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Predictive maintenance unlocks lower costs

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African power utilities are evolving as they are unbundled into separate generation, transmission and distribution companies and as they come under growing pressure to service unserved communities as well as to support industrial growth.

By Colin Beaney, global industry director for asset-intensive and energy & utilities at IFS

They need to find ways to optimise their businesses. To combat current challenges such as ageing workforces, ageing assets, rising costs and growing user expectations, their approach to maintaining assets, in particular, must be more strategic and optimised.

Investment for modernising transmission and distribution equipment is limited, so utilities are looking to get more from their existing infrastructure. Preventive maintenance schedules alone are not effective enough in helping utility organisations to avoid asset failures and the associated costs.

Getting more from old infrastructure

According to an ARC Advisory Group research report in 2015, 82% of assets have a random failure pattern, which renders preventive maintenance strategies ineffective in managing equipment downtime and maxi¬mising equipment lifetime.

Against this backdrop, predictive maintenance (PdM)– a set of technologies that determine the condition of in-service equipment to predict when maintenance should be performed–is becoming increasingly relevant for African utilities.

As utilities struggle to maintain ageing transmission and distribution equipment, manage costs better and extend the reach, quality and reliability of their infrastructure, PdM promises cost savings over routine or time-based preventive maintenance.

Utility organisations that implement emerging sensor technology in conjunction with a strong enterprise asset management solution complete with advanced analytics will be able to oper-ate more efficiently and cost effectively while providing safer environments for their employees and better reliability for their customers.

A new-age business system is key

PdM requires not only the ability to contin¬uously monitor asset performance through sensors such as vibration monitor¬ing, but also a predictive engine that can process input and provide intelli¬gent responses automatically.

For the strategy to be effective, the col¬lected data and resulting responses must all be captured and processed in a streamlined enterprise asset management system to ensure compliance, effective business intelligence, and customer satisfaction.

With PdM, a sensor is put in place to monitor gas levels of a transformer, for example. After comparing historical data with real-time operating data, an alert triggers a utility organisation’s enterprise asset management software to automatically schedule a techni¬cian with the right skillset and the right parts to fix the failing transformer. A chain of events is triggered that unify and optimise the entire process from inventory management to human resources.

Cost savings of up to 12%

According to the US Department of Energy, a maintenance program that uses PdM can result in savings of 8% to 12% percent over a programme utilising preventive maintenance alone. Predictive maintenance can reduce energy and maintenance costs by up to 30%, breakdowns by 35% to 45%, and downtime by up to 75%. Realising these benefits starts with putting the right enterprise backbone in place.

Monolithic legacy systems do not have the capability to embrace new technologies and platforms without extensive, costly measures. Best-in-class utilities look to run leaner with agile solutions that are built for easy integration and scalability. The future of PdM success begins with internal change management, a solid IT infrastruc¬ture as a foundation, and software solution that can process and apply new strategies as the world and expectations continue to change.


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