Engineering Tools and Methods - imc-aesop.org
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Engineering Tools and Methods IMC-AESOP: ArchitecturE for Service-Oriented Process - Monitoring and Control Seventh Framework Programme (FP7) Theme ICT - Information and Communication Technologies Grant agreement no: 258682 | Project Co-ordinator: Armando Walter Colombo | Schneider Electric Automation GmbH © 2013 The IMC-AESOP consortium. All disclosure and/or reproduction rights reserved CEP Engine Event Sources Weather Feed Energy Sources Other Systems News Feed Data … LINQ Orchestrator Event Based Feedback Example System Closed Opening Open Closing No Car Car Detected Unoccupied Occupied Home Parking System Car Detection Sensor Garage Status Sensor Garage Port Actuator Heating System Road Sensors Home Parking System External Systems Modelling Deployment Support Complete Lifecycle Support System Requirements Virtual Build, Simula4on and valida4on 3D visualisa4on & control logic control code and Interface Build addi4onal Components Orchestra4on Engine Control Device Mechatronic Components Physical Implementa4on Install and Commissioning Integrate machine and 3D visualisa4on for monitoring and maintenance Build a new component in PDE Tool Library of Preexis4ng Components The Process Definition Environment (PDE) toolkit provides engineering tools and methods that have been used in the IMC-AESOP to integrate systems using a component-based approach. The PDE tools shown here are used to support the design and development of a fully distributed system built from components, sub-systems and systems. Utilising SOA based components operating in independent sub-systems (heating, road and home parking systems) that are integrated with external systems (e.g. weather forecasting system) cooperating systems can be developed. Here short range weather forecasts and the home parking system status direct the driver to the most appropriate parking location. The PDE toolkit is used to build components from geometric data (lightweight CAD, kinematic data, and assembly points (link points)), behaviour (using Finite State Machines) and error/ maintenance/ configuration data that are specific to each component. Lightweight 3D models of the systems are assembled using the component link points in a similar fashion to ‘Lego’; as such, effective simulations may be quickly built. The behaviour of the system is created by interlocking the component state machines. This behaviour can be used to validate system behaviour and implement control software, such that there is a 1-1 mapping between the simulated and real control definition. A B C D A B C D Use Case 4: System Definition Complete System Behaviour The Complex Event Processing (CEP) engine, implemented using Microsoft StreamInsight, provides an efficient mechanism to integrate asynchronous events from external systems. The event streams are processed using LINQ queries in order that time-based decisions can be used to influence the behaviour of the orchestrated system. Output from the orchestrated system may be used as an input event stream to provide feedback, and integrated with external event streams to further influence system behaviour. The advantage of CEP is that the queries may be enhanced and extended dynamically, creating an agile system capable of reacting to changing external factors; or used to integrate events from large scale systems to provide a method for building scalable systems. A high level of reuse can be achieved using component based systems with mechatronic devices. More robust systems may be created from libraries of validated components with additional components being created as required. These systems may be commissioned virtually, reducing the risk associated with deployment. Virtual 3D models can be driven directly from the “real” components, as it is the same control system driving both the simulated and real components. These models may be used as a maintenance tool, as part of the PDE toolkit. This will result in any reconfiguration of the physical control system being directly reflected in the simulation. System Model Components Component Models Component Behaviour Interlocks
Transcript of Engineering Tools and Methods - imc-aesop.org
Engineering Tools and Methods
IMC-AESOP: ArchitecturE for Service-Oriented Process - Monitoring and Control Seventh Framework Programme (FP7) Theme ICT - Information and Communication Technologies
Grant agreement no: 258682 | Project Co-ordinator: Armando Walter Colombo | Schneider Electric Automation GmbH © 2013 The IMC-AESOP consortium. All disclosure and/or reproduction rights reserved
CEP Engine
Event Sources
Weather Feed
Energy Sources
Other Systems
News Feed
Data
…
LINQ
Orchestrator Event Based Feedback
Example System
Closed
Opening
Open
Closing
No Car
Car Detected
Unoccupied
Occupied
Home Parking System
Car Detection Sensor
Garage Status Sensor
Garage Port Actuator
Heating System Road Sensors Home Parking System External Systems
Modelling Deployment Support
Complete Lifecycle Support
System Requirements
Virtual Build, Simula4on and valida4on
3D visualisa4on & control logic
control code and Interface
Build addi4onal Components
Orchestra4on Engine
Control Device
Mechatronic Components
Physical Implementa4on
Install and Commissioning
Integrate machine and 3D visualisa4on for monitoring and maintenance Build a new component in
PDE Tool
Library of Pre-‐exis4ng Components
The Process Definition Environment (PDE) toolkit provides engineering tools and methods that have been used in the IMC-AESOP to integrate systems using a component-based approach. The PDE tools shown here are used to support the design and development of a fully distributed system built from components, sub-systems and systems. Utilising SOA based components operating in independent sub-systems (heating, road and home parking systems) that are integrated with external systems (e.g. weather forecasting system) cooperating systems can be developed. Here short range weather forecasts and the home parking system status direct the driver to the most appropriate parking location. The PDE toolkit is used to build components from geometric data (lightweight CAD, kinematic data, and assembly points (link points)), behaviour (using Finite State Machines) and error/ maintenance/ configuration data that are specific to each component. Lightweight 3D models of the systems are assembled using the component link points in a similar fashion to ‘Lego’; as such, effective simulations may be quickly built. The behaviour of the system is created by interlocking the component state machines. This behaviour can be used to validate system behaviour and implement control software, such that there is a 1-1 mapping between the simulated and real control definition.
A
B
C
D
A
B
C
D
Use Case 4: System Definition
Complete System Behaviour
The Complex Event Processing (CEP) engine, implemented using Microsoft StreamInsight, provides an efficient mechanism to integrate asynchronous events from external systems. The event streams are processed using LINQ queries in order that time-based decisions can be used to influence the behaviour of the orchestrated system. Output from the orchestrated system may be used as an input event stream to provide feedback, and integrated with external event streams to further influence system behaviour. The advantage of CEP is that the queries may be enhanced and extended dynamically, creating an agile system capable of reacting to changing external factors; or used to integrate events
from large scale systems to provide a method for building scalable systems.
A high level of reuse can be achieved using component based systems with mechatronic devices. More robust systems may be created from libraries of validated components with additional components being created as required. These systems may be commissioned virtually, reducing the risk associated with deployment. Virtual 3D models can be driven directly from the “real” components, as it is the same control system driving both the simulated and real components. These models may be used as a maintenance tool, as part of the PDE toolkit. This will result in any reconfiguration of the physical control system being directly reflected in the simulation.
System Model
Components
Component Models
Component Behaviour
Inte
rlock
s
