Multi-Agent Based Information Access Services for Condition Monitoring in Process Automation

1. INDIN’05 3rd International IEEE Conference on Industrial Informatics 10-12 August 2005, Perth, Western Australia Multi-Agent Based Information Access Services for Condition Monitoring in Process Automation Teppo Pirttioja1, Antti Pakonen2, Ilkka Seilonen3, Aarne Halme1, Kari Koskinen3 Helsinki University of Technology, Finland 1Automation Technology Laboratory 3Information and Computer Systems in Automation VTT Technical Research Centre of Finland 2Industrial Systems Perth, Australia

2. Automation and agent technologymotivation • Automation has become an informative intensive application domain, in which • Users need right information, in the right place, in right time, and in the right format to perform well • More and more information is available in various electronic forms, eg. design documents, process and simulation models • Rise of semantically tagged data • There is a need for more powerful design methodologies and techniques to ease up building of monitoring applications, which handles • Dynamically changing situations and process setups • Information that is provided by intelligent field devices • Agent technology may be seen as potential solution, as it is • Argued to perform well in an environment that is distributed and dynamically changing • Used for same kind of problems in other application domains Perth, Australia

3. Current state of the art in process automation information access • For Operators in Control room • Number of separate information systems with different user interfaces (confusing) • Basic alerts and reporting available • Digital diary for notes • But NO easy way to access combined infomation • For Service people • Embedded intelligency for advanced monitoring • Every solution provider has their own system • Information is store in separate systems • Data is gathered but not effectively used Perth, Australia

4. Future needs of process automation information services (user perspective) • Temporal monitoring of some combination of measurements • Easy setup for monitoring a combination of various measured variables • Monitoring of changing values and getting the human attention in abnormal situations (Electronic secretary?) • Access to variables based on process models and simulators • e.g., value combination in startup situation or overview of device performance after service operation • ”Process Automation Google” • Find situations that are interested by the user • Instead of direct access to quantities, browsing via • semantic connections between various aspects of process • Process models, electronic diary • User interface for all process related data • Communication aid for personel between different departments • State of the process tags to measurements in historical databases Perth, Australia

5. From this… AVG(A[0…100]) > (MIN(B[120…150]) + MAX(C[2…15])) ? (History) Databases Automation System Physical instrumentation Perth, Australia

6. …to this SYSTEM OK  Multi Agent System (History) Databases OK Automation System Physical instrumentation Perth, Australia

7. Semantic Automation Vision User goals and actions Understanding the user needs and adapting of services Perth, Australia

8. Agent augmented architecture for Information services in automation • Challenges • Combining different information from different sources • Adapting to changes in information, environment, physical setup • The add-on approach • Enables the use of agent technology with present day automation solutions • No real-time requirements • Provides information services to • human users • external computational systems Perth, Australia

9. Different roles of agents • Client Agent (CA) • User interaction • Information agent (IA) • Searching of information • Accessing, formatting and processing of information • Process agent (PA) • Specialist for some functionally or spatially divided process area • Process hierarchy • Monitors actively • Wrapper agent (WA) • Provides access to legacy information sources • Data formatting • Directory Facilitator (DF) • Yellow pages – services (from FIPA) Perth, Australia

10. Goal oriented-functionality and information processing modules • Manager module controls • Belief-Desires-Intentions based • Adapts to changing situations • Action modules • Connects to process automation • Connection to information systems • Communication between agents • Reasoning (math, simulations, …) • Automation related problem • how to combine symbolic (classical agent/AI viewpoint) and numerical (automation viewpoint) processing effectively Perth, Australia

11. Why the architecture is so complex? Why not to use e.g., SQL server? • Monitoring in automation is a task or a process, it’s not just QUERY of Information! • Some information is ready to be access directly • Other information require triggering events • How human users could define these tasks? • Should be easy to desing, configure and maintain • Framework, architecture etc. is needed • How about the previously presented agent architecture? • How about goals for defining monitoring applications? Perth, Australia

12. Goals as generic building blocks • Agents can decide locally how and when to acquire the required information • Goals as design methodology has already some standards (e.g., Tropos) • Automation related solutions are still missing • Agent can fulfill goal by itself by • Knowing it already • Executing local actions that produce required information • Agent can request information from elsewhere • Partitioning to subgoals • Using agent communication • Terminology is based on generic automation ontology and process related variables have their references in semantic plant model • Not here yet, but are being developed by other projects • Should be publicly available Perth, Australia

13. Goals as generic building blocks Example questions: Is there any PT100 type of temperature measurement oscillating during process startup? Notify if some online measurement differs from the corresponding laboratory measurement? Perth, Australia

14. Demonstration scenario • Real-world test scenario • Industrial setting and actual data • Sensor validation • Comparing uncertain online sensor to exact laboratory measurement • Exact value once in 8hrs • Notifying deviations Perth, Australia

15. E C A B F D Building process monitoring applications • Building the application from separately maintable pieces • Generic automation ontology (A) • Sematic plant model (B) • General monitoring services (C) • Site related services (D) • General reasoning rules (E) • Site related rules (F) Perth, Australia

16. Conclusions • Possibility to use systematic agent tools to design and implement condition monitoring services in automation environment • Provide goal oriented and high level programming for human user • Information processing in automation: No need for hard real time • Few simple tests were implemented and working • Ontologies and semantic web tools may also be used Perth, Australia

17. Future Work • Architecture is quite ok • There is a place for things, but • Operational principles are still much open • Developing of the Semantic Automation • Testing more complex condition and other monitoring tasks • Test Scenarios motivated by real life problems • Industrial settings • Use of Semantic Web tools? • Consentrating more on the user viewpoint • What are the services really needed by the user? • How to model physical environment and information services? Perth, Australia

18. 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 Perth, Australia