A lexicographic weighted Tchebycheff approach for multi-constrained multi-objective optimization of the surface grinding process

2016 ◽  
Vol 49 (5) ◽  
pp. 878-895 ◽  
Author(s):  
Soheyl Khalilpourazari ◽  
Saman Khalilpourazary
Keyword(s):  
Surface Grinding ◽  
Grinding Process ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Lexicographic Weighted Tchebycheff

scholarly journals COMBINATION OF TAGUCHI METHOD, MOORA AND COPRAS TECHNIQUES IN MULTI-OBJECTIVE OPTIMIZATION OF SURFACE GRINDING PROCESS

2020 ◽  
pp. 1-9
Author(s):  
Do Duc Trung
Keyword(s):  
Surface Roughness ◽  
Material Removal Rate ◽  
Material Removal ◽  
Optimization Problem ◽  
Removal Rate ◽  
Optimization Techniques ◽  
Surface Grinding ◽  
Grinding Process ◽  
Multi Objective Optimization ◽  
Multi Objective

This study presentes a combination method of several optimization techniques and Taguchi method to solve the multi-objective optimization problem for surface grinding process of SKD11 steel. The optimization techniques that were used in this study were Multi-Objective Optimization on basis of Ratio Analysis (MOORA) and Complex Proportional Assessment (COPRAS). In surface grinding process, two parameters that were chosen as the evaluation creterias were surface roughness (Ra) and material removal rate (MRR). The orthogonal Taguchi L16 matrix was chosen to design the experimental matrix with two input parameters namely workpiece velocity and depth of cut.  The two optimization techniques that mentioned above were applied to solve the multi-objective optimization problem in the grinding process. Using two above techniques, the optimized results of the cutting parameters were the same. The optimal workpiece velocity and cutting depth were 20 m/min and 0.02 mm. Corresponding to these optimal values of the workpiece velocity and cutting depth, the surface roughness and material removal rate were 1.16 µm and 86.67 mm3/s. These proposed techniques and method can be used to improve the quality and effectiveness of grinding processes by reducing the surface roughness and increasing the material removal rate.

scholarly journals Multi-Objective Optimization for Grinding Parameters of 20CrMnTiH Gear with Ceramic Microcrystalline Corundum

Materials ◽  
2019 ◽  
Vol 12 (8) ◽  
pp. 1352 ◽  
Author(s):  
Shengyong Zhang ◽  
Genbao Zhang ◽  
Yan Ran ◽  
Zhichao Wang ◽  
Wen Wang
Keyword(s):  
Surface Roughness ◽  
Practical Significance ◽  
Grinding Wheel ◽  
Linear Regression Method ◽  
Grinding Process ◽  
Low Carbon ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Grinding Parameters ◽  
The Impact

(1) The alloy material 20CrMnTiH is widely used in gear manufacturing, but difficult to process, and its quantity (efficiency) and quality (surface quality) are generally negative correlation indicators. As a difficult but realistic problem, it is of important practical significance to explore how to efficiently grind high-precision low-carbon alloy gear workpieces. (2) Firstly, the pixel method was applied to analyze the grinding principles and explore the grinding parameters—the grinding wheel speed and grinding wheel frame moving speed—as well as the feed rate, which impacts the grinding indicators. Secondly, based on the ceramic microcrystalline corundum grinding wheel and the 20CrMnTiH gear workpiece, controlled experiments with 28 groups of grinding parameters were conducted. Moreover, the impact curves of the grinding parameters on the grinding indicators—the grinding efficiency, grinding wheel life, and surface roughness—were obtained by the multiple linear regression method. Finally, the multi-objective optimization method was used to comprehensively optimize the grinding process. (3) Compared with the traditional grinding process, under optimized grinding parameters, the 20CrMnTiH gear workpieces have a lower surface roughness and a longer grinding wheel life, and require a shorter time to achieve grinding accuracy. (4) The grinding experiments showed that the grinding parameters are linearly related to the grinding indicators. The optimization results show that the precision, efficiency, and economy of the 20CrMnTiH gear grinding process have been improved via the comprehensive optimization of the grinding parameters.

Modified Multiobjective Dynamic Multi-Swarm Particle Swarm Optimization for Mineral Grinding Process

2014 ◽  
Vol 971-973 ◽  
pp. 1242-1246
Author(s):  
Tie Jun Chen ◽  
Yan Ling Zheng
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Problem ◽  
Pareto Frontier ◽  
Particle Swarm ◽  
Similarity Criterion ◽  
Grinding Process ◽  
Multi Objective Optimization ◽  
Swarm Optimization ◽  
Multi Objective ◽  
Simulation Results

The mineral grinding process is a typical constrained multi-objective optimization problem for its two main goals are quality and quantity. This paper established a similarity criterion mathematical model and combined Multi-objective Dynamic Multi-Swarm Particle Swarm Optimization with modified feasibility rule to optimize the two goals. The simulation results showed that the results of high quality were achieved and the Pareto frontier was evenly distributed and the proposed approach is efficient to solve the multi-objective problem for the mineral grinding process.

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