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Part III Simulation: Information Flow for Performance Enhancement with Case Studies

Part III Simulation: Information Flow for Performance Enhancement with Case Studies.

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Part III Simulation: Information Flow for Performance Enhancement with Case Studies

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  1. Part III Simulation: Information Flow for Performance Enhancement with Case Studies

  2. Systems have grown in complexity over the years mainly due to the increased striving for performance enhancing combined with a greater degree of informational uncertainty and imprecision in system's external and internal environments. This complexity, always present in real life systems, makes the application of quantitative tools as problem solvers questionable in many instances. This issue was extensively discussed in some previous Chapters of this book.In this Section discrete computer simulation technique is proposed as an additional analysis tool that proved to be an adequate, effective and economically efficient problem solver in a number of cases of information flow and management related to scheduling and resource allocation and utilisation forcomplex real life servicing, processing and manufacturing system.

  3. SIMULATION:TO SIMULATE MEANS TO DUPLICATE THE ESSENCE OF THE SYSTEM OR ACTIVITY WITHOUT ACTUALLY ATTAINING REALITY ITSELF.

  4. COMPUTER SIMULATION:ESTABLISHMENT OF A MATHEMATICAL-LOGICAL MODEL OF A SYSTEM AND THE EXPERIMENTAL MANIPULATION OF IT ON A COMPUTER.

  5. MAIN ADVANTAGES: • TIME • COST • SAFETY

  6. SIMULATION FOR

  7. Modern simulation platforms

  8. Visual SLAM & AweSIM

  9. SIMULATION FOR PERFORMANCE ENHANCEMENT

  10. PROJECTS steel processing manufacturing hospital operation mining preventive maintenance servicing

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

  12. “AIRBORN” SIMULATION

  13. DECOMPOSITION INTO FUNCTIONS AND TASKS

  14. OPEN-CUT COAL MINE

  15. SIMULATION REPORTS

  16. The average number of sampling positions and their location

  17. Skill level needs and service requirements at different locations

  18. The model can be used to simulate the monitoring service and optimise the manning scale and instrument resources for this service. It provides an adoptable, flexible management framework that may be applied to any company with a condition monitoring workforce that is varying in versatility, expertise, and availability.

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