Modeling, Experimental Investigation and Optimization of Machining Parameters in Cnc End Milling of an Aerospace Material: A Novel Approach

Abstract

Machining of aerospace materials is a challenging task, as it involves high strength; huge variety of materials, requirement of complex geometric shapes with very close tolerances. Especially machined components assembled in fighter aircraft structures such as: longerons, spars, central frames, side frames, shear walls, trouser ducts, integral fuel walls and various supporting ribs of the fuselage etc., will be subjected to high level of fatigue loads during maneuvering. In case of these structural components surface finish as well as dimensional accuracy of the fabricated parts plays an important role in their fatigue life and in-turn durability of fighter aircraft. Therefore, it is very important to fabricate a component with good surface finish to enhance the life of each structural detail component and in-turn life of an aircraft. Machining process is the removal of unwanted material from workpiece, so as to obtain an end product of desired size and shape with required surface quality. End milling process is a multipoint, uninterrupted cutting process, in which contact between cutting tool edge and workpiece is not continuous. Underutilization of the high-cost CNC machine tools to its full capacity is the major drawback in the manufacturing domain and it is limiting the efficient usage of machine tools, as it is being continuously run at sub-optimal conditions since many years. At the same time demand for better quality fabricated products has encouraged the metal cutting industry to continuously enhance the quality of machined products through various machining processes. Out of several types of available machining processes, end milling is one of the most fundamental metal removal process occupying the center of manufacturing industries. It is affected by controlled and uncontrolled parameters like: input machining process parameters, ambient conditions, type of coolant being used, tool geometric parameters, tool and workpiece material combination etc. The present research work has been carried out in three phases while machining of BS L168 aluminum alloy using carbide solid end mills under two different kinds of machining environments called constant feed machining (CFM)and progressive feed machining (PFM).In the first phase a new approach of controlling the machining feed rate called progressive feed machining has been adopted through part programming then experimentally studied and analyzedits merits and demerits over the traditional constant feed machining, by mainly focusing on the measurement, prediction and analysis of output performance characteristics such as: average surface roughness (Ra), cutting tool tip temperature (T), material removal rate (MRR), surface topography and chip morphology through end milling experiments on the said aluminum alloy work material. Further, it is investigated, the influence of cutting parameters on above said performance characteristics in PFM over CFM through predictive modelling by response surface methodology (RSM) and Analysis of variance (ANOVA) techniques. Three level variations of cutting process parameters were considered with CFM and PFM machining environments for modelling and optimization purpose by keeping nose radius and rake angle constant at 0.8mm and 160 respectively. Feed rate (f), cutting speed (s) and depth of cut (d) are the cutting parameters considered as significant factors here. Cutting speed(s) varies from 2.09m/sec(2000rpm) to 4.188m/sec(4000rpm), feed rate(f) varies from 0.1mm/rev(200mm/min) to 0.15mm/rev (600mm/min) and depth of cut(d), varies from 0.75mm to 2.25mm. Taguchi’s Design of Experiment (DoE) has been followed to perform the end milling experiments and to analyze machining process parameters. Later, regression mathematical models were developed for the experimental values of surface roughness (Ra), cutting tool tip temperature rise (T) and material removal rate (MRR) using response surface methodology (RSM) technique. The predicted values of performance characteristics are compared against respective experimental results and were found in close agreement. Further, signal to noise (S/N) ratio analysis was carried out using ‘lower-the-better’ quality characteristics for surface roughness and cutting tool tip temperature rise, since these performance characteristics are to be minimized for betterment of the machining process. At the same time ‘higher-the-better’ quality characteristic has been chosen for material removal rate, since higher MRR is always recommended and it is required for quick machining. Later on, ANOVA was applied to further analyze the data in order to check not only the adequacy of developed regression models but also to find the influence of individual input cutting parameters on the output performance responses. Furthermore, correlation plots, model fitness check plots, main effect plots, interaction plots, 3D surface plots and lastly contour plots have been established for all the circumstances of machining conditions with CFM and PFM for further analysis.Detailed comparative study and experimental investigation between proposed PFM and traditional CFM characteristics on work material using end milling process have been established. In the second phase, further experimentation has been carried out according to One Factor at A Time (OFAT) approach. For this experimental study, five level variation of cutting parameters were considered: cutting speed(s) varies from 2.09m/sec (2000rpm) to 6.28m/sec (6000rpm), feed rate (f) varies from 0.1mm/rev (200mm/min) to 0.167mm/rev (1000mm/min) and depth of cut (d) varies from 0.75mm to 3.75mm respectively,in-order to obtain smooth and extended form of two-dimensional plots. Besides that, nose radius (NR) and rake angle are the tool geometric features have been taken into consideration. Therefore, better understanding of the influence of individual cutting parameters on performance characteristics is possible. Tungsten carbide solid end mills with different nose radii of 0.4mm, 0.8mm and 1.2mm with a rake angle of 160 and tool diameter of 20mm have been used for this OFAT experimentation on the above-mentioned CNC milling machining center. Combined effect of variation in nose radius and cutting parameters have been analyzed with the help of established graphs on surface roughness, cutting tool tip temperature and material removal rate. Furthermore, effect of nose radius on surface topography has been carried out by means of optical microscopic study. From the experimental results and established two dimensional plots, it is observed that lower surface roughness and minimum MRR and maximum cutting tool tip temperature were obtained with 1.2mm nose radius. Whereas higher surface roughness, maximum material removal rate and lower cutting tool tip temperature rise were observed with 0.4mm nose radius. An increase in nose radius of end mills from 0.4mm to 1.2mm, resulted in decrease of material removal rate as well as decrease of surface roughness, but an increase in cutting tool tip temperature within the selected range of process parameters was noticed. In the third phase, Taguchi’s single-objective optimization further multi-objective optimization of end milling process parameters have been carried out by means of multi-objective optimization techniques such as: Taguchi based Grey Relational Analysis (T-GRA) and Taguchi coupled ‘Technique of Order Preference Similarity to the Ideal Solution’ (T-TOPSIS). Experimental outcomes have proved that the output responses in end milling process can be enhanced efficiently through T-GRA approach. Comparative analysis between T-GRA and T-TOPSIS has been carried out, which revealed that T-GRA is giving a better output result over T-TOPSIS and hence it is more suitable technique for multi-characteristic optimization of end milling process. Experimental results were further analyzed using ANOVA and S/N Ratio techniques. Then, to validate the test results obtained through optimized conditions, confirmation tests were performed.Finally, it has been investigated that, proposed PFM along with the chosen multi-objective optimization techniques has yielded better results. The investigation reveals that surface roughness (Ra) is predominantly affected by feed rate and the proposed PFM yields better surface finish over the existing CFM with both coated (TiAlN) and un-coated cutting tools. Depth of cut was identified as the most influencing parameter affecting the cutting tool tip temperature followed by feed rate and cutting speed is having least effect over it. However, progressive feed machining had yielded lower values of cutting tool tip temperature over existing constant feed machining with both coated (TiAlN) and uncoated cutting tools. Coated cutting tool has given a better result in case of surface roughness and cutting tool tip temperature. However, there is no much difference was found in material removal rate between coated and uncoated tools.