PARAMETRIC ANALYSIS OF A GRINDING PROCESS USING THE ROUGH SETS THEORY

被引：10

作者：

Agarwal, Subham ^{[1
]}

Dandge, Shruti Sudhakar ^{[2
]}

Chakraborty, Shankar ^{[1
]}

机构：

[1] Jadavpur Univ, Dept Prod Engn, Kolkata, W Bengal, India

[2] Govt Polytech, Mech Engn Dept, Murtizapur, Maharashtra, India

来源：

FACTA UNIVERSITATIS-SERIES MECHANICAL ENGINEERING | 2020年 / 18卷 / 01期

关键词：

Data Mining; Rough Sets Theory; Grinding; Parameter; Rule; MACHINING PARAMETERS; SURFACE-ROUGHNESS; RULE-GENERATION; OPTIMIZATION; PREDICTION; EFFICIENCY; ALGORITHM;

D O I：

10.22190/FUME191118007A

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

With continuous automation of the manufacturing industries and the development of advanced data acquisition systems, a huge volume of manufacturing-related data is now available which can be effectively mined to extract valuable knowledge and unfold the hidden patterns. In this paper, a data mining tool, in the form of the rough sets theory, is applied to a grinding process to investigate the effects of its various input parameters on the responses. Rotational speed of the grinding wheel, depth of cut and type of the cutting fluid are grinding parameters, and average surface roughness, amplitude of vibration and grinding ratio are the responses. The best parametric settings of the grinding parameters are also derived to control the quality characteristics of the ground components. The developed decision rules are quite easy to understand and can truly predict the response values at varying combinations of the considered grinding parameters.

引用

页码：91 / 106

页数：16

共 50 条

[21] Software safety analysis using rough sets
Chen-Jimenez, IE
Kornecki, A
Zalewski, J
PROCEEDINGS IEEE SOUTHEASTCON '98: ENGINEERING FOR A NEW ERA, 1998, : 15 - 19
[22] The study of normal form of relational rough sets theory database based on rough sets theory
An Qiusheng
Wang Gaoping
Zhang Wenxiu
GRC: 2007 IEEE INTERNATIONAL CONFERENCE ON GRANULAR COMPUTING, PROCEEDINGS, 2007, : 245 - +
[23] The Solution to Poor Data Bank Using Rough Sets Theory
Zhang Shilin(Security and Environmental Engineering Department of Jixi University
EngineeringSciences, 2006, (01) : 94 - 97
[24] Constructing associative classifier using rough sets and evidence theory
Jiang, Yuan-Chun
Liu, Ye-Zheng
Liu, Xiao
Zhang, Jie-Kui
ROUGH SETS, FUZZY SETS, DATA MINING AND GRANULAR COMPUTING, PROCEEDINGS, 2007, 4482 : 263 - +
[25] FEATURE SELECTION AND IMAGE CLASSIFICATION USING ROUGH SETS THEORY
Aguiar Pessoa, Alex Sandro
Stephany, Stephan
Garcia Fonseca, Leila Maria
2011 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2011, : 2904 - 2907
[26] Support vector machine ensemble using rough sets theory
Department of Automation, Shanghai Jiaotong University, Shanghai 200030, China
High Technol Letters, 2006, 1 (58-62):
[27] The Application of Rough Sets Theory in Video Information Processing and Analysis
Li, X. W.
Kang, Y. X.
Li, X. W.
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON COMPUTER INFORMATION SYSTEMS AND INDUSTRIAL APPLICATIONS (CISIA 2015), 2015, 18 : 403 - 405
[28] Application of Rough Sets Theory to Sources Analysis of Atmospheric Particulates
Fang Chunsheng
Chen Fending
Wei Qiang
Wang Shouchao
Wang Ju
2010 4TH INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICAL ENGINEERING (ICBBE 2010), 2010,
[29] Methods to Edit Multi-label Training Sets Using Rough Sets Theory
Bello, Marilyn
Napoles, Gonzalo
Vanhoof, Koen
Bello, Rafael
ROUGH SETS, IJCRS 2019, 2019, 11499 : 369 - 380
[30] THEORY OF GRINDING PROCESS
BLECHSCHMIDT, J
ZELLSTOFF UND PAPIER, 1977, 26 (04): : 111 - 113

← 1 2 3 4 5 →