contributor author | John T. Roth | |
contributor author | Dragan Djurdjanovic | |
contributor author | Xiaoping Yang | |
contributor author | Laine Mears | |
contributor author | Thomas Kurfess | |
date accessioned | 2017-05-09T00:39:18Z | |
date available | 2017-05-09T00:39:18Z | |
date copyright | August, 2010 | |
date issued | 2010 | |
identifier issn | 1087-1357 | |
identifier other | JMSEFK-28393#041015_1.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/144032 | |
description abstract | Tool condition monitoring (TCM) is an important aspect of condition based maintenance (CBM) in all manufacturing processes. Recent work on TCM has generated significant successes for a variety of cutting operations. In particular, lower cost and on-board sensors in conjunction with enhanced signal processing capabilities and improved networking has permitted significant enhancements to TCM capabilities. This paper presents an overview of TCM for drilling, turning, milling, and grinding. The focus of this paper is on the hardware and algorithms that have demonstrated success in TCM for these processes. While a variety of initial successes are reported, significantly more research is possible to extend the capabilities of TCM for the reported cutting processes as well as for many other manufacturing processes. Furthermore, no single unifying approach has been identified for TCM. Such an approach will enable the rapid expansion of TCM into other processes and a tighter integration of TCM into CBM for a wide variety of manufacturing processes and production systems. | |
publisher | The American Society of Mechanical Engineers (ASME) | |
title | Quality and Inspection of Machining Operations: Tool Condition Monitoring | |
type | Journal Paper | |
journal volume | 132 | |
journal issue | 4 | |
journal title | Journal of Manufacturing Science and Engineering | |
identifier doi | 10.1115/1.4002022 | |
journal fristpage | 41015 | |
identifier eissn | 1528-8935 | |
keywords | Force | |
keywords | Wear | |
keywords | Sensors | |
keywords | Hardware | |
keywords | Signal processing | |
keywords | Artificial neural networks | |
keywords | Condition monitoring | |
keywords | Cutting | |
keywords | Feature extraction | |
keywords | Signals | |
keywords | Grinding | |
keywords | Milling | |
keywords | Drilling | |
keywords | Machining AND Spindles (Textile machinery) | |
tree | Journal of Manufacturing Science and Engineering:;2010:;volume( 132 ):;issue: 004 | |
contenttype | Fulltext | |