Benefit from data analytics for condition monitoring and predictive maintenance

  • Automate condition monitoring
  • Offer additional services with predictive maintenance
  • Analyze whole fleets and environments

Turn Big Data into Smart Data

Machines and devices are quick to supply vast amounts of data, which is a good reason for using automated cleansing and consolidation processes for example. Elements for IoT incorporates open source tools such as Jupyter Notebooks for this purpose and provides support for efficient analysis and publishing processes.

Directly from the IoT dashboard to big data analysis with Jupyter Notebook

Monitor your machines and assets

The cleansing and pre-compacting of the field data is followed by a search for relevant patterns – for example in the context of predictive maintenance – and analyses based on known quantities and events (condition monitoring). If an incident occurs, the responsible services are automatically notified. Use these chains of events with Elements for IoT and share these processes with your customer and user community.

Gain an overview with dashboards

Customers, fleets, devices, time intervals, data streams, events, measures and much more: Companies that gain the best overview are the companies that use principles such as management by exception and drill-down with customized dashboards. For example, for geo-monitoring and geo-fencing in the context of fleet management.

Easily configure the Elements for IoT dashboard using predefined widgets and maintain an overview when managing devices in the field

Data is the new oil!

Modern analysis methods are a decisive success factor for service-oriented business models around IoT and industry 4.0. A new white paper explains the state of the art and shows what the latest methods can achieve in practice. Our white paper Data Science & Analytics provides an overview of the development and perspectives of a key science.

Download White Paper

Related Elements

Designing successful products in the closed loop of operation and further development

Analyze and evaluate field data for targeted product improvements

Involve customer communities in the ongoing optimization of products

Use best practices such as ticket systems and quality issues for integration into the development process

Use the virtual representation of devices in the field for product and process improvements

Establish the digital twin as a database for all IoT business processes

Create complete profiles across the entire lifecycle of your products and map changes in the field   

Use the digital twin as a basis for creating added value for your customers

Further Information

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