A new predictive maintenance service from ABB is set to improve the reliability of critical drives used in demanding environments. ABB AbilityTM Predictive Maintenance for drives harnesses the power of cloud computing, machine learning and ABB’s expertise, together with a remote monitoring system.
Predictive maintenance is a widely used term in connection with mechanical equipment such as electric motors, where it entails an understanding of the condition of components such as bearings, and the impact of vibration.
Predictive maintenance has never accurately been applied to solid state electronic devices such as variable speed drives (VSDs). Even though VSDs have been packed with digital sensors for the past 20 years, understanding how to use the data available and what to forecast has proved a challenge.
Static electronic converters, such as VSDs, are packed with discrete components like capacitors and insulated gate bipolar transistors (IGBTs). It is virtually impossible to predict accurately when such devices are likely to fail because, unlike with the bearings in an electric motor, there is no way of visually inspecting the components.
Until now, predictive maintenance for drives was limited to considering only a handful of parameters and knowing the drive’s history, combined with calculations based on probability theory. This was coupled with physical site visits to gather fault information and manually establish what might happen to the drive. Using data alone, it is easy to miss potential failure modes that can only be picked up by the
eyes and ears of the operators.
A new approach
Now, ABB has combined new technology such as cloud computing, advanced algorithms and machine learning with its engineering expertise to create the first predictive maintenance service for VSDs used in critical applications.
ABB Ability Predictive Maintenance for drives enables users to maximise operational efficiency through targeted maintenance for critical drive applications. The latest machine learning algorithms and analytics make it possible to estimate drive component lifetimes based on duty cycle and stress monitoring.
The use of machine learning is crucial because it allows multiple parameters to be considered simultaneously.
Users can now have real-time visualisation of the future status of the drive, enabling its health to be more accurately, and cost efficiently, predicted. This approach allows precise maintenance times and actions to be proposed to reduce the risk of failure. The slightest anomalies in the process can be found and reported. More reliable availability of drives can translate into improved performance.
Because of the complexity of a drive, ABB needs to aggregate data progressively from specific sections. This starts with the power stage, because this is the most valuable and difficult to exchange if it fails.
It is important to realise that the predictive maintenance service is still only a first step. Machine learning is a gradual process. Just as it would take a human years to become expert, machine learning will provide progressively more accurate results over a period of years. For predictive maintenance to be truly effective, knowledge needs to be accrued over time from many drives operating in different applications and ABBs huge global installed base, as the world’s leading VSD supplier, will contribute to this. Future iterations of ABB’s predictive maintenance service will be even more powerful.
Even so early, there have already been positive outcomes in several trials worldwide. ABB has been able to anticipate and prevent failures of highly critical applications. It has advised clients on how to optimise drive usage and tailor maintenance to reduce risks to the continuity of their operations, saving hundreds of thousands of euros in repairs and lost production.
With predictive maintenance ABB is focusing on large power drives in heavy industries, where the impact of a malfunction on a critical application or process can be damaging and hugely costly. This also translates to other high demand applications such as storm pump drives in the water industry.
ABB is interested in locating drives controlling large motors in demanding processes. So far there are six pilot installations worldwide, each chosen because of their technical, harsh and demanding applications. The chosen applications include a mine hoist and metals industry processes. However, ABB Ability Predictive Maintenance for drives is now launched and available to end-users as part of a service support package.
ABB (ABBN: SIX Swiss Ex) is a pioneering technology leader in electrification products, robotics and motion, industrial automation and power grids, serving customers in utilities, industry and transport & infrastructure globally. Continuing a history of innovation spanning more than 130 years, ABB today is writing the future of industrial digitalization with two clear value propositions: bringing electricity from any power plant to any plug and automating industries from natural resources to finished products. As title partner of Formula E, the fully electric international FIA motorsport class, ABB is pushing the boundaries of e-mobility to contribute to a sustainable future. ABB operates in more than 100 countries with about 135,000 employees. www.abb.com