EKE-Electronics Ltd. acquires software company specialised in predictive maintenance
Posted: 7 March 2019 | Global Railway Review | No comments yet
Through this acquisition, EKE-Electronics expands its range of offerings to become a global supplier of remote condition monitoring systems for railway applications.
EKE-Electronics Ltd. has bought Humaware, a UK firm specialising in predictive condition monitoring analytics.
EKE-Electronics is a Finnish supplier of intelligent train automation and onboard data systems, and has developed a cloud-based remote diagnostic software for train fleets – Smartvision™ – that is deployed in projects in Singapore, London and Australia.
As a result of this acquisition, the company’s range of services now extends to the analysis of signals and sensor data collected from trains by means of the extremely accurate and reliable predictive analytics algorithms developed by Humaware. Unforeseen failures in rail traffic result in additional maintenance costs, delays and reduced passenger satisfaction. Humaware’s advanced data-driven algorithms and anomaly-detection techniques provide an improved approach to obtain remote condition monitoring benefits. Fixed thresholds are replaced with an adaptive threshold to detect changes in remote condition monitoring data earlier than fixed threshold methods. This earlier detection provides the opportunity to switch from costly schedule-based maintenance to a dynamic maintenance programme based on the actual condition of the trains. The pooling of expertise will provide a predictive maintenance capability that will improve reliability, cost-efficiency and passenger comfort.
Humaware possesses extensive experience in data-driven remote condition monitoring. Their predictive algorithms were originally developed for monitoring the condition of helicopters; highly complex machines where the characteristics of remote condition monitoring data is affected by environment, operator and operational mode. The algorithms were rigorously validated by the U.S. Army (AMRDEC), among others. Over the years, the software has been transferred into rail and developed further in a number of RSSB/Innovate UK funded research projects working with Network Rail and London Underground.
EKE-Electronics will utilise Humaware’s algorithms, combined with Smartvision™ software, for rolling stock applications including trains, metros and trams to provide real-time actionable information about the condition of rolling stock so that maintenance intervention is undertaken at the optimal time.
Intelligent maintenance solutions are in great demand in the railway industry because of the substantial benefits they offer. The acquisition of Humaware makes EKE-Electronics a global forerunner in predictive condition monitoring.
“With Humaware’s unique software, we’re able to offer a comprehensive solution for data collection and analytics, as well as for planning a dynamic maintenance programme that is of interest to rail operators all over the world,” said Karl Lönngren, who is responsible for EKE-Electronics’ condition monitoring business.
“Intelligent maintenance – or the utilisation of predictive maintenance and analytics to improve efficiency in maintenance operations and the operational reliability of the rolling stock – is a key element of VR Maintenance Ltd’s strategy,” said Mikko Alanko, Director of the company’s maintenance systems and analytics. According to Alanko, VR has achieved major benefits through predictive maintenance and is constantly looking for new opportunities and partners to extend condition monitoring to all the rolling stock serviced by the company.
“From our point of view, EKE-Electronics’ strengths include its independence from train manufacturers and excellent relations with component suppliers, which gives access to the data generated by them. Personally, I’m pleased with this acquisition as it expands EKE-Electronics’ range of expertise in this branch of high technology,” he added.
Related topics
Mergers & Acquisitions, Regulation & Legislation, Rolling Stock Maintenance