ISyE 3104: Introduction to Supply Chain Modeling: Manufacturing and Warehousing
Instructor: Spyros Reveliotis
Summer 2002
Homework #2
Due Date: Wednesday, 6/12/02
Problem set:
1. Chapter 4:
 Discussion Questions: 1,3,4,9,16
2. Chapter 5:
 Discussion Questions: 2,4,6,10,12
 Problem 5.13 and 5.14
 Case Study 2 on Regal Marine
Extra Credit (40%)
Use your background on linear regression from your statistics class, to address the case
study on Southwestern University at the end of Chapter 4 in your textbook.
Chapter 4 Forecasting
DISCUSSION QUESTIONS
1. The steps that should be used to develop a forecasting system are:
(a) Determine the purpose and use of the forecast
(b) Select the item or quantities that are to be forecasted
(c) Determine the time horizon of the forecast
(d) Select the type of forecasting model to be used
(e) Gather the necessary data
(f) Validate the forecasting model
(g) Make the forecast
(h) Implement the results
(i) Evaluate the accuracy of results, and if necessary revise the model (in case
of repetitive use)
C.f. also the corresponding slide in the class presentation on forecasting.
3. A time series model uses only historical values of the quantity of interest to predict
future values of that quantity. The associative model, on the other hand, attempts to
identify underlying causes or factors that control the variation of the quantity of
interest, predict future values of these factors, and use these predictions in a model
to predict future values of the specific quantity of interest.
4. Qualitative models incorporate subjective factors into the forecasting model.
Qualitative models are useful when subjective factors are important and/or in case
that more quantitative data is difficult to obtain. In general, in Operations
Management, longer term forecasts tend to be based more on qualitative rather than
quantitative models.
9. MAD (Mean Absolute Deviation) is the method for determining the accuracy of a
forecast by taking the average of the absolute deviations between the forecasted
values and actual/observed values. MAD is an important method because it
provides a measure of forecast accuracy that can be easily calculated. Furthermore,
in most practical cases, a good estimate of the standard deviation of the forecast
error, eeethat characterizes the variability in the observed quantity, can be obtained
from MAD through the equation: eee MAD.
16. Any functional relationship y = f(x) defines a causal relationship between variables
x and y, in the sense that knowledge of the value of x, allows the determination of
the value of y. Hence, x is characterized as the independent variable and y is
characterized as the dependent variable).
Chapter 5 Design of Goods and Services
DISCUSSION QUESTIONS
2. Explicit documentation accomplishes two things:
(a) it provides the information necessary to produce the product in the appropriate
fashion.
(b) if the product we produce does not perform as we anticipated, the
documentation provides the basis for finding and correcting the problems in a
logical manner.
4. Configuration management is a system by which a product’s planned and changing
configurations are managed. Such a system is of particular value where the product
is rapidly and continually evolving or where safety is a particular issue. Examples
of industries that practice configuration management include those who
manufacture airplanes or microcomputers.
6. Group technology is basically a manufacturing practice that encourages similar
components to be produced by the same process in the same work area. Successful
implementation leads to:
(a) improved product design
(b) reduced raw material and parts purchases
(c) simplified production and planning
(d) improved routing and machine loading
(e) reduced tooling setup time, work-in-process inventory, and production time
(f) a systematic way to reduce component proliferation by reviewing existing
component designs to ascertain if an existing component can be used in a new
design.
10. Product selection and design is plays a crucial role for the quality image projected
by any given company, because one of the basic ways to define quality is through
the intended product functionality and the way/degree in which the actual product
supports this functionality (i.e., product functional specifications and conformance
to these specifications). Apparently, both of these issues are strongly determined at
the product design stage.
12. Configuration management is used by every automobile manufacturer to track all of
the changes between and during a model year. Notice that when ordering a spare
part, companies use the car model and the year it was produced, but also, quite
often, they will use the VIN (vehicle identification number). This information
allows the manufacturer to trace the particular lot in which the car was produced,
and therefore, ship out the exact type of the required spare part that fits this
particular version of the model.
PROBLEMS
CASE STUDY 2
PRODUCT DESIGN AT REGAL MARINE
1. The concept of product life applies to Regal Marine because Regal is constantly
under pressure to introduce new products – and those products have life cycles
of relatively few years. As it is suggested in the text material, it is a matter of
typically less than five years before a boat is out of style and its life cycle
terminated.
2. Regal Marine uses a strategy of product differentiation, which constantly
introduces new products with new innovations and new styling to stay
competitive in the luxury performance boat market. Some of these new designs
are enhancements or migrations of older ones.
3. The cost and time saving at Regal Marine through use of CAD is typical of the
use of CAD everywhere. It allows a variety of designs and styles to be tested
very fast and economically. The ratio of savings of engineering talent is about
four to one. Hence,, it allows them to be creative, both, economically and
rapidly.
4. The payoff from CAD is not only evident in efficiency, creative designs, and
styling but by production of the control code – i.e., software - necessary for the
numerical machines, used in the production operations of Regal Marine. CAD
also provides, as a by-product, very effective and comprehensive documentation
of design variables.
Extra Credit (40%)
CASE STUDY: SOUTHWESTERN UNIVERSITY
1. Develop a forecasting model using linear regression to project attendance
through 2002.
Since the attendance of the different games presents strong systematic
fluctuation from game to game – i.e., seasonalities – a different prediction
model must be built for each particular game in the season, if the used approach
is linear regression (there are other more sophisticated approaches, like Winter’s
method, that account for the seasonality effects in a single model).
Below we show the detailed calculation for the homecoming game (game 2)
only:
Year (Xi)
1995
1996
1997
1998
1999
2000
Sum
Average
Sxx =
Sxy =
Xi
1
2
3
4
5
6
21
3.5
Attendance (Yi)
39800
40200
46500
46100
48200
50100
270900
45150
91-(21^2)/6 =
985700-21*270900/6 =
Xi^2
1
4
9
16
25
36
91
Xi*Yi
39800
80400
139500
184400
241000
300600
985700
17.5
37550
  Sxy/Sxx =
37550/17.5 =
2145.714
  E[Y]-  *E[X] = 45150 - 2145.714*(3.5) =
Simple linear regression model:
Regression line:
37640
y i   o   1 xi   i
Y = 37640 + 2145.7*X
Regression on Number of Attendance
60000
50000
40000
30000
20000
10000
0
y = 2145.7x + 37640
R2 = 0.8987
Year
(Xi)
1995
1996
The summary of all forecasts are as follow:
1997
1998
1999
2000
Game
1
2
3
4
5
Total
Model
y = 30,713 + 2,534x
y = 37,640 + 2,146x
y = 36,940 + 1,560x
y = 22,567 + 2,143x
y = 30,440 + 3,146x
Forecasts
2001
2002
48,453
50,988
52,660
54,806
47,860
49,420
37,567
39,710
52,460
55,606
239,000
250,530
R2
0.92
0.9
0.91
0.88
0.93
2. What revenues are to be expected in 2001 and 2002?
Revenue in 2001 = (239,000)($20/ticket) = $4,780,000
Revenue in 2002 = (250,530)($21/ticket) = $5,261,130
3. Discuss the school’s options.
Since the forecast of the 2002 attendance for games 2 and 5 exceeds stadium
capacity, the school should seriously consider the expansion of the stadium
capacity.