1. Simulasi sistem persediaan

2. Outline What is Simulation? Advantages and Disadvantages of Simulation
Monte Carlo Simulation
Simulation and Inventory Analysis
The Role of Computers in Simulation

3. Learning Objectives
When you complete this chapter, you should be able to Identify or Define:
Monte Carlo simulation
Random numbers
Random number interval
Simulation software
Explain or be able to use:
The advantages and disadvantages of modeling with simulation
The use of Excel spreadsheets in simulation

4. Simulation Numerical technique of experimentation
Attempts to duplicate a system
Features
Behavior
Requires description of system
Many application areas
Operations management
Finance & economics

5. Some Applications of Simulation
Ambulance location and dispatching
Bus scheduling
Assembly-line balancing
Design of library operations
Parking lot and harbor design
Taxi, truck, and railroad dispatching
Distribution system design
Production facility scheduling
Scheduling aircraft
Plant layout
Labor-hiring decisions
Capital investments
Personnel scheduling
Production scheduling
Traffic-light timing
Sales forecasting
Voting pattern prediction
Inventory planning and control

6. Simulation The idea behind simulation is to:
Imitate a real-world situation mathematically
Study its properties and operating characteristics
Draw conclusions and make action recommendations based on the results of the simulation

7. The Process of Simulation
Define the Problem
Introduce important variables
Construct simulation model
Specify values of variables to be tested
Conduct the simulation
Examine the results
Select best course of action

8. Advantages of Simulation
flexible, straightforward
can analyze large, complex real-world problems for which no closed-form analytical solutions exists
can include real-world complications which most other techniques cannot
enables “time compression”
allows “what if” type questions
does not interfere with the real-world system
allows study of relationships

9. Disadvantages of Simulation
Can be expensive and time consuming
Does not yield optimal solution
Requires good managerial input
Results not generalizable to other situations
© T/Maker Co.

10. The Monte Carlo Simulation Technique
Setup probability distribution for important variables
Build cumulative distribution for each variable
Establish interval of random numbers for each variable
Generate random numbers
Simulate a series of trials

11. Partial Table of Random Numbers (upper left corner)52 06 50 88 53 30 10 47 99 37 66 91 35 63 28 02 74 24 03 29 60 85 90 82 57 68 05 94 11 27 79 87 92 69 36 49 71 32 75 21 95 98 78 23 67 89 25 96 62 56 72 33 48 17 34 13 44 39 55 18 31 15 40 51 01 61 08 54 12 80 64 73 00 45 14 46 41 86

12. Real World Variables Which Are Probabilistic in Nature
Inventory demand
Lead time for orders to arrive
Time between machine breakdowns
Times between arrivals at a service facility
Service times
Times to complete project activities
Number of employees absent from work each day

13. Simulation and Inventory Analysis - the Basic Model
Begin
Increase
current inv
by qty order
end inv =
begin-demand
# of
lost sales
End inv = 0
Generate Random lead time
Place
order
Compute averages
Enough Days
in simulation?
Order placed
& not arrived?
End inv < reorder
point?
demand >
begin inv?
Order
arrived?
random #
for today's
demand