A multi-agent system to facilitate component-based process modeling and design

Component-based software technology and software interfaces standardization initiatives, such as CAPE–OPEN, have made it possible to model chemical processes and to perform model-based engineering tasks by combining components of process modeling software from different sources, hence providing the potential of exploiting the “best of breed” offered by the CAPE community. In this context, software component libraries, possibly located on a local computer, on the intranet of an organization, or on the Internet, have to be searched to find the most suitable components for a particular engineering task at hand to be integrated into the engineers’ computing environment. This paper proposes to address this issue through a multi-agent software system which facilitates the engineers to find and to integrate software components and aims at reducing the engineers’ effort to the minimum. Within this system, a directory facilitator serves as the “yellow pages” such that an undetermined set of software component libraries located anywhere may be registered with the system. A matchmaker is used to match the specification of a desired software component with the potential candidates in the relevant libraries. The integration of a matching component into the computing environment is handled by an integration manager. A prototype of such a system, called COGents, has been developed employing an existing multi-agent platform. The ontology OntoCAPE defines the chemical engineering and modeling concepts required for specifying desired software components and for characterizing existing ones. OntoCAPE also provides a shared semantic basis for communication between the software agents. Details of the implementation of COGents are presented and the re-usability of the parts of the COGents system is discussed. Three successful demonstrative applications of COGents are reported, each dealing with different types of tasks, specifically flowsheeting, detailed modeling and process design.

[1]  Ignacio E. Grossmann,et al.  Mathematical programming approaches to the synthesis of chemical process systems , 1999 .

[2]  Ignacio E. Grossmann,et al.  Systematic Methods of Chemical Process Design , 1997 .

[3]  Wolfgang Marquardt,et al.  OntoCAPE - A large-scale ontology for chemical process engineering , 2007, Eng. Appl. Artif. Intell..

[4]  B. L. Braunschweig,et al.  Process Modeling: The Promise of Open Software Architectures , 2000 .

[5]  Michael R. Genesereth,et al.  Software agents , 1994, CACM.

[6]  Eric S. Fraga,et al.  Enhancing automated process design with cognitive agents, distributed software components and web repositories , 2007 .

[7]  E. Gallopoulos,et al.  Problem-solving Environments For Computational Science , 1997, IEEE Computational Science and Engineering.

[8]  Eric S. Fraga The automated synthesis of complex reaction/separation processes using dynamic programming , 1996 .

[9]  Gabriela P. Henning,et al.  MODEL.LA. A modeling language for process engineering—I. The formal framework , 1990 .

[10]  Kendall Scott,et al.  UML distilled - a brief guide to the Standard Object Modeling Language (2. ed.) , 2000, notThenot Addison-Wesley object technology series.

[11]  Jean-Pierre Briot,et al.  From Active Objects to Autonomous Agents , 1998, IEEE Concurr..

[12]  Pierre Sens,et al.  DARX - a framework for the fault-tolerant support of agent software , 2003, 14th International Symposium on Software Reliability Engineering, 2003. ISSRE 2003..

[13]  Arthur W. Westerberg,et al.  Building a chemical process design system within soar—2. Learning issues , 1995 .

[14]  Matthias Jarke,et al.  An ontology-based approach to knowledge management in design processes , 2008, Comput. Chem. Eng..

[15]  Thomas R. Gruber,et al.  A translation approach to portable ontology specifications , 1993, Knowl. Acquis..

[16]  Arthur W. Westerberg,et al.  Multiperiod design of azeotropic separation systems. I. An agent based solution , 2001 .

[17]  Ian T. Cameron,et al.  A formal representation of assumptions in process modelling , 2001 .

[18]  R.W.H. Sargent,et al.  Computer generation of process models , 1996 .

[19]  Wolfgang Marquardt,et al.  A formal representation of process model equations , 1995 .

[20]  James M. Douglas,et al.  Conceptual Design of Chemical Processes , 1988 .

[21]  Wolfgang Marquardt,et al.  Towards integrated information models for data and documents , 2004, Comput. Chem. Eng..

[22]  Timothy W. Finin,et al.  KQML as an agent communication language , 1994, CIKM '94.

[23]  Wolfgang Marquardt,et al.  Computer-aided process modeling with MODKIT , 2001 .

[24]  En Sup Yoon,et al.  A modeling and simulation study on a naphtha reforming unit with a catalyst circulation and regeneration system , 1997 .

[25]  Nicholas R. Jennings,et al.  Intelligent agents: theory and practice , 1995, The Knowledge Engineering Review.

[26]  Steinar Hauan,et al.  Toward agent-based process systems engineering: proposed framework and application to non-convex optimization , 2003, Comput. Chem. Eng..

[27]  Yuji Naka,et al.  A life-cycle approach for model reuse and exchange , 2002 .

[28]  Han Chonghun,et al.  Agent-based approach to a design support system for the synthesis of continuous chemical processes , 1995 .

[29]  S. C. Laufmann,et al.  Towards agent-based software engineering for information-depended enterprise applications , 1997, IEE Proc. Softw. Eng..

[30]  Vladan Devedzic,et al.  Understanding ontological engineering , 2002, CACM.

[31]  Gleb Frank,et al.  A General Interface for Interaction of Special-Purpose Reasoners within a Modular Reasoning System , 1999 .

[32]  Ming Liang Lu,et al.  A hypermanager for a computer integrated concurrent process engineering environment , 1996 .

[33]  Steven C. Laufmann,et al.  Toward Agent-Based Software Engineering for Information-Dependent Enterprise Applications , 1996 .

[34]  Michael Uschold,et al.  Ontologies: principles, methods and applications , 1996, The Knowledge Engineering Review.

[35]  Manfred Nagl,et al.  Workflow and information centered support of design processes - the IMPROVE perspective , 2004, Comput. Chem. Eng..

[36]  Antonis C. Kokossis,et al.  On the dynamic management of chemical engineering knowledge using an ontology-based approach , 2006 .

[37]  NICHOLAS R. JENNINGS,et al.  An agent-based approach for building complex software systems , 2001, CACM.

[38]  Eric S. Fraga,et al.  CAPE Web Services: The COGents way † , 2004 .

[39]  Jan Morbach,et al.  OntoCAPE: A Re-Usable Ontology for Chemical Process Engineering , 2009 .

[40]  Gintaras V. Reklaitis,et al.  Ontological informatics infrastructure for pharmaceutical product development and manufacturing , 2006, Comput. Chem. Eng..

[41]  A. Struthers,et al.  A new approach to integrated process systems engineering - the VIBE agent environment , 1998 .

[42]  I. Karimi,et al.  Agent-based supply chain management—1: framework , 2002 .

[43]  Jens Krüger,et al.  A concise conceptual model for material data and its applications in process engineering , 2003, Comput. Chem. Eng..

[44]  Bhaskar D. Kulkarni,et al.  Support vector classification with parameter tuning assisted by agent-based technique , 2004, Comput. Chem. Eng..

[45]  Matthias Klusch,et al.  Larks: Dynamic Matchmaking Among Heterogeneous Software Agents in Cyberspace , 2002, Autonomous Agents and Multi-Agent Systems.

[46]  E. Gallopoulos,et al.  Computer as thinker/doer: problem-solving environments for computational science , 1994, IEEE Computational Science and Engineering.

[47]  Ian T. Cameron,et al.  Applications of modelling: a case study from process design , 2002 .

[48]  Wolfgang Marquardt,et al.  Trends in computer-aided process modeling , 1996 .

[49]  Dongil Shin,et al.  Cooperative problem solving in diagnostic agents for chemical processes , 2000 .