Using the latest IoT and AI technologies, asset-intensive businesses can take the next leap in developing their maintenance approach — moving from corrective and preventive to predictive and prescriptive maintenance. The value is significant. Maintenance activities are not performed too late, hence increasing the availability of assets. But not too early either, thus avoiding unnecessary maintenance costs. Identified anomalies in the process are also valuable insights for the operation for process improvements. Simply put: the right action at the right time.
Nexer solutions are based on one of the following approaches, or in a combination thereof:
Based on known events, e.g. a breakdown of an asset, sensor data can be analysed to build a model. The model can detect when the same failure is about to happen again and give a warning or initiate a workorder in Maximo. Nexer solutions are based on technologies from IBM or Microsoft and are combined with our extensive know-how in maintenance and data analytics.
A pre-made industrialised solution analyses a vast amount of data, often from several thousand sensors, and automatically identifies correlations between signals. Thus, to a high degree it builds the model without the need of manual analytical work. The model then automatically detects anomalies that can be used to optimise a process or initiate a maintenance workorder in Maximo. Nexer offers several unsupervised machine learning solutions called Caverion Intelligence. These have proven results in the Nordic countries — for example, a power plant realised savings of 2,5 MEUR a year in avoided unplanned downtime. But also, a wide range of solutions included in the Maximo Application Suite.
Nexer Predictive Maintenance is fully integrated with Maximo Enterprise Asset Management and Asset Lifecycle Management in the Nexer Asset Management 360 Cloud Suite.
Öresundsbron
Boliden
Sandvik
HITACHI (former ABB Transformers)
Göteborg Energi
HK Scan
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