Production and Operations Management: Manufacturing and Services

1
CHAPTER 15 SIMULATION
2
Technical Note 15Simulation

• Definition of Simulation
• Simulation Methodology
• Proposing a New Experiment
• Considerations When Using Computer Models
• Types of Simulations
• Desirable Features of Simulation Software
• Advantages Disadvantages of Simulation

3
SimulationDefined

• A computer-based model used to run experiments on
  a real system.
• Typically done on a computer.
• Determines reactions to different operating rules
  or change in structure.
• Can be used in conjunction with traditional
  statistical and management science techniques.

4
Major Phases in a Simulation Study
From Exhibit TN15.1
Start
Run the simulation
Define Problem
Evaluate results
Construct Simulation Model
Validation
Specify values ofvariables and parameters
Propose new experiment
Stop
5
Simulation MethodologyProblem Definition

• Specifying the objectives
• Identifying the relevant controllable and
  uncontrollable variables of the system to be
  studied

6
Constructing a Simulation Model

• Specification of Variables and Parameters
• Specification of Decision Rules
• Specification of Probability Distributions
• Specification of Time-Incrementing Procedure

7
Data Collection and Random Number Interval Example
Suppose you timed 20 athletes running the
100-yard dash and tallied the information into
the four time intervals below.
You then count the tallies and make a frequency
distribution.
Then convert the frequencies into percentages.
You then can add the frequencies into a
cumulative distribution.
Finally, use the percentages to develop the
random number intervals.
Seconds 0-5.99 6-6.99 7-7.99 8 or more
Tallies
Frequency 4 10 4 2
20 50 20 10
RN Intervals 00-19 20-69 70-89 90-99
Accum. 20 70 90 100
8
Evaluating Results

• Conclusions depend on
• the degree to which the model reflects the real
  system
• design of the simulation (in a statistical
  sense)
• The only true test of a simulation is how well
  the real system performs after the results of the
  study have been implemented.

9
Proposing a New Experiment

• Might want to change many of the factors
• parameters
• variables
• decision rules
• starting conditions
• run length
• If the initial rules led to poor results or if
  these runs yielded new insights into the problem,
  then a new decision rule may be worth trying.

10
Considerations When Using Computer Models

• Computer language selection
• Flowcharting
• Coding
• Data generation
• Output reports
• Validation

11
Types of Simulation Models

• Continuous
• Based on mathematical equations.
• Used for simulating continuous values for all
  points in time.
• Example The amount of time a person spends in a
  queue.
• Discrete
• Used for simulating specific values or specific
  points.
• Example Number of people in a queue.

12
Desirable Features of Simulation Software

• Be capable of being used interactively as well as
  allowing complete runs.
• Be user-friendly and easy to understand.
• Allow modules to be built and then connected.
• Allow users to write and incorporate their own
  routines.
• Have building blocks that contain built-in
  commands.
• Have macro capability, such as the ability to
  develop machining cells.

13
Desirable Features of Simulation Software

• Have material-flow capability.
• Output standard statistics such as cycle times,
  utilization, and wait times.
• Allow a variety of data analysis alternatives for
  both input and output data.
• Have animation capabilities to display
  graphically the product flow through the system.
• Permit interactive debugging.

14
Advantages of Simulation

• Often leads to a better understanding of the real
  system.
• Years of experience in the real system can be
  compressed into seconds or minutes.
• Simulation does not disrupt ongoing activities of
  the real system.
• Simulation is far more general than mathematical
  models.
• Simulation can be used as a game for training
  experience.

15
Advantages of Simulation (Continued)

• Simulation provides a more realistic replication
  of a system than mathematical analysis.
• Simulation can be used to analyze transient
  conditions, whereas mathematical techniques
  usually cannot.
• Many standard packaged models, covering a wide
  range of topics, are available commercially.
• Simulation answers what-if questions.

16
Disadvantages of Simulation

• There is no guarantee that the model will, in
  fact, provide good answers.
• There is no way to prove reliability.
• Building a simulation model can take a great deal
  of time.
• Simulation may be less accurate than mathematical
  analysis because it is randomly based.
• A significant amount of computer time may be
  needed to run complex models.
• The technique of simulation still lacks a
  standardized approach.