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Towards improved availability of gas turbine equipment
Initial choice of gas turbine equipment should be based on achieving the lowest life cycle cost rather than the lowest installation capital cost, writes Dr Ken Ramsden. In addition, the need for inherent reliability, maximum availability and ease of maintenance are factors of major importance when specifying rotating machinery and ancillary equipment. These issues require informed judgements from the initial procurement stage through to continuous operation in the field.
Furthermore, since equipment suffers considerable degradation with use, on-going maintenance strategies are needed which achieve maximum availability at least cost. In choosing driven equipment to collectively satisfy these criteria, gas turbines nearly always emerge as the principal choice for prime mover within the oil and gas industry.
In delivering continuous improvements in financial performance, modern gas turbines and their related equipment have developed to a high level of sophistication. These advances can be best utilised by the operating company when there is a clear understanding of their implications for equipment management. When coupled with the fast pace of technological change, continuous awareness becomes of increasing importance.
Against this background, if a company is to fully achieve potential cost savings, technical staff, more than ever before, need to thoroughly understand the basic technology and the key issues in procurement, operations, reliability availability and maintenance.
To address these and other related issues, the Gas Turbine Engineering Group at Cranfield has for some years been developing a predictive maintenance capability through the creation of a computer based condition (or engine health) monitoring system.
If the time between maintenance actions is 20000 hours and the down-time is three months, then the availability achieved is 90 per cent. If, however, through use of appropriate diagnostic techniques, the parts could have been identified and ordered some months ahead, the down-time could be giving an availability of 99percent.
This and other related information from analytical models allow engine operators to make an informed judgement on maintenance and operational strategies of their engines.
One example of the use of this diagnostic tool was a techno-economic study which investigated the running costs of several plants over a period of 15 years.
The outcome was to predict performance in terms of the optimisation of cost of ownership, minimising payback period and maximising availability.
At at Cranfield University this work is ongoing and both full time and part time training programmes are being developed to serve the current needs of the oil and gas industry on how to select and manage its equipment.
Dr Ken Ramsden is head of the Gas Turbine Technology Group and Director of Continuous Development Programme, Department of Power and Propulsion, School of Engineering, Cranfield University, Cranfield, Bedfordshire, UK. www.cranfield.ac.uk
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