Adaptive neuro-fuzzy inference system for thrust force prediction in drilling of CFRP laminates

Roshan Mishra1, Divyatman Khare, Inderdeep Singh

Department of Mechanical and Industrial Engineering, Indian Institute of Technology Roorkee, Roorkee, 247667, India

ABSTRACT Machining of Fiber Reinforced Plastics (FRPs) presents unusual conditions and requirements, which are not generally encountered in machining of metals. Drilling is the unavoidable machining process required for facilitating the fastening for assembly operations. A major problem during drilling of FRP composite laminate is the drilling induced damage. The thrust force has been identified as the major cause of damage. The present research is an attempt to develop an adaptive neuro-fuzzy inference system (ANFIS) for predicting the thrust force based on the cutting speed, the feed rate, the drill diameter and the drill point geometry as the input parameters during the drilling of Carbon Fiber Reinforced Plastics (CFRPs). The results of the predictive model have been found to be in good agreement with the test data.


KEYWORDS: ANFIS; CFRP; drilling; predictive model; thrust force

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