Diesel generators play an important role in many different organisations. McKinsey & Company has claimed that between 35% and 55% of companies in Africa, the Middle East and South Asia own a diesel generator, and that in turn these could have a potential annual economic impact of $25 to $100 billion in 2025.
Generator sets (usually made up of a diesel engine, a generator and various ancillary devices) give organisations more flexibility over their energy usage and business continuity, enabling them to avoid costly downtime in the event of mains power failure, and potentially reducing their fuel costs. However, they are costly and cumbersome pieces of equipment – and if, as in many cases, they are not serviced properly, then they are liable to fail precisely at the moment of greatest need.
As such, intelligent maintenance is a crucial aspect of generator procurement and care. But what does ‘intelligent’ maintenance actually mean? Typically, simply scheduling a routine check-up every so often isn’t appropriate. It’s not the most efficient use of maintenance engineers’ time if nothing needs to be addressed – and if something does need to be addressed there’s always the risk that it actually occurred weeks previously, and has escalated to become more costly and complex to fix.
The key, then, is to introduce gateways that read the protocols from the Programmable Logic Controllers (PLCs) that control generator sets – and then send that data to cloud-based systems that can analyse it – creating a real-time view of how crucial aspects of said generators are performing. Bespoke alerts and alarms can be triggered when certain conditions are met, enabling managers to immediately ascertain when a small problem has occurred and maintenance needs to be scheduled. In turn, maintenance can be planned for specific periods of low demand, reducing downtime, and levels of consumables such as oil can be optimised too. Statistics from the Institute of Electrical and Electronics Engineers (IEEE) show that an effective electrical maintenance programme can reduce outages by as much as 66 %.
This predictive or condition-based maintenance offers companies the least expensive, most efficient method of reducing equipment-related downtime. In a predictive maintenance model, maintenance work is scheduled based on diagnostic evaluations that determine when to perform service. The monitoring of equipment conditions provides trending data to help anticipate future maintenance needs.
Generators are a costly and complex asset for most organisations to run, so enabling them to operate at maximum effectiveness, for the longest possible amount of time, has a direct impact on the business bottom line.
InVMA is proud to have carried out some specialist IoT projects involving predictive maintenance and visibility for generators. For example, we built a bespoke solution for P and I Generators, a business that provides critical power solutions through a portfolio of installation and commission, testing and maintenance, rental and hire, spare parts and further services.
Our solution comprised a specially configured version of AssetMinder and two gateways, one of which enables data collection from the computers that control P and I’s generator sets, while the other connects to the UPS. AssetMinder stores and processes this information to present a set of alarms and status updates. In turn, P and I can offer its customers remote, real-time analysis of generator and UPS performance, and a highly proactive, predictive approach to maintenance.
Effective asset management has long been a key concern for businesses looking to balance productivity with costeffectiveness, efficiency with innovation. But the IoT era has made it even more crucial – and more complex. To stay ahead in the dynamic, digitally driven world of the IoT, organisations need to redefine asset management and use automation to share the burden.