Article ID Journal Published Year Pages File Type
10673309 CIRP Annals - Manufacturing Technology 2015 4 Pages PDF
Abstract
Prospectively, the machine should utilize an algorithm that autonomously identifies optimal parameter configurations for new workpieces to realize fast setup procedures. This paper presents a genetic algorithm for a self-learning feeding system that has been validated in comprehensive simulation studies.
Keywords
Related Topics
Physical Sciences and Engineering Engineering Industrial and Manufacturing Engineering
Preview
A genetic algorithm for a self-learning parameterization of an aerodynamic part feeding system for high-speed assembly
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