# Multi-Criteria Decision Making in the PMEDM Process by Using MARCOS, TOPSIS, and MAIRCA Methods
###### Abstract  
Multi-criteria decision making (MCDM) is used to determine the best alternative among various options. It is of great importance as it hugely affects the efficiency of activities in life, management, business, and engineering. This paper presents the results of a multi-criteria decision-making study when using powder-mixed electrical discharge machining (PMEDM) of cylindrically shaped parts in 90 Cgi tool steel. In this study, powder concentration, pulse duration, pulse off time, pulse current, and host voltage were selected as the input process parameters. Moreover, the Taguchi method was used for the experimental design. To simultaneously ensure minimum surface roughness (RS) and maximum material-removal speed (MRS) and to implement multi-criteria decision making, MARCOS (Measurement of Alternatives and Ranking according to Compromise Solution), TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), and MAIRCA (Multi-Attributive Ideal-Real Comparative Analysis) methods were applied. Additionally, the weight calculation for the criteria was calculated using the MEREC (Method based on the Removal Effects of Criteria) method. From the results, the best alternative for the multi-criteria problem with PMEDM cylindrically shaped parts was proposed. PMDEM; multi-criteria decision making; MARCOS; TOPSIS; MAIRCA; MEREC; taguchi; 90 Cgi; surface roughness; material-removal speed +
Footnote †: journal: Applied  
in many mechanical machining processes, such as grinding [4; 5], turning [6; 7; 8], electrical discharge machining [9; 10; 11], waterjet machining [12; 13], etc. For the PMEDM process, it has been used to implement MCDM when machining Al\({}_{2}\)O\({}_{3}\) ceramics [14], Inconel 718 [15], Inconel X-750 [16], etc. The MAIRCA (Multi-Attributive Ideal-Real Comparative Analysis) method was proposed in 2014 [17] for the selection of railway crossings for investment in safety equipment. This method has the advantage that the objective function can be both qualitative and quantitative [6]. In [18], the MAIRCA method was used to rank and select the appropriate location for the construction of ammunition depots. Recently, it has been applied to MCDM in the turning process [6]. The MARCOS approach was recently proposed by [PERSON], [PERSON] et al. [19] when choosing sustainable suppliers in the healthcare industry in Bosnia and Herzegovina. This method is used for supplier selection in steel production [20]. It has been used for MCDM for three methods of processing, including milling, grinding, and turning [21]. In [22], this method was used to select suitable gear material and cutting fluid. A PMEDM process is understood as an EDM process with a dielectric solution mixed with metal powder in order to limit some disadvantages of the EDM process, such as low machined surface quality and small MMR. Like EDM, this type of machining is very effective when processing difficult-to-machine conductive materials and concave parts such as stamping dies and plastic molds. Therefore, there have been many studies on optimization or MCDM of PMEDM processes. The results of MCDM when PMEDM using titanium powder when machining SKD11 tool steel using the Preferred Selection Index (PSI) method have been shown in [23], in which the minimum SR and maximum MRR are selected as criteria. [PERSON] et al. [15] presented the selection of the best option when machining Inconel 718 using PMEDM with titanium powder. In this study, two criteria were SR and MRR, and the MCDM method was the TOPSIS method. The TOPSIS method was also applied in [24] when solving the MCDM problem in PMEDM with mixed Si powder when processing EN-31 tool steel. From the above analysis, it is obvious that there have been quite a few studies on MCDM for mechanical machining processes, including PMEDM, so far. Nevertheless, all of the studies on PMEDM have been carried out when machining concave parts or holes.