Development of a tool wear-monitoring system for hard turning

被引：134

作者：

Scheffer, C

Kratz, H

Heyns, PS ^{[1
]}

Klocke, F

机构：

[1] Univ Pretoria, DSG, Dept Mech & Aeronaut Engn, ZA-0002 Pretoria, South Africa

[2] RWTH Aachen Univ Technol, Lab Machine Tools & Prod Engn, WZL, Chair Mfg Technol, Aachen, Germany

来源：

INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE | 2003年 / 43卷 / 10期

关键词：

process monitoring; tool wear; hard turning; cutting forces; neural networks;

D O I：

10.1016/S0890-6955(03)00110-X

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

This paper describes an in-depth study on the development of a system for monitoring tool wear in hard turning. Hard turning is used in the manufacturing industry as an economic alternative to grinding, but the reliability of hard turning processes is often unpredictable. One of the main factors affecting the reliability of hard turning is tool wear. Conventional wear-monitoring systems for turning operations cannot be used for monitoring tools used in hard turning because a conglomeration of phenomena, such as chip formation, tool wear and surface finish during hard turning, exhibits unique behavior not found in regular turning operations. In this study, various aspects associated. with hard turning were investigated with the aim of designing an accurate tool wear-monitoring system for hard turning. The findings of the investigation showed that the best method to monitor tool wear during hard turning would be by means of force-based monitoring with an Artificial Intelligence (AI) model. The novel formulation of the proposed Al model enables it to provide an accurate solution for monitoring crater and flank wear during hard turning. The suggested wear-monitoring system is simple and flexible enough for online implementation, which will allow more reliable hard turning in industry. (C) 2003 Elsevier Science Ltd. All rights, reserved.

引用

页码：973 / 985

页数：13