The Library

Detecting catastrophic failure events in large-scale milling machines

Tools

Satti, Teysseer, Young, Ken and Grover, Samuel. (2009) Detecting catastrophic failure events in large-scale milling machines. International Journal of Machine Tools and Manufacture, Vol.49 (No.14). pp. 1104-1113. ISSN 0890-6955

Full text not available from this repository.

Official URL: http://dx.doi.org/10.1016/j.ijmachtools.2009.07.01...

Abstract

Catastrophic failure in milling machines is a major concern for manufacturers employing these processes in the production of vital parts. Tool chipping or breakage can lead to machine breakdown, which is a costly consequence in today's highly demanding industry. This paper introduces a novel and practical concept for the detection of failure events in milling. Using the historic data of the machining process (a collection of average spindle power signals) the detection algorithm computes discrete probability distributions representing the power consumption profile along finite synchronous process segments. These distributions play a central role in identifying failure: an unexpected occurrence in the process. Using a combination of real data collected from a powerful industrial milling machine and failure disturbance simulations, concept testing results illustrate that the proposed algorithm is capable of promptly detecting catastrophic faults while keeping unnecessary interruptions to the machine operation to a minimum. (C) 2009 Elsevier Ltd. All rights reserved.

Item Type:

Journal Article

Subjects:

T Technology > TS Manufactures
T Technology > TJ Mechanical engineering and machinery

Divisions:

Faculty of Science > WMG (Formerly the Warwick Manufacturing Group)

Journal or Publication Title:

International Journal of Machine Tools and Manufacture

Publisher:

Elsevier Science Ltd.

ISSN:

0890-6955