IoT Execution Engine - speed in digitization

Away from rigid, hard to change IT and hardware systems to more influenceability and intelligence in the monitoring and control of systems

With the IoT Execution Engine, plant and sensor data can be collected in real time, modeled in the context of the value-added process and all information and status changes recorded in the Digital Twin can be analyzed and persisted during operation.
  • Processing of IoT signals in real time
  • Creation of context and behavior models
  • Creation of Digital Twin models for plants, products and processes
  • Derivation of improvement measures

IoT Execution Engine - speed in digitization

Away from rigid, hard to change IT and hardware systems to more influenceability and intelligence in the monitoring and control of systems

With the IoT Execution Engine, plant and sensor data can be collected in real time, modeled in the context of the value-added process and all information and status changes recorded in the Digital Twin can be analyzed and persisted during operation.
  • Processing of IoT signals in real time
  • Creation of context and behavior models
  • Creation of Digital Twin models for plants, products and processes
  • Derivation of improvement measures

The IoT Execution Engine enables intelligently networked and autonomous production

The Micro-Service Platform enables the:

  • Modelling of subject-specific digital twins for systems, products and processes by the user
  • Configurative connection of hardware and external signals without coding
  • Persistent storage of all IoT signals in the digital file
  • Visualization of signals and context based on a widget library
  • Analysis, optimization and control of production through AI and machine learning

Context-based

Consistent behaviour model from the process model to the signal level

Integrative

Simple and flexible process, system (e.g. SAP) and device integration (e.g. OPC UA)

Real-time capable

Semantic engine with massively parallel real-time information processing

No Coding

Flexible modeling and configuration via graphical user interfaces

The IoT Execution Engine enables intelligently networked and autonomous production

The Micro-Service Platform enables the:

  • Modelling of subject-specific digital twins for systems, products and processes by the user
  • Configurative connection of hardware and external signals without coding
  • Persistent storage of all IoT signals in the digital file
  • Visualization of signals and context based on a widget library
  • Analysis, optimization and control of production through AI and machine learning

Context-based

Consistent behaviour model from the process model to the signal level

Integrative

Simple and flexible process, system (e.g. SAP) and device integration (e.g. OPC UA)

Real-time capable

Semantic engine with massively parallel real-time information processing

No Coding

Flexible modeling and configuration via graphical user interfaces

Components of the IoT Execution Engine

Twin Modeler
Modeling and
configuration of the
Digital Twin models

Twin Execution
Runtime environment
and real-time control
of events

Twin Digital File
Real-time persistence of all parameters in context and controlled access to them

Twin Live Dashboard
Visualization for the end user and intervention in the execution level

Twin Validation
Validation of process logic,
process descriptions, consistency
check

Twin Device Connector
Flexible connection and intelligent data retrieval of plant protocols (OPC UA, S7)

Twin Device Builder
Configuration of the device connection and automatic recognition of new parameters

Twin Control Center
Sanity Twin Infrastructure, Service Discovery, Availability, runtime-environment

Twin AI
Advances Analytics in the context of the Digital Twin (Predictive-, Prescriptive-Analytics)
e.g. Machine Learning Analysis of machine parameters in relation to use case

Standard features of the IoT Execution Engine

Flexible Machine Connection and Data Retrieval

Learn more

Reading of plant parameters from a PLC without coding via standard protocols, such as OPC-UA, MQTT, S7, TCP Client/Server, REST

Messages, Alarms and Anomaly Detection

Learn more

Messages and recommendations for action are generated automatically and are available to the user filterable according to various criteria

Flexible Operation,
Reliability

Learn more

Availability of all operational data to protect your sensitive data for cloud-native, hybrid or on-premise operation

Integration Layer for the Shopfloor

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High-performance integration layer for connecting all production systems, devices, actuators, sensors & networking the IT landscape (e.g. ERP, MES)

Persistence of Data in the Context of Value Creation

Learn more

Persistent and historized storage of all signals and information about state changes including display for selected time in the digital file

User-specific
Visualization

Learn more

Flexible configuration of user-specific dashboards via standardized widget library on different (mobile) devices

Modelling of
Digital Twins

Learn more

Rapid implementation of subject-specific behavioral models through the use of predefined modules and ready-made ontological models

Intelligent, AI-based Analyses

Learn more

Integration of Data Analytics Services for pattern, threshold, correlation detection & for the application of Supervised & Unsupervised Machine Learning

Condition Monitoring &
Quality Monitoring

Learn more

User get a view of production, process & product configured for their specific role with necessary calculations & information

Standard features of the IoT Execution Engine

Flexible Machine Connection and Data Retrieval

Learn more

Reading of plant parameters from a PLC without coding via standard protocols, such as OPC-UA, MQTT, S7, TCP Client/Server, REST

Messages, Alarms and Anomaly Detection

Learn more

Messages and recommendations for action are generated automatically and are available to the user filterable according to various criteria

Flexible Operation,
Reliability

Learn more

Availability of all operational data to protect your sensitive data for cloud-native, hybrid or on-premise operation

Integration Layer for the Shopfloor

Learn more

High-performance integration layer for connecting all production systems, devices, actuators, sensors & networking the IT landscape (e.g. ERP, MES)

Persistence of Data in the Context of Value Creation

Learn more

Persistent and historized storage of all signals and information about state changes including display for selected time in the digital file

User-specific
Visualization

Learn more

Flexible configuration of user-specific dashboards via standardized widget library on different (mobile) devices

Modelling of
Digital Twins

Learn more

Rapid implementation of subject-specific behavioral models through the use of predefined modules and ready-made ontological models

Intelligent, AI-based Analyses

Learn more

Integration of Data Analytics Services for pattern, threshold, correlation detection & for the application of Supervised & Unsupervised Machine Learning

Condition Monitoring &
Quality Monitoring

Learn more

User get a view of production, process & product configured for their specific role with necessary calculations & information

The key to implementing Industry 4.0 and IIoT

1
  • Description of the process and behavioral logic of the system by modeling the functional relationships including all dependencies, states and properties
2
  • Configurative connection of hardware and networking with existing IT infrastructure (e.g. ERP, MES)
  • Capture, storage and processing of data streams in real time
3
  • Providing the context for machine learning
  • Interactive dashboards for visualization and advanced analytics
4
  • Visualization of fault messages, anomalies and trends through Advanced Analytics
  • Worker guidance through recommendations for action in case of deviations/anomalies
5
  • Visualization of fault messages, anomalies and trends through Advanced Analytics
  • Worker guidance through recommendations for action in case of deviations/anomalies
1

Model & Contextualize
2

Connect & Collect
3

Learn & Analyze
4

Alert & Advice
5

Decide & Optimize

The key to implementing Industry 4.0 and IIoT

1
  • Description of the process and behavioral logic of the system by modeling the functional relationships including all dependencies, states and properties
2
  • Configurative connection of hardware and networking with existing IT infrastructure (e.g. ERP, MES)
  • Capture, storage and processing of data streams in real time
3
  • Providing the context for machine learning
  • Interactive dashboards for visualization and advanced analytics
4
  • Visualization of fault messages, anomalies and trends through Advanced Analytics
  • Worker guidance through recommendations for action in case of deviations/anomalies
5
  • Visualization of fault messages, anomalies and trends through Advanced Analytics
  • Worker guidance through recommendations for action in case of deviations/anomalies
1

Model & Contextualize
2

Connect & Collect
3

Learn & Analyze
4

Alert & Advice
5

Decide & Optimize

Get to know our solutions

Assisted Planning

Planning & simulation …

Assisted Production

Operation & Optimization …

Data Analytics

Predictive and preventive analyses …

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