Multi-criteria decision-making is important and it affects the efficiency of a mechanical processing process as well as an operation in general. It is understood as determining the best alternative among many alternatives. In this study, the results of a multi-criteria decision-making study are presented. In which, sixteen experiments on turning process were carried out. The input parameters of the experiments are the cutting speed, the feed speed, and the depth of cut. After conducting the experiments, the surface roughness and the material removal rate (MRR) were determined. To determine which experiment guarantees the minimum surface roughness and maximum MRR simultaneously, four multi-criteria decision-making methods including the MAIRCA, the EAMR, the MARCOS, and the TOPSIS were used. Two methods the Entropy and the MEREC were used to determine the weights for the criteria. The combination of four multi-criteria making decision methods with two determination methods of the weights has created eight ranking solutions for the experiments, which is the novelty of this study. An amazing result was obtained that all eight solutions all determined the same best experiment. From the obtained results, a recommendation was proposed that the multi-criteria making decision methods and the weighting methods using in this study can also be used for multi-criteria making decision in other cases, other processes.

Multi-criteria decision-making (MCDM) methods are used in many fields so as to rank alternatives and find the best one. However, rank reversal after adding or removing an alternative can occur in using some of the methods. In this study, two methods RAFSI and PIV were compared for application of making multi-criteria decisions. They are known to be capable of avoiding rank reversal problems. Sixteen 9XC steel turning tests were performed for the experiment. Tool holder length, spindle speed, feed rate and depth of cut are parameters that vary in each test. Three criteria for evaluating the turning process consist of MRR, RE and Ra. Four methods including MEREC, ROC, RS and EQUAL were used for determining weights of the criteria. The blend of two multi-criteria decision making methods (RAFSI and PIV) with four weight-determining methods resulted in eight ranking options. This is a new approach of the study. A positive outcome was reached that all eight ranking options identified the same best test. The best experiment must ensure to have maximum MRR and minimum RE and Ra simultaneously. A detailed discussion of the ranking results in each case was also carried out. Finally, the directions and issues that need to be studied further were pointed out in this paper as well.

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This paper presented the experimental results about investigation of the influence of the cutting conditions on the surface roughness when hole turning the SCM400 steel. Three cutting paramesters that have mentioned in this study included cutting speed, axial feed rate, and cutting depth. The experimental design was chosen following the orthogonal matrix and added the center experiment points. The analyzed results show that the axial feed rate has the greatest degree of impact on the surface roughness. And, the second and third factors have negligible effect on the surface roughness that are cutting speed and cutting depth, respectively. These results will guide the determination of the cutting conditions in order to machining the part surface with roughness that was ensured the setting requirement. Finally, the directions for further research were also mentioned in this paper.

In the current context, an attempt is being made to improve the electrical discharge machining (EDM) process by using powder particles in a suitable combination. To improve the quality of such procedures, the process parameters should be optimized. The present study proposes to utilize Taguchi–Grey relational analysis to discover the optimal combination of process parameters for SKD61 die steel specimens using titanium powder-mixed EDM (PMEDM). Among the machining parameters chosen, the optimal combination of current (3 A), pulse on-time (37 μs), pulse off-time (37 μs), and powder concentration (4 g/L) was determined experimentally. Due to its relevance in spark energy production, peak current is a more significant factor in PMEDM processes. A superior surface topography was obtained with increased microhardness and fewer microfractures over machined specimens with optimal process parameter in PMEDM. The titanium particles can effectively enhance the surface performance measures during PMEDM-based machining owing to tiny craters and pores with better lubrication.