MGO 302
Operations Management
© NC Simpson 2015
MGO 302:
Production and Operations
Management
SKELETON NOTES: Fall 2015
What is that stuff across the bottom of each
page???
On the left: Occasional humbnails of PowerPoint
slides and spreadsheets discussed in class, which
you can download from the MGO302 Documents
section of UBlearns…
Note Page 1
Intro/Providing Goods and Services
On the right: Thumbnails of “Keyword
Slides” that can be downloaded for free
from noteshaper.com
Information that appears within
‘starbursts’ like this refer to the
textbook Practical Operations
Management
MGO 302
Operations Management
© NC Simpson 2015
OPERATIONS MANAGEMENT: WHERE
DO WE FIT IN...
Note Page 2
Intro/Providing Goods and Services
More Detail:
Pages 18-19; Scenario
1b on page 19
MGO 302
Operations Management
© NC Simpson 2015
An Operation
(Any Operation)
What has productivity got to do with this view of a
production system? Sustainability?
Note Page 3
Intro/Providing Goods and Services
More Detail:
Pages 2-7
MGO 302
Operations Management
Note Page 4
Intro/Providing Goods and Services
© NC Simpson 2015
More Detail:
Pages 14-17; Scenario
1a on page 17
MGO 302
Operations Management
© NC Simpson 2015
CLASSIFYING PRODUCTS:
Goods vs. Services
Note Page 5
Intro/Providing Goods and Services
More Detail:
Pages 8-10
MGO 302
Operations Management
© NC Simpson 2015
CLASSIFYING PRODUCTS:
Standardized vs. Customized
Note Page 6
Intro/Providing Goods and Services
More Detail:
Pages 35-39
MGO 302
Operations Management
© NC Simpson 2015
PRODUCT LIFE CYCLE
Demand
Time
Note Page 7
Intro/Providing Goods and Services
More Detail:
Pages 39-41
MGO 302
Operations Management
© NC Simpson 2015
MEASURING PRODUCTIVITY…
Partial measure-
Multi-factor measure-
Total measure-
Lanark Farms sells fresh strawberries, growing the fruit both in
open fields and within long clear plastic hoop tents, known as its
tunnel operation. Last year, Lanark’s 50 acres of open fields
produced 25 tons of fresh strawberries, while the longer growing
season under its 10-acre tunnel operation produced 20 tons.
How productive is Lanark’s open-field operation? Is it more
productive than Lanark’s tunnel operation?
Note Page 8
Intro/Providing Goods and Services
More Detail:
Pages 41-45, including
Scenarios 1, 2a and 2b
starting on page 42
Similar Practice:
End of Chapter
Scenarios #21 and #22
MGO 302
Operations Management
© NC Simpson 2015
One key to the productivity of Lanark’s tunnel operation is the
higher air temperatures under the plastic tents, extending the
length of the growing season but making the plants more
vulnerable to disease. As a result, Lanark spends $225 per acre
for preventative chemical treatments in its tunnel operation,
whereas it spends only $20 per acre for its open fields. The
tunnel operation costs $250 per acre to construct and maintain
throughout the year. All Lanark’s strawberries require $125 per
acre to plant and $600 per ton to harvest and pack.
Now how productive is Lanark’s open field operation?
Note Page 9
Intro/Providing Goods and Services
MGO 302
Operations Management
© NC Simpson 2015
SIX OLD EXAM QUESTIONS ON PROVIDING
GOODS AND SERVICES:
Video tutorials explaining each of these questions are available on UBlearns.
1. Systems which produce highly customized products typically:
a) produce in relatively high volumes
b) have relatively low costs per unit produced
c) have invested a great deal of money in automation
d) can produce the product relatively quickly
e) use relatively high skilled workers
2. Which of the following is generally not a characteristic of a service operation?
a) intangible output
b) high customer contact
c) high labor content
d) stockpiling of output for future use
e) low uniformity of output
3. A large corporation has twelve different divisions that operate as twelve business units. Two
of its divisions each develop and launch a new product in data management, only to discover that
their new products are competing with each other in the corporation’s largest market. This large
corporation is best described as having a problem with what?
a) core competency b) sub-contracting
c) outsourcing d) goal alignment
e) economies of scale
4. In an assembly operation at a furniture factory, six employees assembled an average of 450
standard dining chairs during a five day work week. Which of the following best describes the
labor productivity of this operation?
a) 450 chairs
b) 90 chairs/day
d) 20 chairs/worker-day
c) 75 chairs/day
e) 15 chairs/worker-day
Similar to this:
Chapter 2 Quick
Start #14, #15, and
#16
5. An operation has a 20 percent scrap rate. As a result, 56 pieces per hour are produced. What
is the potential increase in labor productivity that could be achieved by eliminating the scrap?
a) 20%
b) 25%
c) 75%
d) 80%
e) 100%
Somewhat similar:
Chapter 2 Scenario
#21, part b
Note Page 10
Intro/Providing Goods and Services
MGO 302
Operations Management
© NC Simpson 2015
SIX OLD EXAM QUESTIONS ON PROVIDING
GOODS AND SERVICES, CONT’D:
Consider the following five situations: construction of a luxury cruise ship, operation of casual
dining restaurant, staging of a professional sports match, manufacturing a patented drug, and
rescuing stranded animals from a flooded area. Now consider the following grid, which
indicates five positions marked A, B, C, D and E. Each of these positions indicates differing
levels of tangibility and operation types:
Similar to this:
Chapter 1 Scenario #19
Match each of the five operations to its most appropriate position on this grid, using each
position only once. Please answer the following question, based on this exercise.
6. Which position on the grid best matches rescuing stranded animals from a flooded area?
a) position A
b) position B
c) position C
d) position D
e) position E
Note Page 11
Intro/Providing Goods and Services
MGO 302
Operations Management
© NC Simpson 2015
DEFINING QUALITY
Remember that quality is an “attribute.” That means everything has quality.
FIRST: The “Old” Definition
QUALITY =
NEXT: A “Newer” Definition (s)
Note Page 12
Product Quality and Development
More Detail:
Pages 52-55
MGO 302
Operations Management
© NC Simpson 2015
“TOTAL” QUALITY MANAGEMENT
A FEW ELEMENTS
TQM ELEMENT:
Everyone is a QC Inspector.
Tools?
TQM ELEMENT:
The customer defines quality.
Tools?
TQM ELEMENT:
Fix problems at their source.
Tools?
TQM ELEMENT:
Involve suppliers.
Consider distribution, installation, and use.
TQM ELEMENT:
The commitment of top management is
vital.
Note Page 13
Product Quality and Development
More Detail:
Pages 55-65
MGO 302
Operations Management
© NC Simpson 2015
TQM TOOL: QFD ANALYSIS
Think about the two definitions of quality. How do we relate
the perceptions and expectations of our customers to actual
specifications that we can build by?
Step One: Determine what features our customers consider
valuable.
Example: A Tennis Ball
Step Two: Now survey our customers to find out how they rate
several existing brands with respect to the features discovered in
Step One.
Survey Results:
Customer
Attributes:
Brand
A
Note Page 14
Product Quality and Development
Brand
B
Brand
C
Brand
D
MGO 302
Operations Management
© NC Simpson 2015
Step Three: Now we rate these brands according to their
technical specifications.
Rating Results:
Technical
Specifications:
Brand
A
Note Page 15
Product Quality and Development
Brand
B
Brand
C
Brand
D
MGO 302
Operations Management
© NC Simpson 2015
Step Four: Use the data from steps two and three to compute a
correlation matrix between the value features and the functional
characteristics. Strong correlations mean what?
RELATIONSHIP MATRIX (
Easy to See
Stays Bouncy
Stays Clean
look for QFD_Matrix.xls on UBlearns):
Thickness Density % Nylon % Latex in
of Shell
of Nap in Nap
Shell
-0.36
0.94
0.41
0.24
0.99
-0.50
0.52
-0.99
-0.06
0.87
0.48
-0.07
Note Page 16
Product Quality and Development
More Detail:
Page 58 and
Scenario 1 starting
page 59
MGO 302
Operations Management
© NC Simpson 2015
‘HOUSE OF QUALITY’:
Note Page 17
Product Quality and Development
More Detail:
Pages 66-72,
including Scenarios
2a and 2b
MGO 302
Operations Management
© NC Simpson 2015
SIX OLD EXAM QUESTIONS ON PRODUCT
QUALITY AND DEVELOPMENT:
Video tutorials explaining each of these questions are available on UBlearns.
1. Older, more traditional quality control systems often rely heavily on:
a) trust
b) luck
c) talent
d) inspection
e) good looks
2. Which of the following is (are) true?
I. A fishbone diagram is more useful than a histogram when conducting Pareto analysis.
II. The concept of “quality as conformance” is historically older than the concept of “quality as
improvement.”
III. ‘Remanufacturing’ refers to a ‘cradle-to-grave’ model of product design and production.
a) I only
b) II only
c) I and III
d) II and III
e) I, II and III
3. Which of the following is (are) principles of Total Quality Management?
I. Fix problems at their source.
II. Quality is the responsibility of the Quality Control Department, and no one else.
III. Seek continuous improvement.
a) I only.
b) II only.
c) III only.
d) I and III.
e) I, II, and III.
4. Which of the following is (are) true?
I. Unclear instructions and poor after sales service could lower a customer’s perception
of a product’s quality.
II. Total Quality Management relies heavily on professional inspectors to catch all
defects before they are shipped to the customer.
III. Total Quality Management attempts to involve everyone in an organization in the
effort to achieve quality.
a) I only.
b) I and II.
c) II only.
Note Page 18
Product Quality and Development
d) II and III.
e) I and III.
MGO 302
Operations Management
© NC Simpson 2015
SIX OLD EXAM QUESTIONS ON PRODUCT
QUALITY AND DEVELOPMENT, CONT’D:
5.
Suppose you manufacture high quality stereo equipment. Unfortunately, you hear that
customers think just the opposite: they say that your equipment “doesn’t work half of the time.”
You go out into your warehouse and inspect several hundred boxes of your own equipment.
Everything that you inspect works perfectly. Which of the following might be the source of your
reputation for poor quality stereo equipment?
I. Equipment is being damaged during shipment to the customer.
II. The instructions packed with the stereo equipment are unclear and customers are not
assembling the equipment correctly.
III. The stereo equipment does not conform to your specifications.
a) I only.
b) II only.
c) III only.
d) I and II.
e) I, II, and III.
6. Beserk Tennis Ball company has just conducted a QFD analysis that resulted in the following
“House of Quality” diagram:
An intern who worked on the project said that one of the correlation coefficients calculated when
creating the relationship matrix, “Came out crazy strong… it was -0.99978!” Which of the
following list is most likely to have been the relationship that earned that particular ‘crazy strong’
score?
a) the relationship between ‘Thickness of shell’ and ‘Density of Nap’
b) the relationship between ‘Easy to See’ and ‘Density of Nap’
c) the relationship between ‘Stays Clean’ and ‘Depth of Nap’
d) the relationship between the ‘Doesn’t Bounce Funny and ‘Thickness of shell’
e) the relationship between the ‘Doesn’t Bounce Funny and ‘Easy to See’
Note Page 19
Product Quality and Development
Similar to this:
Chapter 3,
Scenario #18
MGO 302
Operations Management
© NC Simpson 2015
FORECASTING
Qualitative Approaches
Quantitative Approaches
*Expert Opinion Panels
*Consumer Surveys
*Delphi Groups
Associative Models
*Regression Analysis
Time Series
Analysis
*Moving Averages
*Exponential Smoothing
*Seasonal Relatives
Note Page 20
Forecasting
More Detail:
Pages 86-88
MGO 302
Operations Management
© NC Simpson 2015
TIME SERIES TECHNIQUE: Moving Averages
To forecast the next value, simply average the “n” most recent
values!
EXAMPLE:
Month
Forecast:
Actual
2 Month
Monthly Sales Moving Average
Jan.
1,000
Feb.
2,000
March
3,000
Forecast:
3 Month
Moving Average
April
May
WHAT LENGTH OF MOVING AVERAGE SHOULD YOU
USE?
Note Page 21
Forecasting
MGO 302
Operations Management
© NC Simpson 2015
TIME SERIES TECHNIQUE: Simple Exponential Smoothing
To forecast the next value, consider this:
New Forecast = Old Forecast + Fraction * ( Actual Demand - Old Forecast)
EXAMPLE:
Month
Actual
Monthly Sales
Forecast:
 = 0.05
Forecast:
 = 0.90
Jan.
1,000
1,000
1,000
Feb.
2,000
March
April
May
WHAT  SHOULD YOU USE?
Note Page 22
Forecasting
More Detail:
Pages 107-113
including Scenarios
4a and 4b
MGO 302
Operations Management
© NC Simpson 2015
MEAN ERROR (ME)
Is your forecasting system doing a good job? Average its
errors!
ERROR = ACTUAL - FORECAST
ACTUAL:
MAY
JUNE
JULY
AUGUST
10
20
30
5
20
35
15
FORECAST: 5
ERROR:
MEAN SQUARE ERROR (MSE) ?
First square the errors, then average them.
MEAN ABSOLUTE DEVIATION (MAD)?
Average the absolute values of the errors.
MEAN ABSOLUTE PERCENT DEVIATION (MAPE)?
Average the absolute values of the errors.
TRACKING SIGNAL?
Divide the sum of the errors by the MAD.
Note Page 23
Forecasting
More Detail:
Pages 89-93 including
Scenario 1
Similar Practice:
End of Chapter Scenario
#29
MGO 302
Operations Management
CAUSAL MODELING…
Note Page 24
Forecasting
© NC Simpson 2015
MGO 302
Operations Management
© NC Simpson 2015
LINEAR REGRESSION
Livingston Medical Services provides medical transportation.
Comparing clients to actual transports for seven ‘courtesy van’
contracts suggests a relationship between these issues:
What is the linear regression equation that best expresses this
relationship? (
look for Livingston Medical Services Example.xls on UBlearns):
Note Page 25
Forecasting
More Detail:
Pages 96-99 including
Scenarios 2a and 2b
Similar Practice:
End of Chapter Scenarios
#27, #28 and #32
MGO 302
Operations Management
© NC Simpson 2015
SYSTEMATIC VARIATION TIME SERIES TECHNIQUE:
Seasonal Indices
To create a set of seasonal indices:
1. Obtain a sample of time series data and calculate the average
value for each season.
2. Now average the season averages.
3. Divide each season average (the result of step 1) by the
average of the averages (the result of step 2). The result is your
index value for that season.
Example: Parking Tickets on North Campus
Spring
Summer
Fall
30
40
50
30
150
170
160
170
(including Winter
Intercession)
2011
2012
2013
2014
Note Page 26
Forecasting
100
120
110
100
MGO 302
Operations Management
© NC Simpson 2015
WHAT ARE SEASONAL INDICES USED FOR?
* To Seasonalize Data
Multiply the data by the appropriate seasonal index. Why would you do this?
* To De-seasonalize Data
Divide the data by the appropriate seasonal index. Why would you do this?
Note Page 27
Forecasting
More Detail:
Pages 103-107 including
Scenarios 3a, 3b and 3c
Similar Practice:
End of Chapter
Scenarios #26 and #31
MGO 302
Operations Management
© NC Simpson 2015
SIX OLD EXAM QUESTIONS ON FORECASTING:
Video tutorials explaining each of these questions are available on UBlearns.
1. Given an actual demand of 59 in March, a March forecast of 64, and an “alpha” () of 0.3,
what would the forecast for April be using exponential smoothing?
a) 36.9
b) 57.5
c) 60.5
d) 62.5
e) 65.5
Similar to this:
Chapter 4 Quick Start #18
2. Simple exponential smoothing is being used to forecast demand. The previous forecast of 66
turned out to be four units less than actual demand. The next forecast is 66.6, implying an “alpha”
(), equal to:
a) 0.01
b) 0.1
c) 0.15
d) 0.20
e) 0.60
Similar to this:
Chapter 4 Ramp Up
#21
3. Jim’s Bicycle Company has provided you with the following data on their past sales of
unicycles:
October 2012
November 2012
December 2012
January 2013
40
42
44
31
Similar to this:
Chapter 4 Scenario
#25 and #30
Predict sales for February 2013, using a 3-month moving average.
a) -6.00
b) 39.00
c) 39.25
e) 52.33
d) 42.00
4. Here are the errors associated with a particular forecast over the past five months, in
chronological order: 2, 5, 0, -5, -10. Which of the following statements is (are) true?
I. The forecast was too high during the fifth month.
II. The mean error over these five months is 4.4.
III. The forecast was perfectly accurate during one of the months.
a) II only
Note Page 28
Forecasting
b) III only
c) I and III
d) II and III
Similar to this:
Chapter 4 Ramp Up
#23
e) I, II and III
MGO 302
Operations Management
© NC Simpson 2015
SIX OLD EXAM QUESTIONS ON FORECASTING,
CONT’D:
Below are the seasonal relatives (also known as seasonal index numbers) that describe the
weekly fluctuation in the number of distinct users logging into a certain website daily, also
known as the number of unique appearances per day.
Day of the Week
Monday
Tuesday
Wednesday
Thursday
Friday
Saturday
Sunday
Seasonal Relative (or
Index Number) for
Unique Appearances
1.25
1.01
1.03
1.09
0.94
0.66
1.01
Similar to this:
Chapter 4 Scenario
#26
Please answer the following two questions, based on this information.
5. Which of the following is (are) true about the number of unique appearances on the website?
I. Monday is the busiest day of the week in terms of the number of unique appearances on the
website.
II. Only 66% of users log in on Saturday.
III. Fridays are busier than Thursdays in terms of the number of unique appearances that day.
a) I only
b) II only
c) III only
d) I and II
e) II and III
6. Suppose someone has given you a forecast for the first full week of next month: an overall
number of 3,500 unique appearances will be recorded throughout the seven days of that week.
Based on this estimate, which of the following is the most logical estimate of the number of
unique appearances during the Thursday of that week?
a) 459
b) 500
Note Page 29
Forecasting
c) 545
d) 625
e) 3815
MGO 302
Operations Management
© NC Simpson 2015
CAPACITY PLANNING CONCEPTS:
TYPES OF CAPACITY
* Design Capacity- the maximum possible rate of output
that can be achieved
* Effective Capacity- the rate of output the firm is
capable of achieving, given preventative maintenance,
set-up time, etc.
* Actual Output- whatever rate of output is actually
achieved
Note Page 30
Capacity Planning
MGO 302
Operations Management
© NC Simpson 2015
CAPACITY PLANNING CONCEPTS:
MEASURING CAPACITY
* “Efficiency” -
* “Utilization”-
Note Page 31
Capacity Planning
More Detail:
Pages 125-127 including
Scenario 1
MGO 302
Operations Management
© NC Simpson 2015
CAPACITY STRATEGY
CUSTOMER
DEMAND
TIME
Note Page 32
Capacity Planning
MGO 302
Operations Management
© NC Simpson 2015
ANOTHER
CAPACITY STRATEGY
CUSTOMER
DEMAND
TIME
Note Page 33
Capacity Planning
More Detail:
Pages 129-132
MGO 302
Operations Management
© NC Simpson 2015
CAPACITY PLANNING TOOL:
BREAK-EVEN ANALYSIS
When will revenue cover your costs, given you invest in a particular process?
Note Page 34
Capacity Planning
MGO 302
Operations Management
© NC Simpson 2015
BREAKEVEN ANALYSIS: Pick a Cargo Ship…
Vessel
Variable
Fixed Cost Cost per
Ton
Revenue
per Ton
When do
you break
even?
American
Century
Sam Laud
Note Page 35
Capacity Planning
More Detail:
Pages 127-129 including
Scenario 2
Similar Practice:
End of Chapter
Scenario #30
MGO 302
Operations Management
© NC Simpson 2015
SIX OLD EXAM QUESTIONS ON CAPACITY
PLANNING:
Video tutorials explaining each of these questions are available on UBlearns.
1. A production facility has a design capacity of 200 units a day and an effective capacity of 190
units. Which of the following are potential “determinants” of its effective capacity, accounting
for the gap between 200 and 190?
I. The need for periodic maintenance of the equipment in the facility.
II. The actual output of the facility.
III.
Lunch breaks and coffee breaks taken during a typical day in the facility.
a) I only
b) I and II
c) II only
d) I and III
e) I, II and III
2. The Kitti Kreme Donut production facility consists of three identical donut production lines,
each of which operated at 80% efficiency last week. If this facility produced a total of 30,000
donuts last week, what is the apparent effective capacity of one of Kitti Kreme’s donut
production lines?
Similar to this:
a) 8,000 donuts
b) 10,000 donuts
c) 12,500 donuts
Chapter 5 Ramp
d) 24,000 donuts
e) 37,500 donuts
Up #24
3. Costs that continue to be incurred even if no units are produced by a facility are called
a) fixed costs
b) variable costs
c) breakeven costs
d) marginal costs
e) relational costs
Medic Clinic is considering purchasing a new blood analysis machine for $60,000. Medic Clinic
can charge $25.00 for each blood sample analyzed, while the actual cost of the blood analysis
would only be $5.00. The new machine has a design capacity of 6,000 blood analyses a year and
an effective capacity of 5,000 blood analyses a year. The following three questions concern
Medic Clinic.
4. How many blood analyses would have to be performed in order for Medic Clinic to break
even?
a) 12,000
b) 5,000
c) 3,000
d) 2,400
e) 1,000
5. Suppose Medic Clinic expects to perform 4,500 blood analyses next year, if it buys the new
machine. What would be the utilization of this machine?
a) 0%
b) 75%
c) 83%
d) 90%
e) 100%
6. How may blood analyses would Medic Clinic have to perform each year, in order for the use
of the new machine to be 80% efficient?
a) 1,000
b) 3,200
c) 4,000
d) 4,800
e) 5,000
Similar to this:
Note Page 36
Capacity Planning
Chapter 5 Quick Start
#14, #15,#16
MGO 302
Operations Management
© NC Simpson 2015
WAITING LINE THEORY:
THE BASIC ANATOMY OF A LINE
CUSTOMER ARRIVAL ISSUES
* SOURCE?
* DISTRIBUTION OF ARRIVAL?
* DEGREE OF PATIENCE?
Note Page 37
Waiting Lines
MGO 302
Operations Management
© NC Simpson 2015
WAITING LINE ISSUES
* LENGTH?
* NUMBER?
* QUEUE DISCIPLINE?
SERVICE SYSTEM ISSUES
* DISTRIBUTION OF SERVICE TIME?
* STRUCTURE?
Note Page 38
Waiting Lines
More Detail:
Pages 132-139
MGO 302
Operations Management
© NC Simpson 2015
Global Freightways depots are open to drop-off air cargo 24
hours a day, although only one agent is available during nonbusiness hours. A single agent requires an average of 20 minutes
to complete data entry, check cargo, and process the payment
for the shipment. At the Hong Kong depot, an average of one
client arrives each hour during weeknight non-business hours.
CUSTOMER ARRIVALS
Source?
Distribution of Arrival?
Degree of Patience?
WAITING LINE
Length?
Number?
Queue Discipline?
SERVICE SYSTEM
Structure?
Distribution of Service Time?
Note Page 39
Waiting Lines
MGO 302
Operations Management
© NC Simpson 2015
AT THE HONG KONG DEPOT DURING NON-BUSINESS HOURS:
* What is the probability that an arriving customer will have to wait?
* What proportion of the time will the agent be idle?
* What is the probability of exactly one customer being at the Global
Freightways Depot?
* What is the average length of the line at the Global Freightways
Depot?
* What is the average number of customers at the Global Freightways
Depot?
* What is the average wait to speak to the agent?
*What is the average total amount of time spent by a customer at the
depot?
Note Page 40
Waiting Lines
More Detail:
Pages 140-142, including
Scenario 3
Similar Practice:
End of Chapter
Scenario #34
MGO 302
Operations Management
© NC Simpson 2015
AN ALTERNATE (NON-MATHEMATICAL) VIEW…
Absolute vs. Perceived Time
People do not perceive time at a constant rate. One ten minute delay can
be longer than another ten minute delay, given the person waiting was
subject to certain conditions. What are those conditions?
A Ten Minute Delay Will
Be Longer If It Is...
Note Page 41
Waiting Lines
How Can This Be Used to
Make Shorter Waits?
More Detail:
Pages 143-145
MGO 302
Operations Management
© NC Simpson 2015
SIX OLD EXAM QUESTIONS ON WAITING
LINES:
Video tutorials explaining each of these questions are available on UBlearns.
All trucks traveling on I-75 south of Gainesville, Florida must stop at a weigh station. This
station has one set of scales, which can weigh an average of 18 trucks an hour, exponentially
distributed. Trucks arrive at the weigh station at an average of 15 an hour, Poisson distributed.
Note the formulas necessary to analyze this weigh station are included with your exam.
1.
What is the average delay a truck suffers at the I-75 weigh station? That is, what is the
average total time the truck spends waiting and being weighed? (In minutes!)
a) 0.2778 minutes
b) 0.3333 minutes
c) 4.1667 minutes
Similar to this:
d) 16.6667 minutes e) 20 minutes
Chapter 5 Quick Start
2.
What is the probability that there are no trucks at the I-75 weigh station?
a) 0.0000
b) 0.1667
c) 0.2778
d) 0.3333
e) 0.8333
#18 through #23
and Scenario #35
3. You are observing a line of people forming at the ordering counter of Starbuck’s Coffee on
the North Campus of UB. This line has at least fifteen people in it, waiting to order coffee.
Suddenly you notice two people walk through the front door of Starbuck’s, stop when they see
the other fifteen people waiting to order, shake their heads, turn around and exit Starbuck’s again
immediately. What you have just witnessed is an instance of customer impatience best known
as:
a) switching
b) balking
c) reneging
d) dodging
e) restlessness
4. Suppose you are taking a 105 minute airplane flight from Buffalo, NY to Atlanta, GA. This
flight does not occur at mealtime, but the cabin staff still provides you with a small drink and two
packs of honey-roasted peanuts. You eat the peanuts and study the evacuation instructions and
the airline magazine you found in the pocket of the seat in front of you. Which of the following
best describes the psychological waiting principle both you and the airline are employing to
shorten this 105 minute waiting period?
I. In-process waits are shorter than pre-process waits.
II. Unfair waits are longer than fair waits.
III. Occupied waits are shorter than unoccupied waits.
a) I only.
b) II only.
Note Page 42
Waiting Lines
c) III only.
d) I and II.
e) I, II, and III.
MGO 302
Operations Management
© NC Simpson 2015
SIX OLD EXAM QUESTIONS ON WAITING
LINES, CONT’D:
Cars traveling from Canada to the United States through the Thousand Islands Border Crossing
must stop for US Customs and Immigration. During the stop, each passenger in the car will
present a passport for inspection by a US Customs Officer, answer questions, and declare certain
valuables that may be in the car. On average, it takes a Customs Officer about five minutes to
inspect passports and release a car for entry into the United States. Since the Thousand Islands
Border Crossing is not heavily traveled at night, US Customs and Immigration only keeps one
lane open at the checkpoint plaza and one officer on duty to process arriving cars. Between
midnight and 6:00 AM, cars arrive on at the Border Crossing plaza at an average rate of two per
hour.
5. Assuming this scenario meets the assumptions of the M/M/1 model, what percent of the time
is the US Customs Officer busy with inspecting the passports from arriving cars between
midnight and 6:00 AM?
a) 16.7%
b) 33%
c) 40%
d) 67%
e) 167%
6. When a car arrives at this checkpoint between midnight and 6:00 AM, what is the average
length of time it must wait before speaking with this US Customs Officer?
a) 0.02 minutes
b) 0.03 minutes
c) 1 minute
d) 2 minutes
Similar to this:
Chapter 5,
Scenario #36 and #37
Note Page 43
Waiting Lines
e) 6 minutes