The Oil and Gas industry shares many requirements and characteristics with the Defence sector; Operations are conducted in remote, challenging, often hazardous environments with little established infrastructure. Increasingly, remote monitoring is being used to provide more efficient inspection and maintenance of critical equipment. This provides valuable expert resources with effective status monitoring and the ability to function across an organisation, irrespective of location.
Drawing on experience from the Defence sector, this paper discusses how organisations use remote monitoring to deliver predictive, rather than reactive maintenance. It explores the benefits of integrating predictive maintenance with logistics and supply chain management to create a "predictive organisation" which can project and then optimise asset availability and integrity. New approaches for operators to consider are identified which are proven in the Defence sector.
When applied to a fleet of over 240 fast jets, these methods delivered £1.4bn cumulative savings over 6 years whilst meeting availability targets. The annual OPEX budget for the fleet fell from £711m to £328m. The customer was able to demand additional availability as required.
Areas examined include: -
What drivers underpin remote monitoring solutions in both industries? What are the key challenges?
How can data from a wide range of existing sensors be better used to provide reliable decision support?
How can information from a disparate range of equipment from multiple vendors be integrated into asset availability models?
How are availability levels assured, even across large portfolios? How is increased availability delivered on demand?
How can information derived from remote monitoring be used in a wider collaborative network to deliver increased benefits?
What security challenges do collaborative, multi-organisation remote support centres introduce?
The paper concludes with a summary of lessons identified and an example of how these are being harnessed in Oil and Gas.