Computer science, Artificial intelligence, Engineering, Manufacturing engineering