Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/310952
Title: Investigation of Surface Roughness in Drilling of GFRP CFRP and Tool Life Prediction by Using Artificial Neural Network
Researcher: Veeresh Chandra, M. S
Guide(s): Chikkanna, N.
Keywords: Artificial intelligence
Engineering
Engineering and Technology
Engineering Mechanical
Neural networks (Computer science)
University: Visvesvaraya Technological University, Belagavi
Completed Date: 2018
Abstract: The global carbon fiber / glass fiber market was worth INR 141 Billion in 2016, newlineregistering a compound annual growth rate of 9.1% and is slowly replacing metals in engineering newlineapplications. Drilling of carbon fiber reinforced polymer (CFRP) / glass fiber reinforced polymer newline(GFRP) is challenging because of its anisotropic and heterogeneous properties which makes it newlinedifficult to drill. The objective of the work was to find the effect of process parameters viz. newlinediameter, feed rate and cutting speed on delamination and circularity of the drilled hole. newlineExperimental Investigations using drill tools of steel by predictive modeling and optimization newlinetechniques were done. This work also investigated the effect of drilling parameters on surface newlineroughness, flank wear in drilling of CFRP using tool steel drill. Finally the work focused on newlineanalysing Tsai-Wu failure criteria in drilling of CFRP using finite element approach. newlineThe CFRP /GFRP laminates were prepared using hand lay-up technique with stacking newlinesequence 0and#61616;/90and#61616; of 3.5mm thick, 7 layers each constituting 0.5mm thickness with volume fraction newlineof 0.65. Drilling operation was carried out and measurement of the thrust force and temperature newlinewas done during drilling. Further, the drilled hole diameters and delamination factor were newlinemeasured using stereomicroscope. Measurement of circularity error was carried out using coordinate newlinemeasuring machine and tool wear was measured. Design of experiments using Taguchi newlineL27 array was formulated to understand the influence of process parameters on delamination and newlinecircularity. ANOVA was performed to find out the influencing weightage factor for delamination, newlinecircularity and temperature. Regression analysis was used to develop a mathematical model that newlinegives the contribution of individual parameters on responses. Control charts were plotted to know newlinethe acceptability of the drilled hole.
Pagination: XVI, 140
URI: http://hdl.handle.net/10603/310952
Appears in Departments:Department of Mechanical Engineering



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