Prediction and optimization of machining parameters for minimizing power consumption and surface roughness in machining

The grey system theory, identified as one of the developed multiple attribute decision-making techniques, has been published by and indexed in over 300 internationally recognized refereed journals. The objective of this study is to conduct a bibliometric study on publication and citation patterns of grey system theory published from 1996 to 2010 through a systemic search using the ISI web-based databases with a specific focus on grey relational analysis (GRA) and grey prediction. Results of the study demonstrate that there has been a substantial increase in the number of peer-reviewed papers on GRA or grey prediction indexed by the ISI Web of Knowledge. Also, citation analysis was used to examine the contributions of GRA and grey prediction studies. This bibliometric analysis would provide a ready reference for scholarly works on GRA and grey prediction, and serve as an informative summary kit for future research works.

Review: Fifteen years of grey system theory research: A historical review and bibliometric analysis

This paper investigates optimisation design of an in-feed centreless cylindrical grinding process performed on EN52 austenitic valve steel (DIN: X45CrSi93). The major performance characteristics selected to evaluate the process are surface roughness, out of cylindricity of the valve stem and diametral tolerance, and the corresponding centreless cylindrical grinding parameters are dressing feed, grinding feed, dwell time and cycle time. In this study, since the process is with multiple-performance characteristics, therefore, the grey relational analysis that uses grey relational grade as performance index is specially adopted to determine the optimal combination of centreless cylindrical grinding parameters. Moreover, the principal component analysis is applied to evaluate the weighting values corresponding to various performance characteristics so that their relative importance can be properly and objectively described. The results of confirmation experiments reveal that grey relational analysis coupled with principal component analysis can effectively be used to obtain the optimal combination of centreless cylindrical grinding parameters. Hence, this confirms that the proposed approach in this study can be a useful tool to improve the centreless cylindrical grinding performance of valve stem in in-feed centreless cylindrical grinding process.

Grey relational analysis coupled with principal component analysis for optimisation design of the process parameters in in-feed centreless cylindrical grinding

Assessing the response of yield and comprehensive fruit quality of tomato grown in greenhouse to deficit irrigation and nitrogen application strategies

http://www.ysxbcn.com/down/upfile/soft/20120705/05-p1286.pdf

Optimization of machining parameters in drilling hybrid aluminium metal matrix composites

Grey relational analysis coupled with principal component analysis for optimization design of the cutting parameters in high-speed end milling

This paper presents a predicted model of surface roughness of radial relief for resharpening end-mill. This model is constructed using a polynomial network. The major factors affecting grinding parameters are considered to be wheel spindle speed, feedrate, and grinding depth of cut. Experiments under specified conditions are deliberately designed and conducted to obtain the corresponding tested data for surface roughness that are used for training data of the proposed polynomial network. Consequently, a predicted model for surface roughness is established. Furthermore, a computer program in VB language is written based on this model. It can quickly calculate predicted values of surface roughness by simply inputting required cutting parameters. According to the experimental results, the developed polynomial network model shows high predicting capability on surface roughness of radial relief, and possesses promising potential in the application of predicting surface roughness in resharpening end-mill operation.

The Predicted Model of Surface Roughness in Resharpening End-Mill for Tool Grinder

This paper presents an optimal cutting-parameter design of heavy cutting in side milling for SUS304 stainless steel. The orthogonal array with relational analysis is applied to optimize the side milling process with multiple performance characteristics. A grey relational grade obtained from the grey relational analysis is used as a performance index to determine the optimal cutting parameters. The selected cutting parameters are cutting speed, feed per tooth, axial depth of cut, and radial depth of cut, while the considered performance characteristics are tool life and metal removal rate. Experimental results have shown that cutting performance in the side milling process for heavy cutting can be significantly improved through this approach.

H.S. Lu

Papers

Grey relational analysis coupled with principal component analysis for optimization design of the cutting parameters in high-speed end milling

The Predicted Model of Surface Roughness in Resharpening End-Mill for Tool Grinder

The Optimal Cutting-Parameter Design of Heavy Cutting in Side Milling for SUS304 Stainless Steel