AI-enabled predictive maintenance: keeping the lights on and the wheels of industry turning  


Kontron’s powerful new KISS rackmount server supports increased AI performance requirement


Things have come a long way from preventative-only maintenance strategies which revolve around somewhat rigid, prescriptive servicing schedules. Unfortunately, between service intervals such regimes are usually blind to potential issues which can rapidly turn into faults. Sooner or later these often result in expensive machine damage or even complete plant shutdown. Enter predictive maintenance, in response to industry’s realization that organisations in the hyper-connected IIOT age simply can’t afford to allow this to happen from a cost, efficiency, reputational, or safety perspective. 


Predictive maintenance isn’t exactly a new concept and it’s no longer somewhat exclusive to power plants, energy exploration companies, factory floor production lines and machine manufacturers...but in these areas it’s about to get a whole lot bigger!

The rapid emergence of AI-enabled technologies in predictive maintenance is taking it to a new level. Both in energy and industrial automation, predictive maintenance is becoming more ‘intelligent’ and going far deeper than before in terms of the possibilities of what can be monitored, and how quickly the torrents of data from machines and other equipment can be analysed and acted upon more effectively and efficiently. By using AI-powered monitoring analytics, machine anomalies can often be identified before actual problems or unforeseen events occur. On the factory floor, for example, the connectivity of the IIoT and machine learning is now allowing companies to do highly advanced real-time monitoring of many variables such as heat, vibration, light, sound, and moisture across a broad range of production machinery. 


In power plants there’s a growing focus on AI-enabled predictive maintenance - with powerful applications identifying and addressing equipment anomalies caused by day to day wear and tear. Any number of machines and process parameters can be monitored and maintenance requirements dictated in accordance with the status of individual components. Assessing turbomachinery imbalances, misalignments or stripping, to cracks, loosenings, blade fractures and foundation changes, this is allowing maintenance to be targeted far more precisely on actual component wear and tear, eliminating the need to undergo full maintenance.


By providing an increased understanding of deviations from normal machine behavior, AI-powered predictive maintenance is in some cases already detecting failures many months in advance. Action planning algorithms can be extended or replaced by machine learning to identify parameter drift or emerging component failures by using trend analyses and enabling complex pattern recognition - without any prior knowledge of actual or potential problems. The machines actually learn and improve from their own experience with the help of so called deep-learning neural networks!


Server hardware systems must be more powerful and scalable to run increasingly complex AI-enabled machine learning, monitoring and analysis. 

The consistent implementation of AI-enabled predictive maintenance assumes an immediately accessible, in-depth and real-time awareness of machine condition. In the case of power plants, for instance, this can include a diverse range of machinery, from steam turbosets, gas turbines, pump storage sets, compressor and turbo feed pumps, to wind and tidal turbines. 


Storing, processing and analysing large volumes of IoT machine data is a prerequisite. But they must also support powerful graphics for image processing, be quickly and easily configurable, and highly robust for withstanding the often challenging and harsh operating environments that come with industrial grade predictive maintenance. 


Kontron introduces the KISS 4U V3 SKX high performance 4U Rackmount Server:

The latest generation of industrial rackmount server hardware from Kontron is purpose-designed with the power and scalability necessary to maximize the potential of leading AI predictive maintenance software solutions.  Called the KISS 4U V3 SKX, this high performance 4U Rackmount Server is Kontron’s most powerful KISS solution yet. It features Dual Intel® Xeon® SP Processors and complements the company’s extensive range of industrial KISS rackmount 4U, 2U and 1U servers. It provides the processing power and IoT connectivity needed while also being able to withstand shock, vibration and extreme temperatures up to 45° Celsius. Suitable for 24/7 continuous use out in the field, it’s perfect for deployment in the energy and industrial sectors. Furthermore, like all other Kontron KISS solutions, it is designed on proven industry standard technology and ensures long-term availability in the market, therefore guaranteeing the future-proofed peace of mind and flexibility required by customers. 


Effective AI-enabled predictive maintenance can fully optimize your machinery and equipment assets, eliminating unforeseen and damaging downtime while reducing operating costs. How confident are you about predicting the future? 


For more information about Kontron’s KISS rackmount server solutions please visit Kontron


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