Statistical Modelling to Study the Implications of Coated Tools for Machining AA 2014 Using Grey Taguchi-Based Response Surface Methodology

Milling is the surface machining process by removing material from the raw stock using revolving cutters. This process accounts for a major stake in most of the Original Equipment Manufacturing (OEM) industries. This paper discusses optimizing process parameters for machining the AA 2014 T 651 using a vertical milling machine with coated cutting tools. The process parameters such as cutting speed, depth of cut, and type of the cutting tool with all its levels are identified from the previous literature study and several trial experiments. The Taguchi L9 Orthogonal Array (OA) is used for the experimental order with the chosen input parameters. The commonly used cutting tools in the machining industry, such as High-Speed Steel (HSS) and its coated tools, are considered in this study. These tools are coated with Titanium Nitride (TiN) and Titanium Aluminum Nitride (TiAlN) by Physical Vapor Deposition (PVD) technique. The output responses such as cutting forces along the three-axis are measured using a milling tool dynamometer for the corresponding input factors. The input process parameters are optimized by considering the output responses such as MRR, machining torque, and thrust force. Grey Taguchi-based Response Surface Methodology (GTRSM) is used for multiobjective multiresponse optimization problems to find the optimum input process parameter combination for the desired response. Polynomial regression equations are generated to understand the mathematical relation between the input factor and output responses as well as Grey Relational Grade (GRG) values. The optimum process parameter combination from the desirability analysis is the HSS tool coated with TiAlN at a cutting speed of 270 rpm and a depth of cut value of 0.2 mm.

Multi-objective optimization of machining parameters during green machining of aerospace grade titanium alloy using Grey–Taguchi approach

This paper presents multi-objective optimization of aerospace-grade titanium alloy using the Gray–Taguchi approach. Experimentation has been conducted with varying cutting conditions according to Taguchi's L9 orthogonal array. Tool nose wear, tool flank wear, surface roughness and material removal rate are employed as process characteristics. The experimental outcomes are statistically analyzed using the Grey–Taguchi approach. Statistical and sensitivity analysis are also performed. Studies revealed that cutting speed and feed rate are having a significant influence on process performances. Micro analysis of cutting tool is also performed to study the kind of wear. Furthermore, chips were also analysed using scanning electron microscope to study its features and morphology to obtain a better insight into the process.

Vibration Analysis of Partially Cracked Symmetric Laminated Composite Plates Using Grey-Taguchi

Nowadays, the demand for carbon-boron boron-based composites has tremendously increased in the aerospace and automotive industries due to their lightweight and high strength-weight ratio. Hence, it is necessary to study the vibrational behavior of the carbon-boron matrix. The stacking sequences, fiber orientation, crack size, and length-width ratio has all been studied at three levels. A mathematical model has been developed using classical laminated plate theory to evaluate the natural frequency for two boundary conditions; first, all sides were supported (SSSS), second, two adjacent sides clamped, and the other two were simply supported (CCSS). Grey relation analysis has also been applied to optimize the parameters.

Modelling using dimensional analysis and optimization with grey-taguchi based fuzzy approach in s-eddg of skd-11 steel

The SKD-11 steel was machined by the hybrid surface-electro discharge diamond grinding (S-EDDG) machining process with an aim to determine the optimum setting of process parameters for multi-output optimization and thereafter developed the mathematical-models of material-removal-rate (MRR), and surface-roughness (Ra) through the Dimensional Analysis method. In this research work, Grey-Taguchi based Fuzzy method is utilized for multi-output optimization of process parameters. The various process-variables selected in this research work are current, voltage, wheel speed, pulse-on-time, duty-cycle, and nozzle flushing aid. Total 18 experiments have been conducted on S-EDDG set-up according to Taguchi’s L18 orthogonal array. The response table and Analysis of Variance investigation are used to determine the optimum setting of process control-parameters and further help to determine the impact of these control-factors on the multi-output performance index (MPI). In this research work, the Dimensional Analysis method is utilized for the development of mathematical models of MRR, and Ra. The experimental results and predicted estimation of values from the developed models were compared and showed satisfactory matching between them. The optimum combination of process variables suggested by the hybrid optimization method was validated through confirmation experiment whose result depicts that aimed MPI is significantly improved by 0.435. The suggested optimum setting of process variables helps the production engineer to set-up the economical-cum-efficient process.

Optimization of electrical discharge machining processing for ceramics using grey-taguchi system

Electrical discharge machining (EDM) is one of the importantly non-traditional processing technologies employed for ceramics’ surface processing. Modeling and optimization of the EDM process are essentially applied to find and obtain the optimal values of the responses for materials having smaller surface roughness, higher removing rate of materials, lower electrode wear rate. In this study, the Grey-Taguchi system with AHP weighting was applied in order to optimize the multi-responses of the EDM processing for ceramics. When the EDM processing was used in the ZrO2 ceramics for adhesive metal foils, the multi-response gray relational grade for the optimal level of machining parameter was 0.2685, which was higher than those using the initial experimental conditions. This study has proven that using the Grey-Taguchi system method with AHP weighting to find a model with a highly efficient standard for optimizing differently advanced machining processes is profitable.

Modeling of the machining parameters in turning of Al-5052/TiC/SiC composites: a statistical modeling approach using grey relational analysis (GRA) and response surface methodology (RSM)

PurposeMetal matrix composites (MMC) has been a section which gives an overview of composite materials and owing to those exceptional physical and mechanical properties, particulate-reinforced aluminum MMCs have gained increasing interest in particular engineering applications. Owing to the toughness and abrasive quality of reinforcement components such as silicon carbide (SiC) and titanium carbide (TiC), such materials are categorized as difficult materials for machining. The work aims to develop the model for evaluating the machinability of the materials via the response surface technique by machining three distinct types of hybrid MMCs.Design/methodology/approachThe combined effects of three machining parameters, namely “cutting speed” (s), “feed rate” (f) and “depth of cut” (d), together with three separate composite materials, were evaluated with the help of three performance characteristics, i.e. material removal rate (MRR), cutting force (CF) and surface roughness (SR). Response surface methodology and analysis of variance (ANOVA) both were initially used for analyzing the machining parameters results.FindingsThe contours were developed to observe the combined process parameters along with their correlations. The process variables were concurrently configured using grey relational analysis (GRA) and the composite desirability methodology. Both the GRA and composite desirability approach obtained similar results.Practical implicationsThe results obtained in the present paper will be helpful for decision-makers in manufacturing industries, who work on metal cutting area especially composites, to select the suitable solution by implementing the Grey Taguchi and modeling techniques.Originality/valueThe originality of this research is to identify the suitability of process parameters combination based on the obtained research results. The optimization of machining parameters in turning of hybrid metal matrix composites is carried out with two different methods such as Grey Taguchi and composite desirability approach.