CASE S TUDY Background: American International Automotive Automotive Industries (AIAI) (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 !he compan" compan" transports to its foreign foreign markets #" container ships !he compan" $ishes to expand its #usiness % select site for ne $ European $arehouse& distri#ution center !he site should #e selected such that it has minimum distance from the cities $here suppl" is to #e done to seven ma'or customers uantitative anal"sis
http&&$$$prenhallcom&divisionsp&app&russellcd&*+! http&&$$$prenhallcom&divisionsp&a pp&russellcd&*+! EC!&C-A*!E+S&C-A*./&-EA0.1-!M
x, y) Plant Plan t sites si tes ( x
Load
x, y) Distribution center sites ( x,
160 Vienna
(300, 60)
Dresden
(225, 225)
Lodz
(420, 250)
Ha!urg
(90, 340)
100 Leipzig
(180, 225) 180
Budapest
(390, 50) 210
"rague
(240, 160)
#dans$
(3%0, 360)
90 &ra$o'
(400, 1%0)
ran$urt
(40, 160)
120 *uni+ ran$urt
(150, 60) (40, 160)
50 •
-sing te .oad/distan+e te+niue
Comparative chart anal"sis $as used to identif" the site of distri#ution that is placed optimall" $rt $rt the customer sites!he five potential sites $ere 0resden, 2od3, -am#urg, 4dansk, and 5rankfurt % customer locations $ere 6ienna, 2eip3ig, 7udapest, *rague, 8rako$, Munich, and 5rankfurt !he distances of all customer location from each distri#ution site $ere o#tained using standard map of Europe !he data is represented in the form of cross ta#le as sho$n #elo$
Sites Dresd on &od'
Distance in miles time taken to reach miles time miles time
No. of containers to be shipped to the following places 6ienna
2eip3ig
7udapest
*rague
8rako$
Munich
5rankfurt
308 7 !" #8. 3!$ !8" !88 $ hr 0 % hr !! 7 hr %3 $ hr !! hr 3 hr 3 min min min ! hr min min min 3"$ 38$ 8 33# %" "3% "0# " hr 8 " hr % 8 hr %8 " hr $" 3 hr !" # hr $% # hr 3%
!otal
%80$.
!#77
min -am#urg
miles
time miles
4dansk
5rankfurt
time miles
time
min "%0 !" %0 hr %3 hr min min $"# $" %0 h 7 hr $8 min min " !3 7 hr %7 3 hr $$ min min
min
min 73! 0 %% hr 8 " hr $" min min "8# $$ %% hr 37 # hr 3! min min "0% 3!% # hr 30 $ hr %# min min
min $"! # hr 3"8 " hr 38 min "0$ # hr !8 min
min
min
83 7 hr 3# min 70! %% hr 3" min !
3%0 $ hr $ min "80 %% hr %7 min 0
hr
(
)his table suggest that Dresdon could be an ideal site from where customer*s location is nearb+, -ien that there is uniform suppl+ to each customer location. . -raphical representation further gies clearer picture. /oweer, since the suppl+ is not uniforml+ distributed there will be dierent charges inoled in shipping of the container site is assumed that shipping container costs 1s 2 mile 4 that this price is uniform throughout 5urope. /ence it is not possible to identif+ the distribution site solel+ using )able (%.
Distribution of centrewise distance from site to customer's location Ditance from800 the sites to ienna
Ditance from the sites to &eip'ig
700 "00 Ditance from the sit es to Budapest $00
Ditance from the sit es to rague
Distance in miles 00 300 Ditance from the sites to 9rakow
Ditance from the sites to :unich
!00 %00 Ditance from the 0 sites to 6rankfurt Dresdon &od'
/amburg
-dansk
6rankfurt
otential sites
)able ; ! < Sites
rice factor inoled in shipping from the distribution site to 6ienna
Dresd
#!8
2eip3ig
700
7udapest
7""80
*rague
!0""
8rako$
Munich
!#!$
33!
)otal %00 !3%##
5rankfurt
337
00#
!"0
en &od' -am#urg 4dansk 5rankfurt
0 $80 0 #7"0 0 #%0 0 7%3" 0
38$0 0 !"0 0 $"0 0 !30 0
87%!0
7%%#0
%3%7"0 %!0!0
880 %%$ 0
%08%80
"7%0
0 %7" 0 $0$8 0 33%! 0 $$ 0
0 7$7! 0 $7#" 0 8! 0 !#!8 0
30$0 %$$00 3000 0
37"% 0 "!8 0 $!"7 0 3$#8 0
it indicates price factor inoledd in shipping containers to customer location from each distribution site. )his takes care of suppl+ being on uniform. )his is obtained b+ multipl+ing each entr+ of table % b+ no of containers =speci>c to the customer location? @e can use this table to conclude which distribution site inoles minimum price factor. )his conclusiel+ suggest that compan+ AA should open distribution site at dresdon /ere we hae made the assumption that shipping rates are directl+ dependent on no of containers.
rcie factor associated with shipping %0000 %!0000 %00000 80000 "0000 0000 !0000 0
Dresden
&od'
/amburg
-dansk
6rankfurt
rice factor inoled in shipping from the distribution s ite to ienna rice factor inoled in shipping from the distribution site to &eip'ig rice facto r inoled in s hipping from the distribution s ite to Budap est rice fact or inoled in s hipping from the distribution s ite to ragu e rice factor inoled in shipping from the distribution s ite to 9rakow rice fact or inoled in s hipping from the distribution s ite to unich rice factor inoled in shipping from the distribution s ite to 6rankfurt