Case Study Background: American International Automotive Industries (AIAI) manufactures auto and truck engine, transmission, and chassis parts for manufacturers and repair companies in the United States, South America, Canada, Mexico, Asia and Europe. The company transports to its foreign markets by container ships. The company wishes to expand its business & select site for new European warehouse/ distribution center. The site should be selected such that it has minimum distance from the cities where supply is to be done to seven major customers. Quantitative analysis: http://www.prenhall.com/divisions/bp/app/russellcd/PROTECT/CHAPTERS/CHAP09/HEAD06.HTM Plant sites (x, y) Load Distribution center sites (x, y) Vienna          (300,   60) 160 Dresden                    (225, 225) Leipzig        (180,   225) 100 Lodz                          (420, 250) Budapest     (390, 50) 180 Hamburg                    (90, 340) Prague         (240, 160) 210 Gdansk                     (370, 360) Krakow       (400,   170) 90 Frankfurt                    (40, 160) Munich        (150,   60) 120 Frankfurt     (40, 160) 50 · Using the load-distance technique: Comparative chart analysis was used to identify the site of distribution that is placed optimally w.r.t the customer sites.The five potential sites were Dresden, Lodz, Hamburg, Gdansk, and Frankfurt. & customer locations were Vienna, Leipzig, Budapest, Prague, Krakow, Munich, and Frankfurt. The distances of all customer location from each distribution site were obtained using standard map of Europe. The data is represented in the form of cross table as shown below. Sites Distance in miles No. of containers to be shipped to the following places time taken to reach Vienna Leipzig Budapest Prague Krakow Munich Frankfurt Total Dresdon miles 308 74 426 98.4 325 286 288 1805.4 time 5 hr 40 min 1 hr 22 min 7 hr 13 min 2 hr 5 hr 22 min 4 hr 34 min 4 hr 34 min Lodz miles 365 385 484 339 164 631 609 2977 time 6 hr 48 min 6 hr 14 min 8 hr 18 min 6 hr 56 min 3 hr 26 min 9 hr 51 min 9 hr 31 min Hamburg miles 610 246 732 404 562 483 310 3347 time 10 hr 13 min 4 hr 4 min 11 hr 48 min 6 hr 56 min 9 hr 7 hr 39 min 5 hr 5 min Gdansk miles 569 456 689 545 368 702 680 4009 time 10 h 4 min 7 hr 58 min 11 hr 37 min 9 hr 32 min 6 hr 38 min 11 hr 36 min 11 hr 17 min Frankfurt miles 446 243 601 321 605 244 0 2460 time 7 hr 17 min 3 hr 55 min 9 hr 30 min 5 hr 19 min 9 hr 28 min 4 hr - This table suggest that Dresdon could be an ideal site from where customer’s location is nearby, Given that there is uniform supply to each customer location. . Graphical representation further gives clearer picture. However, since the supply is not uniformly distributed there will be different charges involved in shipping of the container site is assumed that shipping container costs Rs X/ mile & that this price is uniform throughout Europe. Hence it is not possible to identify the distribution site solely using Table -1. T ...

1. Case Study
Background:
American International Automotive Industries (AIAI)
manufactures auto and truck engine, transmission, and chassis
parts for manufacturers and repair companies in the United
States, South America, Canada, Mexico, Asia and Europe. The
company transports to its foreign markets by container ships.
The company wishes to expand its business & select site for
new European warehouse/ distribution center. The site should
be selected such that it has minimum distance from the cities
where supply is to be done to seven major customers.
Quantitative analysis:
http://www.prenhall.com/divisions/bp/app/russellcd/PROTECT/
CHAPTERS/CHAP09/HEAD06.HTM
Plant sites (x, y)
Load
Distribution center sites (x, y)
Vienna (300, 60)
160
Dresden (225, 225)
Leipzig (180, 225)
100
Lodz (420, 250)
Budapest (390, 50)
180
Hamburg (90, 340)
Prague (240, 160)
210
Gdansk (370, 360)

2. Krakow (400, 170)
90
Frankfurt (40, 160)
Munich (150, 60)
120
Frankfurt (40, 160)
50
· Using the load-distance technique:
Comparative chart analysis was used to identify the site of
distribution that is placed optimally w.r.t the customer sites.The
five potential sites were Dresden, Lodz, Hamburg, Gdansk, and
Frankfurt. & customer locations were Vienna, Leipzig,
Budapest, Prague, Krakow, Munich, and Frankfurt. The
distances of all customer location from each distribution site
were obtained using standard map of Europe. The data is
represented in the form of cross table as shown below.
Sites
Distance in miles
No. of containers to be shipped to the following places
time taken to reach
Vienna
Leipzig
Budapest
Prague
Krakow
Munich
Frankfurt
Total
Dresdon

3. miles
308
74
426
98.4
325
286
288
1805.4
time
5 hr 40 min
1 hr 22 min
7 hr 13 min
2 hr
5 hr 22 min
4 hr 34 min
4 hr 34 min
Lodz
miles
365
385
484
339
164
631
609
2977
time
6 hr 48 min
6 hr 14 min
8 hr 18 min
6 hr 56 min
3 hr 26 min

4. 9 hr 51 min
9 hr 31 min
Hamburg
miles
610
246
732
404
562
483
310
3347
time
10 hr 13 min
4 hr 4 min
11 hr 48 min
6 hr 56 min
9 hr
7 hr 39 min
5 hr 5 min
Gdansk
miles
569
456
689
545
368
702
680
4009
time
10 h 4 min

5. 7 hr 58 min
11 hr 37 min
9 hr 32 min
6 hr 38 min
11 hr 36 min
11 hr 17 min
Frankfurt
miles
446
243
601
321
605
244
0
2460
time
7 hr 17 min
3 hr 55 min
9 hr 30 min
5 hr 19 min
9 hr 28 min
4 hr
-
This table suggest that Dresdon could be an ideal site from
where customer’s location is nearby, Given that there is uniform
supply to each customer location. . Graphical representation
further gives clearer picture.
However, since the supply is not uniformly distributed there
will be different charges involved in shipping of the container
site is assumed that shipping container costs Rs X/ mile & that
this price is uniform throughout Europe.

6. Hence it is not possible to identify the distribution site solely
using Table -1.
Table _ 2 –
Sites
Price factor involved in shipping from the distribution site to
Vienna
Leipzig
Budapest
Prague
Krakow
Munich
Frankfurt
Total
Dresden
49280
7400
76680
20664
29250
34320
14400
231994
Lodz
58400
38500
87120
71190
14760
75720
30450
376140

7. Hamburg
97600
24600
131760
84840
50580
57960
15500
462840
Gdansk
91040
45600
124020
114450
33120
84240
34000
526470
Frankfurt
71360
24300
108180
67410
54450
29280
0
354980
it indicates price factor involvedd in shipping containers to
customer location from each distribution site. This takes care of
supply being on uniform. This is obtained by multiplying each
entry of table 1 by no of containers (specific to the customer
location)
We can use this table to conclude which distribution site
involves minimum price factor. This conclusively suggest that
company AIAI should open distribution site at dresdon

8. Here we have made the assumption that shipping rates are
directly dependent on no of containers.
check this link
http://www74.homepage.villanova.edu/sohail.chaudhry/MBA85
03/
Solution
s/Russell%20Taylor%204th/ismsup05.pdf
Other answer that I found:
Load Distance Technique
I concluded that the best way to approach this problem is to
start with the load-distance technique. The work is shown in
Exhibit A. This is more unique than the Center of Gravity model
because this formula takes into account distances and weights
between facilities and does an individual analysis for each site.
A Center of Gravity equation on the other hand, does an
analysis where all sites are averaged and a central location is
had. The load distance technique shows the plotting of each of
the seven customer locations, their x/y map coordinates that
show on a graph, and also the five potential site locations and
their corresponding x/y map coordinates. It also shows the
number of containers delivered to each customer per month. The
OM tool was really helpful with this calculation because it

9. calculates between the existing customer facilities and the
proposed sites to assign a load-distance value to each of the
potential locations.
Dresden is the best site based on using the load distance
technique. Dresden is the site with the lightest load distance
value of 133,161.0. Looking at a map of Europe, I was able to
see that Dresden is centrally located among AIAI’s major
customers in Vienna, Leipzig, Budapest, Prague, Krakow,
Munich, and Frankfurt which is also attractive for a new site.
Also, other factors should be taken under consideration when
looking at Dresden. It was mentioned in the text of the case
problem that AIAI currently ships into the port of Hamburg, so
a warehouse/distribution center there would eliminate transport
from the port of entry to a distribution center at Dresden or
anywhere else.
Based on the load distance technique, Hamburg is the worst
consideration for a new site, but is close to the port, Hamburg
might be a more attractive choice. On the other hand, looking at
a map of Europe, Dresden is closer to the plants in Vienna and
Budapest, and there is a possibility that these plants will
continuously need to be replenished with supplies. Another
downside of Dresden for a location is that it is located in old
East Germany, and that area is known problems with decaying
infrastructure, and old agriculture.
Center of Gravity

10. The center of gravity formula is shown in Exhibit B. The OM
tools application was used to calculate the formula. The center
of gravity method does a quantitative analysis of locating a site
at the center of movement in a geographic area. The distances
that are of the result are based on weight and distance and are
placed almost exactly between two or more comparable
coordinates. The OM tool was used to calculate a new x/y
coordinate for the potential warehouse/distribution center. The
calculation of this coordinate is x/y: 266.59/115.60 as shown in
Exhibit B. I looked at each of the five potential site’s
coordinates against the coordinate calculation. The closest
potential site coordinate to the calculated center of gravity will
ultimately determine the best of the five locations to build the
new warehouse/distribution center. Looking at the data, I
determined that Dresden (x/y:225/225) is the best location. The
answer is based on straight-lined decisions, and a real situation
may warrant a slightly different answer because of routes that
may or may not be available.
Distribution of centrewise distance from site to customer's
location
Ditance from the sites
toViennaDresdonLodzHamburgGdanskFrankfurt308.0365.0610.

11. 0569.0446.0Ditance from the sites
toLeipzigDresdonLodzHamburgGdanskFrankfurt74.0385.0246.0
456.0243.0Ditance from the sites
toBudapestDresdonLodzHamburgGdanskFrankfurt426.0484.073
2.0689.0601.0Ditance from the sites
toPragueDresdonLodzHamburgGdanskFrankfurt98.4339.0404.0
545.0321.0Ditance from the sites
toKrakowDresdonLodzHamburgGdanskFrankfurt325.0164.0562.
0368.0605.0Ditance from the sites
toMunichDresdonLodzHamburgGdanskFrankfurt286.0631.0483.
0702.0244.0Ditance from the sites
toFrankfurtDresdonLodzHamburgGdanskFrankfurt288.0609.031
0.0680.00.0
Potential sites
Distance in miles
Prcie factor associated with shipping
Price factor involved in shipping from the distribution site
toViennaDresdenLodzHamburgGdanskFrankfurt49280.058400.0

12. 97600.091040.071360.0Price factor involved in shipping from
the distribution site
toLeipzigDresdenLodzHamburgGdanskFrankfurt7400.038500.02
4600.045600.024300.0Price factor involved in shipping from
the distribution site
toBudapestDresdenLodzHamburgGdanskFrankfurt76680.087120
.0131760.0124020.0108180.0Price factor involved in shipping
from the distribution site
toPragueDresdenLodzHamburgGdanskFrankfurt20664.071190.0
84840.0114450.067410.0Price factor involved in shipping from
the distribution site
toKrakowDresdenLodzHamburgGdanskFrankfurt29250.014760.
050580.033120.054450.0Price factor involved in shipping from
the distribution site
toMunichDresdenLodzHamburgGdanskFrankfurt34320.075720.0
57960.084240.029280.0Price factor involved in shipping from
the distribution site
toFrankfurtDresdenLodzHamburgGdanskFrankfurt14400.030450
.015500.034000.00.0
Scenario: You are an independent consultant, hired by the Vice

13. President of Construction, American International Automotive
Industries (AIAI). Review Case Problem S7-1. Conduct an
appropriate quantitative analysis and provide the vice president
with a decision support paper addressing the issues within the
Case Problem.
Specific guidance: You are expected to use the quantitative
analysis methods within this module to arrive at conclusions
and provide supported recommendations within your formal
paper. You should select appropriate graphical presentation
methodologies to present this material within the paper. Include
all computation materials as appendices to the completed
report.
CASE PROBLEM S7.1
Selecting a European Distribution Center Site for American
International Automotive Industries
American International Automotive Industries (AIAI)
manufactures auto and truck engine, transmission, and chassis
parts for manufacturers and repair companies in the United
States, South America, Canada, Mexico, Asia, and Europe. The
company transports to its foreign markets by container ships. To
serve its customers in South America and Asia, AIAI has large
warehouse/distribution centers. In Europe it ships into Hamburg
and Gdansk, where it has contracted with independent
distribution companies to deliver its products to customers

14. throughout Europe. However, AIAI has been displeased with a
recent history of late deliveries and rough handling of its
products. For a time AIAI was not overly concerned since its
European market wasn't too big and its European customers
didn't complain. In addition, it had more pressing supply chain
problems elsewhere. In the past five years, since trade barriers
have fallen in Europe and Eastern European markets have
opened up, its Europeans business has expanded, as has new
competition, and its customers have become more demanding
and quality conscious. As a result, AIAI has initiated the
process to select a site for a new European
warehouse/distribution center. Although it provides parts to a
number of smaller truck and auto maintenance and service
centers in Europe, it has seven major customers—auto and truck
manufacturers—in Vienna, Leipzig, Budapest, Prague, Krakow,
Munich, and Frankfurt. Its customers in Vienna and Budapest
have adopted manufacturing processes requiring continuous
replenishment of parts and materials.
AIAI's European headquarters is in Hamburg. The vice-
president for construction and development in Dayton, Ohio,
has asked the Hamburg office to do a preliminary site search
based on location, geography, transportation, proximity to
customers, and costs. The Hamburg office has identified five
potential sites in Dresden, Lodz, Hamburg, Gdansk, and
Frankfurt. The Hamburg office has forwarded information about

15. each of these sites to corporate headquarters, including
forecasts of the number of containers shipped annually to each
customer as follows: Vienna, 160; Leipzig, 100; Budapest, 180;
Prague, 210; Krakow, 90; Munich, 120; and Frankfurt, 50.
When the vice-president of construction in Dayton received this
information, he pulled out his map of Europe and began to study
the sites.
Assist AIAI with its site selection process in Europe.
Recommend a site form the five possibilities, and indicate what
other location factors you might consider in the selection
process.
· APA format
· 2.5 pages, Cover and references not counted
· use Russell, Operations Management, 8e chapter 7 Operational
Decision-Making Tools: Facility Location Models as one of the
reference.
· The template bellow is just an example of how the assignment
should be presented like.

16. Enter Project Title here
QSO 600: Operations Management
Enter session and section number here
School name
professor’s title and name here
Enter student name here.
Enter date here. Use full alphanumeric date (i.e. February 22,
2014)
QSO 600Writing Templateenter session here

17. Executive Summary
Briefly summarize the purpose, background, analysis
methodology, task requirements, key findings and
recommendations.
Executive Summary is the preferred methodology in business
and government. You may use Abstract, but if that choice is
made; you shall include a Key Word Summary.
An executive summary or abstract is required if the body
content is four (4) or more pages in length.
Key Word Summary: Note: if this is an abstract include a key
word summary here. If this is an executive summary do NOT
include the Key Word Summary. The Key Word Summary
contains those words which are key or central to the topic of the
paper.
Table of Contents
Executive Summaryi
Purpose3
Background3
Task Issue 13
Task Issue 1a.3
Task Issue 1b.3
Task Issue 23

18. Task Issue 33
Summary and Recommendations3
Summary.4
Recommendations.4
Bibliography5
References6
Abbreviations and Acronyms7
A TOC is required if the body text content exceeds 10 pages.
i
Purpose
Define the purpose of the paper for the reader. Refer to the task
scenario for this.Background
Provide the reader with the background information that led to
the development of the issues at hand and why the paper has
been produced, i.e. who tasked this project and what was
tasked. Again, refer to the scenario.Task Issue 1
Begin defining or addressing each of the task issues in
sequential order of the original task requirements. Paraphrase or
re-state from the tasking and then provide the detailed
responses. Use sub-headings of paragraphs as necessary or
appropriate. Be sure to utilize in text citations such as this
(Craig, 2013). Note replace the headings levels used in the

19. example in each paragraph with a one word or short phrase (2 –
4 words) that describe the paragraph’s content or purpose, i.e.
Hiring Practices.Task Issue 1a.
If a topic requires subdivision, then use of Heading Level 2 is
appropriate. Note, that if one subheading or Heading Level 2
entry is used, then there must be two sub-headings using
Heading Level 2.Task Issue 1b.
See task issue 1a for complete discussion.Task Issue 2
Complete as required.Task Issue 3
Complete as required. Add additional paragraph level headings
as necessary to support the topics within the body of the paper.
Add additional paragraph level headings as required.Summary
and Recommendations
Briefly summarize the key points that have been developed
within the paper. (Public, 2010). Add recommendations in this
section as a subparagraph if required by the tasking. Do so by
adding a sub-paragraph level (meaning heading 2 under styles).
Note: a heading level entry must be followed by at least two (2)
full lines of text. If this is not possible prior to an automatic
page break then force a page break by using the Insert page
break command. Summary.
Summarize key points and findings of the analysis. A very key
point in writing: in qualitative analysis papers, such as in this
course, only summaries can be provided. In quantitative
analysis work (i.e. number crunching scientific methodology

20. using statistical analysis) conclusions may be reached from the
resulting data analysis.Recommendations.
Be specific in your recommendations. Include courses of action
(COA), steps, procedures to be taken, etc.
Bibliography
Craig, C. (2013). Writing Tips. Tmbuktoo, : DoWap Publishers.
Public, J. (2010). How to Write a Report. Department of
Homeland Security, US Government. Washington, D. C.: US
Government Printing Office. Retrieved February 28, 2013, from
www.dhs.gov
Note: the above table has been created using the tools in Word
to create the in text citation and then the bibliography, refer to
Word Help to Create In text Citations and Bibliographies. You
may delete the examples in one of two ways. The first is to
remove the citation that is within the text. Highlight and delete.
The second is after you have created your bibliography, click on
the table, once in the table, then highlight and delete the
examples above.
Abbreviations and Acronyms
APA – American Psychological Association
FBI – Federal Bureau of Investigation
FEMA – Federal Emergency Management Agency

21. Radar – Radio Detection and Ranging
TOC - Table of Contents
Note that the listing is in alphabetical order of the abbreviation
or acronym. Not all abbreviations are acronyms. Radar is an
acronym that has become an actual word. RADAR stands for
Radio Detection and Ranging. The general rule of thumb is
more than four (4) abbreviations or acronyms a definitions page
becomes a requirement.