Surface roughness monitoring in cutting force control system
Journal Title: Proceedings in Manufacturing Systems - Year 2015, Vol 10, Issue 2
Abstract
The aim of this contribution is to present a reliable cutting force control system in end milling with the main focus on the integrated surface roughness prediction model. In this control system, cutting force sensor is used to control the milling process by digital adaptation of cutting parameters. The main goal of this paper is to present a new method for surface roughness (Ra) prediction by using measured maximum cutting forces signals and initial cutting parameters. End milling machining process of hardened die steel with carbide end mill was modeled using the adaptive neuro-fuzzy inference system (ANFIS). The purpose of ANFIS model is to predict the effect of machining variables and maximal cutting force on surface roughness during machining. The surface roughness tester is used to observe the actual surface roughness of the machined surface after the machining tests. The comparison between the predicted surface roughness values determined by ANFIS and experimental measurements indicates that the performance of this method turned out to be satisfactory for evaluating Ra, within a 3% mean percentage error and 96% accuracy rate. The developed model is used to monitor milling operations and provide warnings to the operator. The ANFIS model can also stop the machining process for tool change based on a pre-set surface roughness limits.
Authors and Affiliations
U. Zuperl, T. Irgolic, F. Cus
Keywords
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