PROAGE PROAGE – PROSESSIAUTOMAATION AGENTTIPOHJAISET INFORMAATIOPALVELUT Agent-Based Information Services for Process Automation Semantic Web Research seminar / Metso Automation Tampere

PROAGE Agenda  Motivation and background  Agent Automation Controlling agents  MUKAUTUVA Information agents  PROAGE Agent services for process automation  Conclusions and discussion

PROAGE Process Automation domain  More and more measured and gathered information is stored to different databases  More intelligent field devices available  Distribution of control to subprocess level  Partial diagnostics solutions available  More information available in electronic form; design documents and others

PROAGE Agent Automation: Agenttipohjainen automaatioratkaisu  Research –  Agents and Automation? Process Automation especially Fault tolerant control Abnormal situation handling Potential process automation functions?  Used technology Generic agent technology FIPA standard; negotiations Robot society research, physical agents

PROAGE Agent Automation: A Concept of an Agent- Augmented Process Automation System  Agent-Augmented Real-time problem Supervisory control  Subprocess idea Agents are responsible of certain physical area of the process

PROAGE Agent Automation: Control tests with Laboratory test environment  Real demo process Temperature control & circulation of water Volume 700 L  OPC connection to PAS  Qualitative process models used  Initial ideas for information access Idea: more than OPC “What is the current state of the device?” “When was the device’s last maintenance check?” User agent

PROAGE MUKAUTUVA: Automaatiosovellusten mukautumisperiaatteet ja –mekanismit  Research –  Controlling Agents and Information Agents  Demonstration scenarios: a real industrial process

PROAGE MUKAUTUVA: Information agents  Challenges Combining different information from different sources Adapting to changes in information, environment, physical setup  Information agents used to address similar problems in other application domains  The add-on approach from AGENT AUTOMATION project new features can be tested on top of current PAS

PROAGE MUKAUTUVA: Architecture and the role of agents  Society of hierarchically aligned agents operating in different roles  Client Agent (CA) User interaction  Information agent (IA) Information access and procesessing. Also active monitoring  Process agent (PA) Specialist for some process area, functional or spatial  Wrapper agent (WA) Provides access to legacy information sources  Directory Facilitator (DF) Yellow pages - services

PROAGE MUKAUTUVA: Demo I – Combining info 12/2003  Problem : Combining measurement information from systems with different data format, semantics and query language  Implementation : Wrapper agents and a common data format Directory service (DF) Distributed query  Results : Basic agent communication & planning defined

PROAGE MUKAUTUVA: Demo II – Monitoring 6/2004  Problem : Active monitoring of sensors that are vulnerable to defects Comparing manual laboratory measurements to online data  Implementation : Task distribution Data polling & processing at the low level Subscription protocol Offline, with actual process data  Results : Generic monitoring functions, easily configured to a specific task Problems in combining different languages: FIPA-SL/OWL/RDQL

PROAGE MUKAUTUVA: Demo III – State classification 12/2004  Problem : Classification of the operational state of a process  Implementation : Distributed classification Several active agents Lower level: state based on process measurements Higher level: state based on lower level states  Results : Detection of an actual state transition from actual process data In general: all but clear

PROAGE MUKAUTUVA: Internal design of agents  Internally: separate modules for different information processing tasks Control: a planning manager module Action: specialized (e.g. math) information processing modules Plans: a high-level information processing goal is divided to atomic tasks

PROAGE Ontology-based information processing  Motivation Combining different information from different sources A computer-processable world / process model  Implementation: OWL Our ontology is limited & exemplar Measurements, devices, states… Concepts derived from standards of the domain

PROAGE Conclusions: control  Real-time control not yet feasible  Possibilities in supervisory control Ecxeption handling Sequential control For low-level control: PID etc...  Complex problems require agent- based methods

PROAGE Conclusions: information agents  No real-time requirements  Refined information processing on top of current systems: an easy & safe application domain?  MUKAUTUVA: Overall architecture seems OK  Internal design needs a little work Goal-oriented operation seems reasonable Math/logic processing??

PROAGE Conclusions: ontologies  There will be no ”universal automation ontology” A combination of ontologies from different viewpoints Current domain references are few & from narrow viewpoints Concept modelling state-of-the-art: XML Schema  Our focus: investigating the mechanisms of ontology-based information processing

PROAGE From MUKAUTUVA to PROAGE  MUKAUTUVA demos: general, more or less basic functionalities State classification still somewhat unclear  How about the process automation services? Detection of slowly developing faults State-based alarm filtering Validation of measurement data Proactive condition monitoring of devices

PROAGE  Agent-Based Information Services for Process Automation  HUT Automation Technology lab HUT Information Technology in Automation lab VTT Industrial Systems Metso Automation, UPM, Teleca

PROAGE PROAGE : Motivation  User interfaces provide the operator with a lot of process data but no refined knowledge about the process state and performance.  Combining different existing monitoring and diagnostics solutions is difficult.  Process models or simulators cannot be efficiently utilized in condition monitoring, if the state of the process is not known.

PROAGE PROAGE : The Goal  Project goal is to design intelligent and cooperative condition monitoring and maintenance services for e.g. process operators.  These services are based on information agent and Semantic Web technologies.  Idea: Information agents operate as a team that extends the state awareness of human users.

PROAGE PROAGE : Work Packages  Defining the information agent services Services relevant to industry Services suitable to agent-based approach  Further developing the information agent system architecture  Demonstrating the agent services Goal: online, on-site  Outlining a roadmap for adoption of agent-based solutions in automation

PROAGE PROAGE : Potential ideas for services  State-aware, model-based condition monitoring  Adaption of fault diagnostics to exceptional operational states ”this is not a problem, since we are shutting down”  Metadata labelling of measurement history  More abstract, refined information to user interfaces From direct variables to calculated variables

PROAGE PROAGE Semantic Automation

PROAGE discussion / open questions / …  Our focus: investigating the mechanisms of ontology-based information processing Creating suitable ontologies for the domain a substantial challenge ”Someone else will do it”  Our challenges No W3C specification yet for:  A query language  Logic & math on top of OWL How to combine goal-based planning with ontology-based information processing

PROAGE discussion / open questions / …  What are the actual needs in process monitoring? Which of these can benefit from agent- based approach?