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INFORMATION AND KNOWLEDGE MANAGEMENT IN COMPLEX SYSTEMS

INFORMATION AND KNOWLEDGE MANAGEMENT IN COMPLEX SYSTEMS. Ksiazka jest do nabycia w GTN, Gdansk. Zamowienia mozna przesylac do Biura Towarzystwa e-mailem gtn@3net.pl , faksem 305-81-31. Ksiazka jest wysylana poczta z faktura VAT.

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INFORMATION AND KNOWLEDGE MANAGEMENT IN COMPLEX SYSTEMS

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  1. INFORMATION AND KNOWLEDGE MANAGEMENT IN COMPLEX SYSTEMS

  2. Ksiazka jest do nabycia w GTN, Gdansk. Zamowienia mozna przesylac do Biura Towarzystwa e-mailem gtn@3net.pl , faksem 305-81-31. Ksiazka jest wysylana poczta z faktura VAT. Sprzedaz prowadzi tez Ksiegarnia Naukowa przy ul. Lagiewniki 56 w Gdansku

  3. SOCIAL CHARACTERISTICS OF THE AGRICULTURAL, INDUSTRIAL AND INFORMATION SOCIETIES (Castells 2001, 2003)

  4. MANAGEMENT OF INFORMATION… Presentation outline: • significance and aims • methods and techniques • results so far • implementations

  5. SIGNIFICANCE AND AIMS • If all the N elements of a system are required to communicate, the amount of information transfer is likely to become unmanageable. • The above has been the reason why systems that are divided into smaller subsystems (called atomized or multi-agent or multi-component systems) are recently gaining considerable attention. • In atomized approach efficiency of components depends on quality and quantity of information flow (Jain 2001) • Our research is primarily concerned with capture of knowledge useful in structuring and evaluation of such an information flow.

  6. AUTONOMOUS AGENTS/SYSTEMS • AUTONOMOUS AGENTS CONSIST OF GROUPS OF PEOPLE, MACHINES, ROBOTS, AND/OR GUIDED VEHICLES TIED BY THE FLOW OF INFORMATION BETWEEN AN AGENT AND ITS EXTERNAL ENVIRONMENT AS WELL AS WITHIN AN AGENT • AUTONOMOUS AGENTS CAN STILL BE INTERRELATED AND EMBEDDED IN LARGER SYSTEMS, AS AUTONOMY AND INDEPENDENCE ARE NOT EQUIVALENT CONCEPTS. (E. Szczerbicki, IEEE Transactions on Systems, Man, and Cybernetics, Vol. 23, p. 1302)

  7. SOLVING COMPLEX PROBLEMS DECOMPOSITION INTEGRATION INTEGRATED SOLUTION COMPLEX SYSTEM REPRESENTATION

  8. DECOMPOSITION…..

  9. DECOMPOSITION….

  10. AND/OR CLAUSES

  11. EXAMPLE:AND/OR NOTATION

  12. SOLVING COMPLEX PROBLEMS COMPLEX SYSTEM DECOMPOSITION REPRESENTATION INTEGRATION INTEGRATED SOLUTION

  13. QUESTIONS……. • How to structure an exchange of information between a system and its uncertain, dynamic and imprecise environment? • What is better, complete information but heavily delayed, or incomplete information less delayed?

  14. INFORMATIONAL BALANCE

  15. EVALUATION OF INFORMATION FLOW

  16. ENERGY, INFORMATION AND ACTION

  17. INFORMATION STRUCTURE 1 0 0 0 0 1 0 0 0 0 1 1 0 0 1 1 X1 X2 X3 X4

  18. THE VALUE OF INFORMATION STRUCTURE C

  19. SOFT VS HARD MODELLING THEORY RICHNESS SOFT MODELLING NEURAL NETWORKS EXPERT SYSTEMS PHYSICAL MODELLING DATA RICHNESS

  20. NEURAL NETWORKS

  21. THE USE OF THE TRAINED NETWORK

  22. DECISION TREE CLASSIFIERS

  23. DECISION TREE: TESTING ON INTERNAL ENVIRONMENT

  24. SIGNED DIRECTED GRAPHS (SDG)

  25. SDG MODEL OF AN INFORMATIONAL BALANCE – FINAL SIMPLIFICATION

  26. SAMPLE OF PRODUCTION RULES RULE 12 IF an external environment of an autonomous agent is static, AND there is an interaction in the internal environment, AND the relationship between variables describing the external environment is of statistical character, THEN information structure should include observation (sensoring) and communication. RULE 13 IF an external environment of an autonomous agent is static, AND the relationship between variables describing the external environment is given by function dependence, THEN communication between agent elements does not affect the value of information structure; information flow should be restricted to observation (sensoring).

  27. SOLVING COMPLEX PROBLEMS COMPLEX SYSTEM DECOMPOSITION REPRESENTATION INTEGRATION INTEGRATED SOLUTION

  28. FIVE LEVEL HIERARCHICAL TREE OF THE OVERALL INTEGRATED SYSTEM

  29. INTEGRATION…… Reference

  30. IMPLEMENTATIONS…. • Product design co-ordination • Modeling and simulation of information flow for performance enhancement: • coal mine • steel processing • hospital operation • maintenance • manufacturing • Concurrent engineering philosophy • Information systems development for environmental issues

  31. SUPPORT FOR INTEGRATION TECHNOLOGY EMBODIMENT OF INTEGRATED APPROACH TO INFORMATION PROBLEMS GENERALLY AND INFORMATION SYSTEMS DESIGN SPECIFICALLY

  32. SIMULATIONFORPERFORMANCE ENHANCEMENT

  33. PROJECTS • steel processing • manufacturing • hospital operation • mining • preventive maintenance • servicing

  34. VISUAL SLAM & AWESIM The computer simulation software package that we use is called Visual SLAM. “Visual SLAM supports the modeling of systems from diverse points of view through a graphical based interface. AweSIM is a simulation problem-solving environment for Visual SLAM. AweSIM provides a database, project maintainer, interactive execution environment, standard textual and graphical reports and concurrent and post process animation facilities.”

  35. “AIRBORN” SIMULATION

  36. SOLVING COMPLEX PROBLEMS COMPLEX SYSTEM DECOMPOSITION REPRESENTATION INTEGRATION INTEGRATED SOLUTION

  37. DECOMPOSITION INTO FUNCTIONS AND TASKS

  38. CONDITION MONITORING

  39. OPEN-CUT COAL MINE

  40. SIMULATION REPORTS

  41. SIMULATION… • Simulation Modelling can be Applied to the Whole Life Cycle of a Typical Industrial Systems Project. • Probably one of the most important advantages of simulation modelling is its adaptability. It can be easily applied concurrently to all project stages as the project evolves. The stages usually involve (i) concept design, (ii) detailed design, (iii) implementation, and (iv) operation. Using simulation models developed concurrently with each stage we can: • understand basic system operation at the concept design level, • select the best concept to proceed with to the detailed design, • test all proposed operating and control procedures, • test the impact of all design changes made during the implementation stage, • test the impact of all proposed changes during the operation stage, • predict necessary changes in the system operation to follow the envisaged changes in the external and internal environments of the system

  42. SIMULATION… • Do not simulate when: • the problem can be solved using common sense analysis, • the problem can be solved analytically, • it's easier to change or perform direct experiment on the real system, • the cost of the simulation exceeds possible savings, • there are not proper resources available for the project, • there is not enough time for the model results to be useful, • there is no data - not even estimates, • the model can not be verified or validated, • project expectations can not be met, • the system's behaviour is too complex or can't be defined.

  43. RESEARCH TOWARDS THE DEVELOPMENT OF A PLANNING SYSTEM FOR CONCURRENT ENGINEERING DESIGN

  44. SEQUENTIAL PRODUCT DEVELOPMENT PROCESS MARKETING DESIGN PRODUCTION DISTRIBUTION

  45. Concurrent Engineering (CE) has been described as(IDA Report 1988): “a systematic approach to the integrated design of products and their related processes, including manufacture and support. This approach is intended to cause the developers from the outset, to consider all elements of the product life cycle from conception through disposal, including quality, cost, schedule and user requirements.”

  46. CE BENEFITS: US DEPARTMENT OF DEFENCE • Engineering Change Orders reduced by 50% or greater. • Product development cycle time reduced 40-60%. • Cost to Manufacture reduced 30-40%. • Rework and scrap reduced by up to 75%.

  47. KEY FEATURES OF CE: • Cross-Functional Teams (CFT’s) • Concurrent Product Realisation Process Activities • Incremental Information Sharing and Use • Design for “X” (DFX) • Integrated Project Management • Early and Continual Supplier Involvement • Early and Continual Customer Focus

  48. CE BUILDING BLOCKS AND CORE PHILOSOPHY

  49. THE MAIN ELEMENTS OF CE MANAGEMENT • COLLABORATION • COMMUNICATION • COORDINATION • CONTROL • INFORMATION DEPENDENT SYSTEM

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