Product category:
Maintenance planning, services and equipment
News Release from: CSIRO | Subject: Remote Diagnostic and Maintenance System
Edited by the Manufacturingtalk Editorial
Team on 30 January 2004
Remote machine diagnosis is on the march
Machines will all work better and be less likely to fail if they are managed by a remote diagnostic and maintenance system integrated with internet capability writes Dr Murray Hollis.
What do aircraft, industrial machinery, metal die-casting equipment, automobiles, bridges and tall buildings have in common? They will all work better and be less likely to fail if they are managed by CSIRO's RDMS (Remote Diagnostic and Maintenance System) - a system developed by Dr John Mo and his team at CSIRO's Manufacturing and Infrastructure Technology This exciting development looks like lifting the reliability and safety of a vast array of machines to new levels
This article was originally published on Manufacturingtalk on 7 Jul 2008 at 8.00am (UK)
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In this context, 'machine' could mean anything from die-casting equipment to an automobile engine, to a large aircraft or a structure such as a bridge or large building.
All of these vibrate, distort or otherwise move in characteristic ways.
Data history for a specific machine that is operating as it is supposed to, provides the first basis for analysis by the RDMS.
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When operating 'signatures' differ from the ideal, fault conditions might be indicated.
Such fault diagnostic signals can by identified by the RDMS 'learning' about the machine.
The RDMS can then either automatically feed back remedial action or alert managers to maintenance or adjustment needs.
The new system is also integrated with internet capability to enable remote monitoring and management of machines.
For more than a century, engineers have strived to improve their methods of machine operation diagnosis and maintenance, using increasingly sophisticated methods of statistical and frequency analysis that have required detailed understanding of the characteristics of each machine.
The RDMS's feature-recognition algorithms, developed by Dr Mo and his colleagues, have greatly reduced the need for detailed understanding of machine dynamics, and do not rely on statistical or frequency analysis.
With some human input (how much really depends on the budget: a higher budget means less need for human input), the RDMS learns from the machine's history and continues to learn as it monitors machine operation.
It produces time signatures, generated through complex relationships by the RDMS from multiple data signal streams, to compare with acceptable signatures, and makes decisions for action.
The RDMS decisions could range from emergency shutdown to sending a finetuning feedback to the machine to bring it back into the normal operating regime.
Between these extremes, it might provide early warning of maintenance needs to managers or operators, or indicate that they should modify some operating parameters.
The core of the new development is the algorithm that enables this learning and diagnosis to be performed in a relatively machine-independent manner, and its integration with the internet or intranet services to enable very easy remote management of machines.
The RDMS has a scalable global system architecture that enables its application to one machine or thousands of machines located around the world - even the world is not the limit! The Windows-based integrated user interface and the compatibility of the RDMS with most major database systems ease the integration of the RDMS with clients' existing hardware and software.
A manufacturer of precision grinding machines uses the diagnostics capability of RDMS to identify and remedy grinding machine commissioning problems.
In one of the report cases, the service engineer spent two days trying to diagnose faults without success.
After using the RDMS methodology, the cause was identified immediately.
The potential for its application in the automotive industry has been demonstrated with a spark plug simulator; and RDMSs have been developed for die-casting and plasma-cutting equipment.
Dr Mo is keen to develop collaborative programs with industrial partners for the application of the RDMS technology to other machine operation diagnosis and management.
Dr Mo emphasises that the word 'machine' should be liberally interpretedScivil, mechanical, aeronautical, building and process engineering are just some of the fields where the application of the RDMS has great potential.
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