Version 1.0, August 31, 2001, Copyright, Hugh Jack 1993-2001

15. SIMULATION

 

· Some complex systems can't be modeled because of,

  1. - random events
  2. - changing operating conditions
  3. - too many interactions
  4. - exact solutions don't exist

 

· Simulation is used to determine how these systems will behave

 

· Simulation typically involves developing a model that includes discrete stations and events that occur with some probable distribution.

 

· We can then examine the simulation results to evaluate the modeled system. Examples include,

  1. - machine utilization
  2. - lead time
  3. - down time
  4. - etc.

 

· This is a very effective tool when considering the effect of a change, comparing decision options, or refining a design.

 

· Some simulation terms include,

  1. System - the real collection of components
  2. Model - a reasonable mathematically (simpler) representation of the system
  3. State - the model undergoes discrete changes. A state is a `snapshot' of the system
  4. Entity - a part of the system (eg machine tool)
  5. Attributes - the behavior of an entity
  6. Event - something that changes the state of a machine
  7. Activity - when an entity is going through some activity. (eg, press cycling)
  8. Delay - a period of time with no activity

 

· Good approach to simulation,

  1. 1. Determine what the problem is
  2. 2. Set objectives for the simulation
  3. 3. Build a model and collect data
  4. 4. Enter the model into a simulation package
  5. 5. Verify the model then check for validity
  6. 6. Design experiments to achieve goals
  7. 7. Run simulations and collect results
  8. 8. Analyze and make decisions

 

 

15.1 MODEL BUILDING

15.2 ANALYSIS

15.3 DESIGN OF EXPERIMENTS

15.4 RUNNING THE SIMULATION

15.5 DECISION MAKING STRATEGY

15.6 PLANNING

15.7 NEURAL NETWORK THEORY