Optimization of grinding efficiency considering surface integrity of bearing raceway

Chang, Zhou; Jia, Qi

doi:10.1007/s42452-019-0697-8

Cited by 4 publications

(21 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this study, to overcome the mentioned difficulties, an approach to the solution for the multi-objective optimization problem by using a genetic algorithm was applied. The genetic algorithm, the same as in general evolutionary terms, was developed based on the idea that natural evolution is a perfect and appropriate process as well as a preeminent one [3,5]. This method is different from other traditional methods in several features [3,5]:…”

Section: Establishing the Objective Functionmentioning

confidence: 99%

“…Based on the above analysis results as well as mathematical models of previous studies [3,28], the output factors (Ra, Hz, O, MRR) can be hypothesized as products of exponents of the input variables (S nf , V w , a f , N p ).…”

mentioning

confidence: 94%

“…The raceway surface is the working surface of the bearings; its machining quality directly affects the durability and rotational accuracy of the bearings [1,2]. The shoe-type centerless grinding (STCG) is one of the most important processing methods used in the manufacture of bearing raceways because of its high productivity, technological reliability, and the possibility of full automation [3,4]. This processing method makes it possible to ensure the high accuracy of the size and shape of products and also a high degree of automation of both machine tools and automatic lines.…”

Section: Introductionmentioning

confidence: 99%

“…As far as the author knows, studies on shoe-type centerless grinding for bearing inner ring raceways and especially multi-objective optimization studies are scarce [1][2][3][4]. James E. Charmley [4] analyzed the effects of the angular position of two support "shoes" on the geometric and dynamic stability of the shoe-type centerless grinding process in his 1992 thesis.…”

Section: Introductionmentioning

confidence: 99%

“…In 2017, based on the integrated grinding process model, Jingliang Jiang et al [1] proposed the determination method on the process parameters in the inner ring raceway grinding operation in order to avoid the dark layer occurrence, to ensure the technical requirement on the roughness, and to reach the smallest value of the machining time. Recently, Zhou Chang et al [2,3] proposed a multi-objective optimization method that considers the surface integrity constraints of the bearing raceway. In this optimization problem, the objective function is the minimum grinding time and maximum material removal rate.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Multi-Objective Optimization of Process Parameters to Enhance Efficiency in the Shoe-Type Centerless Grinding Operation for Internal Raceway of Ball Bearings

Tuan¹

2021

Metals

View full text Add to dashboard Cite

In this article, new research on the multi-objective optimization of the process parameters applied to enhance the efficiency in the shoe-type centerless grinding operation for the inner ring raceway of the ball bearing made from SUJ2 alloy steel is presented. The four important input parameters for this process, which included the normal feed rate of fine grinding (Snf), the speed of the workpiece (Vw), the cutting depth of fine grinding (af), and the number of ground parts (Np), were investigated. The aim of the study was to find the most appropriate value set of process parameters in order to, simultaneously minimize the grindstone wear (Gw), maximize the material removal rate (MRR) and the total number of ground parts in a grinding cycle (N’p), while guaranteeing other technology requirements such as surface roughness Ra ≤ 0.5 (µm), oval level Op ≤ 3 (µm), etc. In order to solve the problem, based on the experimental data, in which the grindstone wear was measured online by a measuring system consisting of two pneumatic probes, the optimization of the target functions of Gw, N’p, and MRR and mathematical models that express the dependencies of outcome parameters Gw, Ra, Op, MRR, etc. on the process parameters were determined. Therefore, a global optimal solution of such a discrete and nonlinear multi-objective optimization problem was solved by using a genetic algorithm, presenting the most appropriate process parameters as follows: Snf = 15.38 (µm/s), Vw = 6.00 (m/min), af = 11.76 (µm), and Np = 20 (parts/cycle). In addition, the impact of the four process parameters (Snf, Vw, af, Np) on the wear of the grinding wheel (Gw), the oval level of parts (Op), and the surface roughness of parts (Ra) was evaluated. The discovered technology mode has been applied to the real machining process for the inner ring raceway of the 6208_ball bearing made from SUJ2 alloy steel, and the outcome showed a much better result in comparison with default setting modes, while still ensuring the technology requirements. The difference between the predicted values and the real values of the parameters Gw, Ra, Op, and MRR were controlled within 5% of the ranges.

show abstract

Section: Establishing the Objective Functionmentioning

confidence: 99%

mentioning

confidence: 94%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Multi-Objective Optimization of Process Parameters to Enhance Efficiency in the Shoe-Type Centerless Grinding Operation for Internal Raceway of Ball Bearings

Tuan¹

2021

Metals

View full text Add to dashboard Cite

show abstract

Roughness Prediction and Performance Analysis of Data-Driven Superalloy Belt Grinding

et al. 2022

View full text Add to dashboard Cite

Abrasive belt grinding has unique advantages in avoiding machining defects and improving surface integrity while grinding hard materials such as superalloys. However, the random distribution of abrasive particles on the abrasive belt surface is uncontrollable, and chatter and machining errors accompany the machining process, leading to unclear mapping relationship between process parameters and surface roughness, which brings great challenges to the prediction of surface roughness of superalloy. Traditional empirical equations are highly dependent on empirical knowledge and the development of scientific theories and can only solve problems with relatively simple and clear mechanisms, but cannot effectively solve complex and mutually coupled problems. The method based on data-driven patterns has a better idea for mining the implicit mapping relationship and eliminating the uncertainty of complex problems. This study presents a data-driven roughness prediction method for GH4169 superalloy. First, a superalloy grinding platform is built. According to the grinding empirical equation, the mapping relationship between process parameters and surface roughness is analyzed, and a prediction model is established based on the error back propagation (BP) algorithm. Second, genetic algorithm (GA) and particle swarm optimization (PSO) algorithm are used to optimize the weights and thresholds of the neural network, and the global optimal solution is obtained. Finally, the prediction performance of different algorithms is compared. The results show that the non-uniform absolute errors of the BP algorithm, GA-BP algorithm, and PSO-BP algorithm are 0.12, 0.085, and 0.078, respectively. The results show that the roughness prediction algorithm based on PSO-BP is more suitable for GH4169 superalloy.

show abstract

The Effects of Process Parameters on Workpiece Roundness in the Shoe-Type Centerless Grinding Operation for Internal Raceway of Ball Bearings

Tuan

2023

Coatings

View full text Add to dashboard Cite

One of the most important indices of bearing raceway, roundness, has an important influence on the life and performance of the bearing. Currently, shoe-type centerless grinding (STCG) is a core process for the fabrication of the raceway surface. Some researchers have carried out studies in this field; however, the reason and extent of the influence of process parameters on the workpiece roundness in the STCG operation for the internal raceway of the 6208 ball bearings are not clear up to now. In this paper, new research on the effects of process parameters on workpiece roundness in the STCG operation for the internal raceway of the 6208 ball bearings is presented. The influence of the angular placement of the two shoes, as well as the technology parameters including the offset between the rotational centers of the workpiece and the magnetic drivehead (e), the normal feed rate (Snf), the speed of the workpiece (nw), and the grinding depth (af), on the roundness of the raceway surface were investigated both theoretically and experimentally to solve the difficulties in the STCG operation to ensure the roundness of the raceway surface. Based on the research results, a guideline for selecting initial process parameters is introduced to ensure the roundness of the bearing raceway in the STCG operation for the internal raceway of 6208_ball bearings on the 3MK136B grinder.

show abstract

Optimization of grinding efficiency considering surface integrity of bearing raceway

Cited by 4 publications

References 20 publications

Multi-Objective Optimization of Process Parameters to Enhance Efficiency in the Shoe-Type Centerless Grinding Operation for Internal Raceway of Ball Bearings

Multi-Objective Optimization of Process Parameters to Enhance Efficiency in the Shoe-Type Centerless Grinding Operation for Internal Raceway of Ball Bearings

Roughness Prediction and Performance Analysis of Data-Driven Superalloy Belt Grinding

The Effects of Process Parameters on Workpiece Roundness in the Shoe-Type Centerless Grinding Operation for Internal Raceway of Ball Bearings

Contact Info

Product

Resources

About