contributor author | K. Ramamurthi | |
contributor author | C. L. Hough | |
date accessioned | 2017-05-08T23:41:50Z | |
date available | 2017-05-08T23:41:50Z | |
date copyright | August, 1993 | |
date issued | 1993 | |
identifier issn | 1087-1357 | |
identifier other | JMSEFK-27765#268_1.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/112228 | |
description abstract | Machining economics may be improved by automating the replacement of cutting tools. In-process diagnosis of the cutting tool using multiple sensors is essential for such automation. In this study, an intelligent real-time diagnostic system is developed and applied towards that objective. A generalized Machining Influence Diagram (MID) is formulated for modeling different modes of failure in conventional metal cutting processes. A faster algorithm for this model is developed to solve the diagnostic problem in real-time applications. A formal methodology is outlined to tune the knowledge base during training with a reduction in training time. Finally, the system is implemented on a drilling machine and evaluated on-line. The on-line response is well within the desired response time of actual production lines. The instance and the accuracy of diagnosis are quite promising. In cases where drill wear is not diagnosed in a timely manner, the system predicts wear induced failure and vice versa. By diagnosing at least one of the two failure modes, the system is able to prevent any abrupt failure of the drill during machining. | |
publisher | The American Society of Mechanical Engineers (ASME) | |
title | Intelligent Real-Time Predictive Diagnostics for Cutting Tools and Supervisory Control of Machining Operations | |
type | Journal Paper | |
journal volume | 115 | |
journal issue | 3 | |
journal title | Journal of Manufacturing Science and Engineering | |
identifier doi | 10.1115/1.2901660 | |
journal fristpage | 268 | |
journal lastpage | 277 | |
identifier eissn | 1528-8935 | |
keywords | Machining | |
keywords | Cutting tools | |
keywords | Failure | |
keywords | Patient diagnosis | |
keywords | Drills (Tools) | |
keywords | Wear | |
keywords | Machinery | |
keywords | Assembly lines | |
keywords | Sensors | |
keywords | Algorithms | |
keywords | Economics | |
keywords | Modeling | |
keywords | Metal cutting AND Drilling | |
tree | Journal of Manufacturing Science and Engineering:;1993:;volume( 115 ):;issue: 003 | |
contenttype | Fulltext | |