Lecture Operations management: Creating value along the supply chain (Canadian edition) - Chapter 13S

Chapter 13 supplement - Operational decision-making tools: Simulation. This chapter includes contents: Monte carlo simulation, computer simulation with excel, areas of simulation application.

Robert S Russell, Bernard W Taylor III, Ignacio Castillo, Navneet Vidyarthi

CHAPTER 13

SUPPLEMENT

Operational Decision-Making Tools:

Simulation

OPERATIONS MANAGEMENT:

Creating Value Along the Supply Chain,

Canadian Edition

Lecture Outline

—Monte Carlo Simulation

—Computer Simulation with Excel

—Areas of Simulation Application

—Mathematical and computer modeling technique

for replicating real-world problem situations

—Modeling approach primarily used to analyze

probabilistic problems

—It does not normally provide a solution; instead it provides information that is used to make a decision

—Physical simulation

—Space flights, wind tunnels, treadmills for tires

—Mathematical-computerized simulation

—Computer-based replicated models

Monte Carlo Simulation

— Select numbers randomly from a probability

distribution

— Use these values to observe how a model

performs over time

— Random numbers each have an equal likelihood

of being selected at random

Probability Distribution of Demand

Roulette Wheel of Demand

90

0

x = 2

x = 0

x = 4

x = 3

x = 1

Generating Demand from

Random Numbers

DEMAND, RANGES OF RANDOM NUMBERS,

Random Number Table

15 Weeks of Demand

WEEK r DEMAND (x) REVENUE (S)

1 39 1 4,300

2 73 2 8,600

3 72 2 8,600

4 75 2 8,600

5 37 1 4,300

7 87 3 12,900

8 98 4 17,200

10 47 1 4,300

11 93 4 17,200

12 21 1 4,300

13 95 4 17,200

14 97 4 17,200

Computing Expected Demand

E(x) = (0.20)(0) + (0.40)(1) + (0.20)(2)

+ (0.10)(3) + (0.10)(4)

= 1.5 laptops per week

• Difference between 1.5 and 2.07 is due to small number of periods analyzed (only 15 weeks)

• Steady-state result

Estimated average demand = 31/15 = 2.07 laptops/week

Random Numbers in Excel

Simulation in Excel

Enter this formula

in G6 and copy to G7:G20

Enter “=4300*G6”

in H6 can copy to H7:H20

Generate random number for cells F6:F20 with the

=AVERAGE(G6:G20)

Simulation in Excel

Spreadsheet “frozen”

Decision Making with Simulation

=G6*50 entered into cell L6 and copied

to L7:L105

This formula entered in G7 and copied to

G8:G105

=VLOOKUP (F6,LOOKUP,2)

in H6 and copied

to H7:H105

Decision Making with Simulation

New formula for two laptops ordered

per week.

Areas of Simulation Application

—Waiting Lines/Service

—Complex systems for which it is difficult to develop

analytical formulas

—Determine how many registers and servers are needed

to meet customer demand

—Inventory Management

—Traditional models make the assumption that customer demand is certain

—Simulation is widely used to analyze JIT without having to implement it physically

Areas of Simulation Application

—Production and Manufacturing Systems

—Production scheduling, production sequencing, assembly line balancing, plant layout, and plant location analysis

—Machine breakdowns typically occur according to some probability distributions

—Capital Investment and Budgeting

—Capital budgeting problems require estimates of cash

flows, often resulting from many random variables

—Simulation has been used to generate values of cash

flows, market size, selling price, growth rate, and market share

Areas of Simulation Application

—Logistics

—Random variables include, distance, transport modes, shipping rates, and schedules

—Allows analysis of different distribution channels

—Service Operations

—Police departments, fire departments, post offices,

hospitals, court systems, airports

—Complex operations where only simulation can be

employed

—Environmental and Resource Analysis

—Impact of manufacturing plants, waste-disposal facilities,

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