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Continuous Monitoring of Critical Valves, Leading to Predictive Maintenance

Continuous Monitoring of Critical Valves, Leading to Predictive Maintenance

TRC-2018 Learning Zone 39:16
by David Anderson, Score Diagnostics Limited

100% Valve Reliability (optimisation of valve performance over time, for minimum investment, with no surprises) is our vision for your valves. Since the year 2000, Score have been working with valve diagnostics equipment and systems to improve valves’ operating performance and reliability, dependent upon their criticality to the process. This track record has allowed us as a valve management company, to identify and develop strategies which optimise process operations and reliability. Being exposed to all of the failure modes in all of the valve designs and types commonly found in process plants throughout the world has shown us what to look for in terms of performance indicators that lead to in-service failures. Consequently, the ability to identify any/all emerging failure modes as early as possible delivers an operational reliability advantage. So, what we are interested in is, can we see and quantify any developing failure mode at any time, through a continuous condition and performance monitoring approach? What is that failure mode going to do to your process? And at what point do we want to make an intervention in terms of our valve management strategy? The most commonly deployed maintenance strategies lead to calendar-based interventions, so we are going to demonstrate new ways of working, to achieve better outcomes. We shall challenge the audience’s thinking on commonly applied maintenance management strategies and focus their attention on maximizing efficiency through an evidence-based approach to reliability centered maintenance. To support this, we shall present a real-life case study where the evidence from condition and performance monitoring of valves can be used to safely extend the MTBMI (Mean Time Between Maintenance Interventions) for critical valves in a gas distribution network. The results of course are minimised production downtime, minimised risks to process and personnel and greater efficiencies in operations.

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