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Assessing the financial health of banks is crucial to ensure the stability of the financial system. This is not only a way to safeguard the interests of customers and shareholders but also to prevent inherent risks and ensure reliability in banking operations. Thus, evaluating financial health plays a crucial role in maintaining stability and sustainable development in the banking sector. This study employed three methods: RAM (Root Assessment Method), PSI (Preference Selection Index), and SRP (Simple Ranking Process), to assess the financial health of twenty-eight banks in Vietnam. Capital adequacy rating, asset quality rating, management rating, earnings rating, liquidity rating, and sensitivity to market risk rating are the six criteria used to characterize each bank. The evaluation results using these three methods were compared with each other and with the evaluation using the CAMELS rating system. The study identified banks with good financial health and those with weak financial health. The notable point is that the results of ranking financial health of banks using three methods: RAM, PSI, and SRP, and according to the CAMELS system are quite similar. These findings are vital in providing valuable information for managers and investors, aiding them in making informed decisions regarding investment, risk management, and development strategies based on empirical data.

This study aimed to optimize the selection of manufacturing solutions for flame retardant nanocomposite materials based on polyvinyl chloride (PVC). A total of eight different options were considered. The first option utilized PVC as the base material, and the subsequent options were carried out by adding specific amounts of reinforcing agents, including aluminum hydroxide (ATH) and zinc borate (ZB). The seven following options were denoted by their respective symbols: 5ATH/PVC, 10ATH/PVC, 15ATH/PVC, 5ZB/PVC, 10ZB/PVC, 15ZB/PVC, and 5ATH/5ZB/PVC. The number preceding the symbol of the reinforcing agent represents the percentage of the reinforcing agent added to the PVC material. For example, 5ATH/PVC signifies the addition of 5% of ATH reinforcing agent to the PVC material. To evaluate each option, five different indices were employed. The weight for each index was determined using four different methods, including the Equal method, Entropy method, MEREC method, and LOPCOW method. The RAM method was used to select the best option. The combination of the RAM method and the four weight determination methods generated four different datasets of option rankings. In all four of these datasets, the best and worst options consistently matched. The results indicated that the 15ATH/PVC option was deemed the best, while the pure PVC option was the worst.

Low surface roughness and high Material Removal Rate (MRR) are expected in most machining methods in general and milling method in particular. However, they sometimes do not occur, for example, the MRR is often small as the surface roughness is low. In this case, the decisions made should ensure that desires are simultaneously satisfied. This situation leads to a problem known as multi-criteria decision making (MCDM). In this study, five methods including EDAS, MARCOS, PIV, MOORA and TOPSIS are used together for the decision-making in the milling process. The purpose of the research is to determine the value of cutting parameters for both the low surface roughness and large MRR. The comparison of these methods for finding the best is carefully discussed as well.

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.

The purpose of the data normalization is to transfer the quantities with different dimensions to the same dimensionless form. The multi-criteria decision-making (MCDM) methods that require identifying the weight for each criterion, so the data normalization should be performed. In this study, five distinct data normalization methods were used in combination with a multi-criteria decision-making method (MARCOS method). All five of these data normalization methods were performed in combining with the MARCOS method and applied in three different cases. The number of solutions and the criteria in each case were different. Two different weighting methods were also used in each situation. After defining the most suitable data normalization methods in combining with the MARCOS method, this study proposed two new data normalization methods. The results show that solution rank is likely stable. The works in the future were mentioned in the last section of this article as well.

In this article, a multi-objective optimization of turning process study is presented. Two output parameters of the turning process taken into consideration are surface roughness and Material Removal Rate (MRR). Taguchi method has been applied to design the experimental matrix with four input parameters including nose radius, cutting velocity, feed rate and cutting depth. Copras method has been employed to solve the multi-objective optimization problem. Finally, the optimal values of the input parameters have been determined to simultaneously ensure the two criteria of the minimum surface roughness and the maximum MRR.

Abstract. In this article, a study on multi-objective optimization of the milling process is presented. CNC milling machine, cutting tool as TiAlN, experimental material as SCM400 steel and coolant as Caltex Aquatex 3180 oil have been used in the experiment. The objective of this study is to simultaneously ensure the minimum surface roughness and the maximum material removal rate (MRR). Taguchi method has been applied to design an experimental matrix with five input parameters, including coolant flow, coolant pressure, cutting velocity, feed rate, and cutting depth. Analysis of experimental results by Pareto chart has determined the effect of input parameters on output parameters. Moora method has been applied to determine the values of input parameters to simultaneously ensure the two criteria as mentioned above. Finally, the direction for further research has also been recommended in this study

In this paper, a study on multi-objective optimization of the cylindrical grinding process is presented. The experimental material used in this study is X12M steel. The two output parameters of the grinding process considered in this study are surface roughness and material removal rate (MRR). The cutting mode parameters including cutting speed, feed rate, and cutting depth have been selected as input parameters of the experimental process. Experimental matrix by Taguchi method has been used to design a matrix with 27 experiments. Analysis of experimental results by Pareto chart has determined the effect of input parameters on output parameters. The Data Envelopment Analysis-based Ranking (DEAR) method has been applied to determine the values of input parameters to simultaneously ensure the two criteria of minimum surface roughness and maximum MRR. Finally, the development direction for further studies has also been recommended in this study.

This paper presents a study on surface roughness of workpiece when grinding SKD11, SUJ2 steels using Al2O3 and CBN grinding wheels. The method on modeling and predicting of surface roughness of workpiece in the grinding theoretical research was applied. However, when applying this method, it is necessary to identify the value of the roughness adjust factor in practical case. In this paper, this factor was found by experimental process when surface grinding SKD11 and SUJ2 steels by Al2O3 and CBN wheels. It helps values of calculating surface roughness to be similar to experimental datas.