Mixing powder into dielectric fluid in electrical discharge machining (PMEDM) is a very interesting technological solution in current research. This method has the highest efficiency in simultaneously improving the productivity and quality of a machined surface. In this study, material removal rate (MRR), surface roughness (SR), and the micro-hardness of a machined surface (HV) in electrical discharge machining of die steels in dielectric fluid with mixed powder were optimized simultaneously using the Taguchi–TOPSIS method. The process parameters used in the study included workpiece materials (SKD61, SKD11, SKT4), electrode materials (copper, graphite), electrode polarity, pulse-on time, pulse-off time, current, and titanium powder concentration. Some interaction pairs among the process parameters were also used to evaluate the effect on the optimal results. The results showed that MRR and HV increased and SR decreased when Ti powder was mixed into the dielectric fluid in EDM. Factors such as powder concentration, electrode material, electrode polarity, and pulse-off time were found to be significant in the optimal indicator (C*) and the S/N ratio of C*. Powder concentration was also found to be the most significant factor; its contribution to C* was 50.90%, and S/N ratio of C* was 51.46%. The interactions of the powder concentration and certain process parameters for C* were found to be largest. The optimum quality characteristics were MRR = 38.79 mm3/min, SR = 2.71 μm, and HV = 771 HV. The optimal parameters were verified by experiment, and its accuracy was good (max error ≈13.38%). The finished machined surface under optimum conditions was also analyzed. The machined surface quality under optimum conditions was good. In addition, the results of the study showed the TOPSIS limitations of TOPSIS in a multi-criteria optimization problem.

Application of TOPSIS to Taguchi method for multi-characteristic optimization of electrical discharge machining with titanium powder mixed into dielectric fluid

The bullwhip effect leads to considerable inefficiencies along the food supply chain such as missed production schedules, poor customer service, excessive inventory, and misguided capacity plans. To tackle this problem, it is necessary, apart from other interventions, to continuously monitor the performance of food suppliers so that the demand information flow, order batching, transportation planning, and inventory management can be substantially improved. Therefore, supplier assessment has then become critical decision‐making support for identifying and addressing inefficiencies of food providers, which ends up reducing the variation of several key logistics parameters for upstream members of the food supply chain. In addition, such assessment is of multicriteria nature given the presence of several criteria from different domains and various food suppliers. With these considerations in mind, this paper proposes a hybrid approach integrating the analytic hierarchy process (AHP), decision‐making trial and evaluation laboratory (DEMATEL), and the technique for order of preference by similarity to ideal solution (TOPSIS) for evaluating the performance of pork suppliers. Thereby, the economic and operational burden caused by the bullwhip effect throughout the pork supply chain can be alleviated. AHP was first used to determine the criteria and subcriteria weights. Then DEMATEL was applied to assess the interdependence and feedback between the decision elements. Finally, TOPSIS was implemented to discriminate between high‐performance and low‐performance pork suppliers. A case study from the Colombian pork supply chain is presented to validate the proposed approach. The results of this study evidenced that the most important criterion was the “service level” and the most influencing factor was the “financial profile.” In addition, based on the supplier assessment results, improvement plans, and new negotiation, strategies were established for each supplier in order to diminish the bullwhip effect along the pork supply chain.

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A case of food supply chain management with AHP, DEMATEL, and TOPSIS

Multi Criteria Decision Making (MCDM) is the quantitative and qualitative method, problem has many solution but to find the solution and to get the appropriate decision regarding the solution is the application of MCDM. This paper gives the information about all the MCDM methods with the applications of maximum MCDM methods to various fields as per the literature. The aim is revel MCDM methods and their applications to understand the nature of MCDM for various problems. The utilization of MCDM to other field gives an idea for the new research area. The review helps to find the problems studied by different researcher and the solution they interpreted by using MCDM methods like ELECTRA, PROMETHEE, TOPSIS, AHP,GP etc. AHP, TOPSIS, MAUT were the most used methods but hybrid or integrated methods gives the solution for problem like location, finance, bankrupt, construction bridges, waste water and many more. This combination creates the new era in MCDM history.

/pdf/multi-criteria-decision-making-mcdm-methods-and-its-2asaa1ap57.pdf

Multi Criteria Decision Making (MCDM) Methods and its applications

The present research focuses on optimizing the process parameters of die-sinking electric discharge machining on tool steel. The basic objective of this research is to investigate the influence of two categorical factors including dielectric type and electrode polarity, and two numeric factors including discharge current, and Spark/Discharge Gap on material removal rate (MRR) and surface roughness (Ra) for machining of AISI D2 steel. Box-Bhenken design based on response surface methodology (RSM) was applied for experimental design. For estimation and evaluation, the effects of the process parameters on response variables, RSM has been integrated with grey relational analysis (GRA). Ranking of factors has been done with respect to the grey relational grade. (ANOVA) was further performed for determining the significance of grey relational grade. ANOVA results reveal that that polarity having 50% of percentage contribution was the most significant factor affecting the performance measures followed by the spark gap, discharge current, and dielectric type. The grey relational grades were further optimized through desirability function and the optimal condition for input parameters was obtained. The optimum levels were discharge current at 15 A, dielectric type of kerosene oil, spark gap at 6 mm, and polarity of positive has been determined. The confirmatory tests were run for verifying and validating the results and improvement in productivity (MRR) up to 17.23 mm3/min and quality (Ra) up to 3.86 μm at an optimum have been observed.

Investigating the effects of electric discharge machining parameters on material removal rate and surface roughness on AISI D2 steel using RSM-GRA integrated approach

Multi criteria decision making through TOPSIS and COPRAS on drilling parameters of magnesium AZ91

Applications of TOPSIS Algorithm on various Manufacturing Processes: A Review☆

In this work, a Material removal rate (MRR), Tool wear rate (TWR), Radial and overcut (ROC), a study on the die-sinking Electrical discharge machining (EDM) of Al-LM6/SiC/B4C hybrid composites has been carried out. The selection of above-mentioned hybrid composite was made considering its widespread application in aerospace, automotive, defense, biomedical and marine industries, due to its light weight and higher mechanical properties. This experiment was made only for the finish stage and has been carried out on the influence of four design factors: composition, discharge current (Ip), Pulse-on-time (Ton), Radial overcut (ROC) and Duty factors (Tau), over the previously mentioned, responded variables. This has been done by means of the method of design of experiment (DOE) which allows us to carry out the above-mentioned analysis performing a relatively small number of experiments. The study indicates that when discharge current (Ip) increases, Material removal rate increased. In the case of Tool wear rate the most influencing factor is discharge current, then pulse on time. In radial over cut most influence factor is discharge current then pulse on time, duty factor and composition has least.

Experimental Investigation of EDM Parameters on Al-LM6/SiC/B4C Hybrid Composites

Microstructural evolution, compressive deformation and corrosion behaviour of thermally oxidized porous Ti4Al4Co alloy made of mechanically alloyed powder

Ti-foam of varying relative densities has been synthesis through the PM route using ABC as a space holder. Microstructure, cell size and cell wall were evaluated. The compressive deformation of Ti-foams samples with different relative densities was conducted at different temperatures. The yield stress, elastic modulus, energy absorption increases with increasing relative density and also decrease with increase testing temperature. Densification strain decreases with increasing relative density and testing temperature. The micro shear bands visible when deformed at 400-600 °C whereas at lower temperatures foam crumbled. It is due to improved ductility at a higher temperature.

Pankaj Agarwal

Papers

Applications of TOPSIS Algorithm on various Manufacturing Processes: A Review☆

Experimental Investigation of EDM Parameters on Al-LM6/SiC/B4C Hybrid Composites

Microstructural evolution, compressive deformation and corrosion behaviour of thermally oxidized porous Ti4Al4Co alloy made of mechanically alloyed powder

Microstructure and High Temperature Compressive Deformation in Lightweight Open Cell Titanium Foam