Experimental Characterization and Multi-Objective Optimization of the Orbital Drilling Process of CFRP

Defects associated with drilling of Carbon Fiber-Reinforced Polymers (CFRPs) are of major economic and safety concerns for aerospace manufacturers. One of the most critical defects associated with drilling of CFRP laminates is delamination of layers which can be avoided by keeping the drilling forces below some threshold levels. Orbital Drilling (OD) is an emerging drilling process that exhibits lower cutting forces and temperatures, easier chip removal, higher produced surface quality, longer tool life, and a high possibility for dry machining. The OD process is featured by cyclic engagement and disengagement between the tool and the workpiece whereby a considerable part of the work done by the tool is directed towards the tangential direction while the work done in the axial direction is reduced. This reduces the risk of delamination at the exit. The objective of this research work is to investigate the effect of the OD process key parameters with respect to the produced hole attributes (surface roughness, delamination, and hole accuracy), as well as the cutting forces and temperatures. All the OD tests were performed under dry conditions using a four-flute 6.35 mm end-mill. The cutting forces were recorded using a 3-component dynamometer Kistler 9255B and cutting temperatures were measured using a FLIR ThermoVision A20M Infrared camera at the holes exit. A full factorial design of the experiment was used whereby the feeds varied from 60 to 360 mm/min and the speeds from 6,000 to 16,000 rpm. The test material used was a quasi-isotropic laminate comprising woven graphite epoxy prepreg. Analysis of the results showed 45% reduction in the axial force component in orbital drilling (OD), compared to conventional drilling. None of the holes produced by the entire set of experiments has experienced any entry or exit delamination. ANOVA was used to identify the significance of the controllable variables on the experimental outputs. To overcome the challenge of optimizing the competing parameters of the hole quality attributes while maximizing the productivity, an algorithm was applied by hybridizing Kriging as a meta-modeling technique with evolutionary multi-objective optimization to optimize the cutting parameters.