Abstract
In most of the machining processes, the complexity arises in the selection of the right process parameters, which influence the machining process and output responses such as machinability and surface roughness. In such situations, it is important to estimate the inter-relationships among the output responses. One such method, Decision-Making Trial and Evaluation Laboratory (DEMATEL) is applied to study the inter-relationships of the output responses. Estimation of proper weights is also crucial where the output responses are conflicting in nature. In the current study, DEMATEL technique is used for estimating the inter-relationships for output responses in machining of EN 24 alloy under dry conditions. CRiteria Importance Through Inter-criteria Correlation (CRITIC) method is used to estimate the weights and finally the optimal selection of machining parameters is carried out using Techniques for Order Preference by Similarity to an Ideal Solution (TOPSIS) method. The model developed guides the decision maker in selection of precise weights, estimation of the inter relationships among the responses and selection of optimal process parameters.
Highlights
During the machining process, the friction developed at the tool-workpiece contact, which is generally reduced using a coated cutting tool or a coolant
Some Design of Experiments (DoE) methods based on Taguchi Orthogonal Array (OA) (Gaitonde et al, 2009) and Response Surface Methodology (RSM) (Mir & Wani, 2018) allow the user to conduct least number of experiments, as well as they are helpful in analyzing the effect of each factor, interaction effects between the process parameters
Decision-Making Trial and Evaluation Laboratory (DEMATEL) method is applied to dry machining of alloy steel to identify the relationships among the responses; criteria Correlation (CRITIC) method is used to identify the weights for the responses, and TOPSIS employed for optimal process parameters estimation
Summary
The friction developed at the tool-workpiece contact, which is generally reduced using a coated cutting tool or a coolant. Researchers have investigated Surface Roughness (SR), tool wear (flank wear & crater wear) and chip coefficient reduction in machining of titanium grade 5 alloy using Physical Vapor Deposition (PVD) AlTiN coated carbide as a cutting insert (Pradhan & Maity, 2018) They have optimized the machining parameters with desirability function approach, and found cutting speed is the most significant parameter. DEMATEL method is applied to dry machining of alloy steel to identify the relationships among the responses; CRITIC method is used to identify the weights for the responses, and TOPSIS employed for optimal process parameters estimation. This is a novel integrated MADM approach, which combines the three techniques: DEMATEL-CRITIC-TOPSIS. RSM – two full factorial designs – 27 runs ultra-high-strength steel 300M (Wang & Zhao, 2016b) 17-4 PH stainless steel (Sivaiah & Uma, 2019)
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