1. DIS 2006 15.6.2006Helsinki University of Technology Multi-Agent System Enhanced Supervision of Process Automation Teppo Pirttioja 1, Antti Pakonen 2, Ilkka Seilonen 3, Aarne Halme 1, Kari Koskinen 3 Helsinki University of Technology, Finland 1 Automation Technology Laboratory 3 Information and Computer Systems in Automation 2 VTT Technical Research Centre of Finland DIS 2006 IEEE 2006 Workshop on Distributed Intelligent Systems June 15 -16, Diplomat Hotel Prague, Czech Republic

2. DIS 2006 15.6.2006Helsinki University of Technology Agenda  Background and motivation Process automation and user needs Available technologies  Architecture Multi agent system based architecture Roles of agents Internals of an agent  Test scenario  Conclusions and future work

3. DIS 2006 15.6.2006Helsinki University of Technology Background and Motivation: process automation  Process Automation Factories are running 24/7 and as effectively as possible General trend: Less personnel and bigger and more complex factories, so there is more to supervise Ordinary IT solutions are used, because its cheap and it works  Results often data systems with mixed user interfaces Information is measured and gathered but not easily available to users  User need easy and efficient access to all data Users need right information, in the right place, in right time, and in right level of abstraction and easily! It’s not about tools and technology, it’s also the way people are used to operate

4. DIS 2006 15.6.2006Helsinki University of Technology Background and Motivation: user needs within process automation  System within process automation is running mainly on it’s own User intervention mainly needed when there are problems in the system Users need to get information when critical changes happen Changes may result from input material variations, devices malfunctions, etc...  Various user profiles of supervision Process operators; physical process, measurements,... Servicemen; device conditions for drives, valves,... System developers; performance issues, control optimization,... Business managers; orders, financial aspects,...  What kind of concrete supervision tools are needed? Easy browsing and navigating trough all process related data Search engine to access data in separate and heterogeneous systems Find situations and data combinations that are interested by the user Easy setup for monitoring a combination of various measured variables

5. DIS 2006 15.6.2006Helsinki University of Technology Background and Motivation: What technologies might be useful?  Integration problem Semantic Web tools makes more and more information available in machine understandable form May make the integration of separate systems easier There are no ontologies about factories available yet and there is no ready and standardized solution of how to combine number of services to build up more complicated services (orchestration)  Supervision problem Automate routine supervision as much as possible Let people be just decision-makers for real problems that are not possible to automate Proactive agents are argued to be suitable for active supervision

6. DIS 2006 15.6.2006Helsinki University of Technology Architecture: agents as information mediators in Semantic Automation Proactive operation of agents System integration with semantic web tools

7. DIS 2006 15.6.2006Helsinki University of Technology Architecture: agents operating in various roles IA PA DF CA PA FA AA CA DA IA CA Continuous data analyzing Various events from wrapper agents CA = Client Agent, DA = Diary Agent IA = Information Agent, FA = Fault Agent AA = Alarm Agent, DF = Directory Facilitator IA Information processing User Interface

8. DIS 2006 15.6.2006Helsinki University of Technology Architecture: internal structure of an agent  User configurable manager module Uses data processing modules for actual information processing Adapts to changing situations with context depended operation (Belief-Desires-Intentions)  Data processing modules Communication with other agents Data I/O connections  Connecion directly to process automation measurements  Connection to other databases Data processing  Reasoning and logic  Mathematic processing  Data storage modules Temporal storage of data

9. DIS 2006 15.6.2006Helsinki University of Technology User configurability supervision of process  How human users could define these tasks? Should be easy to desing, configure and maintain Framework, architecture etc. is needed  This solution should be as flexible as SQL servers are in data management area  But SQL servers as such can’t be used because Monitoring in automation is a task or a process, it’s not just QUERY ! Some information is ready to be access directly, but quite often we need to wait for triggering events Data is stored in mixed formats (semantics)  What if we use the previously presented agent architecture? Let see how it could work in typical process related monitoring task

10. DIS 2006 15.6.2006Helsinki University of Technology Temporal monitoring scenario Process related problem explained  Problem: There are slowly drifting measurements in the processes Sensors that become dirty, etc.  Alarms provided by process automation system are not helping, because Limits are often set too wide to minimize false alarms Limits are set normally to check just one value at the time Control loops are compensating the error  User need a tool to monitor a combination of process quantities This kind of monitoring would be especially useful temporally e.g., startups and shutdowns of a process, or when there is a change in product  ”for next 15 minutes make sure that pump is running and level in the tank is rising”  Solution proposal: fault may be found by gross checking process quantities User defines a set of constraints that agents are then set to monitor e.g., check that Measurement1 is always more than Measurement2

11. DIS 2006 15.6.2006Helsinki University of Technology Temporal monitoring scenario Operation of agents  CA = Clint Agent Provides user interface and lets user define constraints  IA = Information Agent Performs the monitoring task Divides the set of constraints based on the initial values Delegates monitoring to peers Reports to the user when needed  PA1 = Process Agent 1 Knows Meas1 value  PA2 = Process Agent 2 Knows Meas2 value  DF = Directory Facilitator Yellow page services Knows what agent is providing what information

12. DIS 2006 15.6.2006Helsinki University of Technology Temporal monitoring scenario Active monitoring of agents  Normally the situation is OK in the beginning so changes in measured values need to be monitored  Process agents monitor their own values and report when their partial constraints are broken  When partial constraints are broken the Information agent tests the set of constraints again If constraints are ok the monitoring continues with updated values If some constraint of the overall set of constraints is broken, then the user is informed

13. DIS 2006 15.6.2006Helsinki University of Technology Conclusions and Future Work  Users within process automation need powerful tools to search, access, and supervise information produced in all around the factory And this system should be easy to setup, configure, and maintain  Enabling technologies seems to be available Ontologies and semantic web tools “solves” interoperability issues Agents for proactive operation - monitoring on behalf of human user  Combining architecture - Semantic Automation  Future Work Testing on more complex monitoring tasks Test Scenarios motivated by real life problems and situated in real factories Use semantic web tools to provide user configurability  e.g., SPARQL (Query language for RDF/OWL from W3C)  OWL for plant models, etc. Internal operational principles are still much open  Consentrating more on the user viewpoint What services are really needed by the user? How user would like to configure and use various services?

14. DIS 2006 15.6.2006Helsinki University of Technology That’s it Questions Thanks to Project group:www.automation.hut.fi/projects/proage/ Funding:National Technology Agency of Finland, Metso Automation, UPM Kymmene, Teleca