Digital Transformation

Explosive growth in connected smart machines is one of the main drivers for enterprise and industrial adoption for IoT. In turn, it drives the demand for advanced IoT platforms and solutions to handle connectivity and data processing in real time for a large number of machines, and an extensive amount of data that is generated by these machines.

The solutions are required to bring more intelligence to the network and solve complex scenarios autonomously. Data is used to optimize utilization, reduce downtime, improve Quality of the network and to reduce the Opex and Capex while adding the capability for increased revenue.

“Interactor” brings the most efficient and user-friendly environment for working with all required functionalities, enabling an end-to-end solution for any complex Industrial IoT scenario. Interactor provides a configuration-based development environment with technology building blocks that makes it fast and easy to create and manage any application.

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USE CASES

Predictive Maintenance & Enhanced Field Service

Integration to industrial machinery to collect data in real-time

  • Streaming data from multiple sources
  • Data can be in any format, standard format or custom. Interactor handles it
  • Data is filtered and sorted per machine and/or machine type
    Ex. type of data: pressure, speed, vibration, flow, operational state, etc.
  • Data is modeled for further processing

Data Normalization and Aggregation for predictive maintenance and field service

Ex. Speed and Vibration is correlated to a performance identifier
 

Apply solution logic and applicable policy and rules

Ex. Correlate real-time performance data with historical data (readable from database)

  • The policy could be a defined threshold (based on historical data) for expected variance (range) in the value of current performance data.
  • Rule ex. If the current value is outside the expected range, notification needs to be prepared, check the system, and/or an indication created for the technician to schedule a visit or an indication for additional capacity need.

Application and Data Output

  • Realtime and Historical Data (expected range) for each machine or machine type can be sent to a dashboard for visualization. Also stored in the database.
  • Data is sent to other services (warranty service, ..)
  • APIs are created for use by any application/systems (OSS/BSS).
Analytics, Predictive Analytics

Integration to industrial machinery to collect data in real-time

  • Streaming data from multiple sources
  • Data can be in any format, standard format or custom. Interactor handles it
  • Data is filtered and sorted per equipment and/or equipment type
    Ex. type of data: electricity, gas, heat and water usage
  • Data is modeled for further processing

Data Normalization and Aggregation for predictive maintenance and field service

Ex. Filter and normalize the energy data with internal and external temp, humidity, CO2

Apply solution logic and applicable policy and rules

Ex. Correlate real-time usage data with historical data (readable from database)

  • The policy could be a comparison of normalized usage data with a set threshold (based on historical data, and/or set by the user)
  • Rule and solution logic option is to, for ex. apply the policy and link energy data with industrial processes and production units for energy generation, storage and consumption to achieve optimized energy usage

Application and Data Output

  • Output data to GUI, and/or relevant notification to a user for the optimization need, or if the automated process, apply it to the equipment
    Ex. Turn off lights or heating system if no one is present in location for a certain period of time
  • APIs are created for use by any application/systems (OSS/BSS)
Asset Tracking, Traceability, Supply Chain Efficiency

Integration to industrial machinery to collect data in real-time

  • Streaming data from multiple sources
  • Data can be in any format, standard format or custom. Interactor handles it
  • Data is filtered and sorted per asset/device/sensor
    Ex. type of data: inventory and movement data
  • Data is modeled for further processing

Data Normalization and Aggregation for predictive maintenance and field service

Ex. Filter and normalize the data Ex. correlate asset specific data with order type, order location, shipping info, external data like weather,…and normalize it to a few scenarios for further analysis and business insight

Data Normalization and Aggregation for predictive maintenance and field service

Ex. Filter and normalize the data Ex. correlate asset specific data with order type, order location, shipping info, external data like weather,…and normalize it to a few scenarios for further analysis and business insight
 
Apply solution logic and applicable policy and rules
Apply logic for data flows into a central analytics engine from all stakeholders such as vendors, retailers, customers, and create insight on ex. demand forecasting, available supplier capacity or any other data/ intelligence enabling optimized supply chain
Application and Data Output
  • Output data to GUI, and/or relevant notification to a user for asset location, or supply chain efficiency need
  • APIs are created for use by any application/systems (OSS/BSS)