1. Introduction
As technology advances, machining processes must meet ever-increasing demands for mechanical product quality and productivity. Grinding is a type of machining that uses hard abrasive particles as the cutting medium. It is often the key to achieving the required quality [
1], so it is widely used for finishing and semi-finishing machine parts. It accounts for approximately 20 to 25 percent of the total industry spent on mechanical parts [
2].
In practice, the grinding wheel wears while working, affecting the process’s quality and productivity. As a result, the dressing process is required to ensure the grinding wheel’s original specification. The dressing process impacts the profile, topography, and wear behavior of the grinding wheel. Therefore, it has a significant influence on the grinding process’s efficiency and accuracy. For those reasons, researchers are always interested in improving the quality and productivity of grinding process as well as determining the best grinding mode.
A. Daneshi et al. [
3] conducted a study to identify appropriate dressing strategies for dressing in internal cylindrical grinding. In this study, two different types of wheels, including CBN (cubic boron nitride) and corundum wheels, and three separate dressing rollers, including an electroplated, a vitrified bond form roller, and a cup-dresser were used. Yueming Liu et al. [
4] used kinematic simulations to predict surface roughness in grinding. Three different abrasive grain shapes (sphere, truncated cone, and cone) and a single-point diamond dressing model were investigated in their study. In addition, the proposed surface roughness model was experimentally validated with a difference of 7–11 percent. F. Klocke and B. Linke [
5] investigated the mechanisms resulting in the formation of grinding wheel topography by dressing. The effect of kinematical dressing factors on wheel wear behavior has been computed in this work. Christian Walter et al. [
6] discussed the dressing and truing of hybrid bonded (metal-vitrified) CBN grinding wheels using a short-pulsed fiber laser. Several studies have been conducted to determine the optimum dressing mode. Optimal dressing parameters have been suggested for cylindrical grinding [
7,
8,
9], surface grinding [
10,
11,
12], and internal grinding [
13,
14]. L.M. Kozuro et al. [
15] proposed the following dressing mode for external grinding to achieve the surface roughness Ra = 0.32–1.25 (μm); a longitudinal feed rate of 0.4 (m/min); dressing four passes with a dressing depth of 0.03 (mm); and four passes non-feeding dressing.
Difficult-to-cut materials are becoming more popular as materials engineering advances. According to their application fields, difficult-to-cut materials are required to go through the grinding process. However, due to the complexity of the grinding process, several challenges are encountered while grinding these materials. These difficulties can be mitigated by employing effective lubricating techniques and selecting appropriate process parameters. Furthermore, a proper wheel dressing mode guarantees a reduction in these challenges during the grinding operation. As a result, many researchers are interested in grinding these materials. Manish Mukhopadhyay and Pranab Kumar Kundu [
16] conducted an experimental study of grinding Ti-6Al-4V using an alumina wheel. In their study, the simple and inexpensive RQL (restricted quantity lubrication) technique was shown to be significantly efficient in expanding Ti-6Al-4V grindability than both dry and flood cooling. It also greatly reduces coolant consumption when compared to flood cooling. Manish Mukhopadhyay et al. [
17] noted that using grinding fluid via the SQL (small quantity cooling and lubrication) technique results in better grinding results. In this study, alkaline soap water is discovered to be more efficient than conventional grinding fluid in the grinding of titanium alloy Ti-6Al-4V. Manish Mukhopadhyay and Pranab Kumar Kundu [
18] introduced an economical and environmentally friendly drop by drop delivery technique for improving the grindability of Ti-6Al-4V. The effective use of the environment-friendly unconventional fluids when machining Ti-6Al-4V has also been reported when using an alumina wheel [
19,
20] and a SiC wheel [
21]. Berend Denkena et al. [
22] investigated the wear-adaptive optimization of in-process conditioning factors during the face plunge grinding of PcBN. It was noted that the optimal input factors allow the process of in-process conditioning to dramatically reduce grinding tool wear without increasing the process time or non-productive time. Dung Hoang Tien et al. [
23] presented the results of a multi-target optimization study to find the optimum input factors for getting the minimum surface roughness and maximum material removal rate when external grinding SCM440 steel. When grinding GH4169 alloy with a ceramic bonded CBN grinding wheel, a multi-information fusion recognition model and experimental study of grinding wheel wear status were reported in [
24]. G. Xiao and S. Malkin [
25] conducted online-optimizing, the internal grinding process, and the dressing parameters to reduce the production time while maintaining part quality requirements. The optimum process parameters when grinding Ti-6Al-4 V using a CBN grinding wheel was introduced in [
26]. The Taguchi method and gray relational analysis (GRA) were applied to find the optimum dressing parameters when processing the SKD11 tool steel in surface grinding to increase the material removal rate and to reduce the roundness tolerance of the ground parts [
11].
Table 1 presents a brief overview of some previous studies on the dressing process of different types of grinding. In this table, the specifications of the grinding type, wheels, dresser, workpiece material, the objective of study, and the output optimum factors presented in these studies are indicated. This table helps to determine the ultimate optimal parametric combination for all methods considered.
From the above analyses and
Table 2, it can be noted that so far, there have been quite a few studies on the dressing mode and on the determination of the optimum or reasonable wheel dressing mode. Besides, different dressing modes such as coarse dressing, fine dressing, and non-feeding dressing influence the efficiency of the dressing process. However, to date, there has been no research on determining the best dressing mode among many different dressing setups for external grinding SKD11 tool steel using an MCDM method. Therefore, finding the best dressing mode in external cylindrical grinding SKD11 tool steel using an MCDM method has been taken into considered.
Multi-criteria decision making (MCDM) is a common problem when it is necessary to analyze multiple options to choose the best one. Numerous studies on MCDM have been conducted for various mechanical machining processes such as milling, turning, grinding, electrical discharge machining (EDM), etc. [
33]. This is because the machining process is frequently required to meet many criteria, such as the maximal material removal rate (MMR), the minimal surface roughness (SR), or the minimal tool wear rate. So far, several studies have been conducted to determine the best dressing mode using MCDM methods. Santonab Chakraborty and Shankar Chakraborty [
34] presented a scoping review on the applications of MCDM methods for the parametric optimization of machining processes. In this paper, more than 120 scientific papers are reviewed while investigating the implementations of various MCDM techniques in solving parametric optimization problems of turning, drilling, and milling processes. This review paper would serve as a knowledge base for determining the best experimental design plan to be deployed (Taguchi’s L9, L18, or L27 orthogonal array); difficult-to-cut advanced engineering materials to be machined (composites, aluminum, titanium, and their alloys); input parameters for turning, drilling, and milling processes, and corresponding responses to study their interaction effects, MCDM tools, and subjective and objective criteria weighting techniques to be used; and the possibility of integrating with other mathematical tools to deal with an uncertain decision-making environment. Ritwika Chattopadhyay et al. [
35] presented the results of a study conducted to determine the best supplier of gearboxes in the Indian iron and steel industry. In this study, a design of experiments (DoE)-based metamodel is developed to connect the computed MABAC scores to the criteria under consideration. Competing suppliers are ranked using a rough-MABAC-DoE-based metamodel, which also simplifies the computational steps when new suppliers are added to the decision-making process. Sanjay S. Patil and Yogesh J. Bhalerao [
32] used the TOPSIS (technique for order of preference by similarity to ideal solution) method to select levels of dressing parameters for a better surface finish in cylindrical angular grinding of En-31 parts. In this study, four input parameters, including the dressing cross feed rate, the dressing depth of cut, the width of the diamond dresser, and the drag angle of the dresser were investigated. However, only three solutions with a surface finish criterion are provided for the MCDM problem. H.Q. Nguyen et al. [
33] carried out a comparison study on MCDM for the dressing process when internal grinding SKD11 steel. Four MCDM methods, TOPSIS, MARCOS (measurement of alternatives and ranking according to compromise solution), EAMR (evaluation by an area-based method of ranking), and MAIRCA (multi-attributive ideal–real comparative analysis), as well as two weight calculation methods, entropy and MEREC, were used in this study. It can be recognized from the above analysis, that while there have been various applications of MCDM methods for different mechanical machining processes, no studies have been conducted to determine the best dressing mode for external cylindrical grinding.
This paper, hence, presents a study on MCDM for the dressing process in cylindrical external grinding. In this work, three criteria were chosen for the investigation: RS, wheel life T, and roundness Rn. In addition, to solve the MCDM problem, the MABAC method was selected. Furthermore, the MEREC and entropy methods were used to determine the weights of the criteria. As a result, the MABAC method has been successfully used to determine the best dressing mode in external cylindrical grinding. This result is also verified by using TOPSIS and MARCOS methods for comparison.