chapter 6-scm s06
TRANSCRIPT
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Chapter 6: Supply ChainManagement (SCM)
IE 3265 POM
R. R. LindekeUMD-MIE
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Topics For Discussion: Defining the issues of SCM
Major Players
How we can work in this new model Vender relationships
Data Management
Major Issues: Bullwhip effect Transportation problems
Location issues
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What is SCM? Supply Chain management deals with the control of
materials, information, and financial flows in a networkconsisting of suppliers, manufacturers, distributors, andcustomers (Stanford Supply Chain Forum Website)
Call it distribution or logistics or supply chainmanagement... In industry after industry . . . executiveshave plucked this once dismal discipline off the loadingdock and placed it near the top of the corporate agenda.Hard-pressed to knock out competitors on quality orprice, companies are trying to gain an edge through theirability to deliver the right stuff in the right amount oftime (Fortune Magazine, 1994)
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Growing Interest in SCM Why? As manufacturing becomes more efficient (or
is outsourced), companies look for ways toreduce costs
Several significant success stories: Efficient SCM at Walmart, HP, Dell Computer
SCM considers the broad, integrated, view ofmaterials management from purchasing
through distribution The huge growth of interest in the web has
spawned web-based models for supplychains: from dot com retailers to B-2-B
business models
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Mass Customization:
Designing Final Choices into Supply Chains Several companies have been able to cut
costs and improve service by postponing thefinal configuration of the product until thelatest possible point in the supply chain.Examples: Hewlett Packard printer configuration
Postponement of final programming ofsemiconductor devices all routines loaded, onlycertain ones activated
Assemble to order rather than assemble to stock(Dell Computer)
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Design For Logistics: Many firms now consider SCM issues in the
design phase of product development One example is IKEA whose furniture comes
in simple to assemble kits that allows them tostore the furniture in the same warehouse-like locations where they are displayed andsold
Shipping container designs for FedEx and UPS airfreight Dunnage control in Big Auto
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Efficient Design of the Supplier Base
Part of streamlining the supply chain is reducingthe number and variety of suppliers
The Japanese have been very successful in thisarena (theyre an Island so getting materialsthere has always been a problem)
In the mid 1980s Xerox trimmed its number ofsuppliers from 5,000 to 400.
Overseas suppliers were chosen based on cost
Local suppliers were chosen based on delivery speed
In 1996, Ford Motor reduced their supplier countby more than 60%
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Dell Designs the Ultimate Supply Chain!
Dell Computer has been one of the mostsuccessful PC retailers. Why? To solve theproblem of inventory becoming obsolete,Dells solution: Dont keep any inventory! -All PCs are made
to order and parts shipped directly frommanufacturers when possible.
Compare to the experience of CompaqCorporation initial success selling throughlow cost retail warehouses but they did notgarner web-based sales
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Data Exchange A Critical Idea EDI: Electronic Data Interchange
Involves the Transmission of documents
electronically in a predetermined formatfrom company to company. (Not webbased.)
The formats are complex andexpensive. It appears to be on thedecline as web-based systems grow.
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Data and Products E-Tailing E-tailing: Direct to customer sales on the web
the so-called Click & Mortor retail model Perhaps best known e-tailer is Amazon.com,
originally a web-based discount book seller Today, Amazon.com sells a wide range of
products (we can think of many, many similarorganizations)
Amazon and others spawned so called dotcom stock explosion in the NASDAQ (1997 to
April, 2000) Today, many traditional bricks and mortar
retailers also offer sales over the web, often
at lower prices
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Dealing with Data the modern way B2B (business to business) supply chain
management:
While not as visible and sexy as E-tailing, itappears that B2B supply chain management is thetrue growth industry!
Web searches yield over 80 matches for supply
chain software providers. Some of the majorplayers in this market segment include:
Agile Softwarebased in Silicon Valley.
i2 Technologiesbased in Dallas.
Aribabased in Silicon Valley
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Data Transfer in Supply Chains: Vendor
Managed Inventory (the real solution?) Walmart and P & G
Target and Pepsi/Coke
But Barilla SpA. An Italian pasta producerpioneered the use of VMI (Vendor ManagedInventory)
They obtained sales data directly from distributorsand decide on delivery sizes based on that
information This is in opposition to allowing distributors (or even
retailers) to independently decide on order sizes!
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Order Growth The Bullwhip Effect
An Important issue
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Information Transfer in Supply
Chains: cause of The Bullwhip Effect First noticed by P&G executives examining
the order patterns for Pampers disposablediapers.
They noticed that order variation increaseddramatically as one moved from retailers todistributors to the factory.
The causes are not completely understood
but have to do with batching of orders andbuilding in safety stock at each level Problem: increases the difficulty of planning
at the factory level
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There has been a Revitalization in the
Analytical Tools needed to Support SCM Inventory management and demand
forecasting models such as those discussed in
this course The transportation problem and more general
network formulations for describing flow ofgoods in a complex system
Analytical methods for determining deliveryroutes for product distribution optimallocation of new resources
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Focusing on the Distribution Problem:
The Goal is to reduce totaltransportation costs throughout the
supply chain Usually solved with some approach to
the Transportation Problem
Our approach will be the BalancedMatrix model
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Lets do one, by example:
\To
FromAlbuquerque Boston Cleveland Capacity
Des Moines$5 $4 $3 100
Evansville$8 $4 $3
300
Ft.Lauderdale
$9 $7 $5300
Demand 300 200 200/700
700/
Cost of moving aunit of productfrom Row tocolumn location
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In the TransportationProblem:
We must have a Supply/Demandbalance to solve
In this problem that requirement is met
If it is not met, we must createDummy sources (at $0 move costs) or
Dummy Sinks (also at $0 move costs)to achieve the require S/D balance
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The Transportation problem:
Goal is to minimize the total cost of shipping
We will allocate products to cells any
allocation means the row resource will shipproduct to the column demand
The process is an iterative one that requires afeasible starting point
Can start by using NW Corner approach
Can start using a more structured VAM (VogelApproximation method)
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Starting with a VAM Solutiontechnique:
Determine Row Penalty number (PNi)the differencebetween lowest and 2nd lowest cost in row Here: R1 is 1; R2 is 1: R3 is 2
Determine Column Penalty Number (PNj) thedifference between the lowest and 2nd lowest col.Cost Here: C1: 3; C2: 0; C3: 0
Choose R or C with greatest penalty cost here is C1
If there is a tie, break tie by choosing C or R with smallestcosts Max out the allocation in chosen C or R at lowest cost cell
then x-out the C or R
And so on after allocation (after we recompute PNs!)
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Phase 1 of VAM:
Step A B C PNr1 PNr2 PNr3
DM $5100
$4 $3 1 X-out -- --
E $8 $4200
$3
1001 1 5 x-out
FL $9200
$7 $5
1002 2 4
PNc1 3 0 0
PNc2 1 3 xout 2
1 -- 2
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Costing The model:
Current: 100*5 + 200*9 +200*4 + 100*3 + 100*5 =
$3900
Before proceeding, check if the Feasiblesolution is (or isnt) degenerate: Number of allocation must be at least: m +n - 1 =
3 + 3 - 1 = 5 (we have 5 is the above set so thesolution is not degenerate! See next slide if it was)
Now, we must determine if its optimal? We must continue to a second phase to
determine this!
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Dealing with Degeneracy (when it isfound)
We must allocate a very small amount of materialmovement (call it ) to any independent cell
An independent cell is any one where we can notcomplete a stepping motion of only horizontal andvertical movements through filled cells to return to theoriginating cell We call this the -path. (this would be done by alternating adding or
subtracting assignments of material to any filled cell we step on) Note any cell were a path can be build is a dependent cell
We would add sufficients to reach allocated cells countof m + n 1 number (make the solution non-degenerate)
Here since R1C1 is independent check for yourself wewill fill it with units this makes our solution non-degenerate 5 cells are allocated!
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Entering Phase II:Determining Optimality
We will explore the MODI (modifieddistribution) algorithm
After finding a non-degenerate initial solution,add a row of Kjs and a column of Ris to theMatrix
To begin, Assign a zero value to any R or Kposition
For each allocated cell, the followingexpression must be satisfied: Ri + Kj + ci,j = 0
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Starting MODI with a possibleR/K allocation:
Kj
Ri
A B C
-5 -2 -1
DM0
$5
100
$4 +2 $3 +2 100
E-2
$8 +1 $4
200
$3
100
300
FL-4
$9
200
$7 +1 $5
100
300
Demand: 300 200 200
Indicator cost for this
cell (= R+K+c)
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MODI continued:
Examine all indicator values for empty cells if allare non-negative the solution is optimal
If some are negative then develop a -path
beginning at most negative cell (here is R3C3) Complete the -path by stepping only to filled cells
(and pivoting) while alternatively subtracting thenadding allocation
After completing the path, determine the - cellwith the smallest quantity and choose its value for
substitute it along the whole path
Note here: all indicators are positive thus we havethe optimal solution!
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Forming the -Path (starts in R2C3)
Kj
Ri
A B C
-5 -4 -3
DM0
$5 +
$4 -
100
$3
Ind: 0
100
E
0
$8
Ind: +3
$4 +
100
$3 -
200
300
FL-4
$9 -
300
$7
Ind: -1
$5 +
Ind: -2
300
Demand: 300 200 200
Smallest - Allocated amount
if we had erroneously allocated as seen below and requiring an
addition
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After 100 unit re-allocation nowrecompute Rs and Ks & Indicators
Kj
Ri
A B C
Cap.-4 -1 0
DM-1
$5
+100$4 +2 $3 +2 100
E-3
$8 +1 $4
200
$3
100
300
FL-5
$9
200
$7 +1 $5
100
300
Demand: 300 200 200
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Looking at this Matrix
All indicators are now positive this indicatesan optimal solution!
Note this agrees with optimal solution foundearlier!!!
Relax value to zero makes cell 1,1allocation 100 units
Optimal transportation cost is: 5*100 + 4*200 + 3*100 + 9*200 + 5*100 =
3900
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Lets try one:
/To
Fr/D E F G Cap.
A 8 6 4 2 4
B10 6 6 2
3
C4 2 3 8
6
Demand 3 3 3 4/13
13/
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But the TransportationProblem can be solved by LP!
Define anObjective
Function:
Subject to:
1 1
:
is cell cost and is amount moved
m n
ij iji j
ij ij
c X
where
c X
1
1
i
j
for 1 i m
for 1 j nwhere:
a are all shipment from a source (capacity)
b are all shipments into a "sink" (Demand)
n
ij ij
m
ij ji
X a
X b
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Our Example (by LP Solver)
Variables XDM-A XDM-B XDM-C XE-A XE-B XE-C XFL-A XFL-B XFL-C
Values: 0 0 0 0 0 0 0 0 0
V*C 0 0 0 0 0 0 0 0 0 OBJ.Fn.
Costs: 5 4 3 8 4 3 9 7 5 0
CapC1 1 1 1 0 100
CapC2 1 1 1 0 300
CapC3 1 1 1 0 300
DemC1 1 1 1 0 300
DemC2 1 1 1 0 200
DemC3 1 1 1 0 200
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Applying Solver:
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Examining Results:
Optimal Value = $3900 (as we foundby hand!)
Ship: 100 DM-A; 200 FL-A; 200 E-B;100 E-C; 100 FL-C
All as we found using the VAM Heuristic
Much Faster and easier using LP!
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Expansion to Transshipment Problem
When a system is allowed to use intermediatewarehousing sites they are Source sites oreven Sink sites in regular transportation
problem for reducing the total cost oftransportation we call the problem thetransshipment network problem
We require more costs to be obtained buttypically, in most complex S. Chains,companies find savings of from 7 to 15% (ormore) in implementations that allowtransshipment
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Expansion to Transshipment Problem
In the general Transshipment problem the transport networkis expanded to allow movement between sources and
between sinks (and even back to other sources)
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Expansion to Transshipment Problem
Extracted from: J.P. Ignizio, LinearProgramming inSingle- & Multiple-Objective Systems,Prentice Hall 1982
The originaltransportationproblem
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Another Level of Transport thedelivery route problem
This problem is usually one of very large scale(classically called the Traveling Salesman Problem)
Because of this, we typically can not find an
absolutely optimal solution but rather only nearoptimal solution as seen in our textbook Here, the knowns are the costs of travel from point to point
throughout the network and we try to save costs byganging up trips
Solution typically follows along a line of attack basedon the Assignment Problem
See Handout, focus on the Shortest Route Problem
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Delivery Optimization:
Realistically, a delivery vehicle canonly carry so much so this may
reduce effectiveness of solutions Deliverys take Real Time again
this must be considered duringscheduling and routing
Loading of vehicles is very critical tocontrol step 2 time load in reversedelivery order!
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Looking at the Locating of NewFacilities:
Considerations:
Labor Climate
Transportation issues: Proximity to markets
Proximity to suppliers & resources
Proximity to parent company (sharingexpertise, purchasing, drop routing) could beplus or minus!
Quality of transportation system
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Looking at the Locating of NewFacilities:
Consideration, cont. Costs to operate (utilities, taxes, real
estate costs, construction) Expansion considerations
Room available for growth?
Construction to modify structure?
Any local incentives to re-locate? Quality of Life (schools, recreational
possibilities, health care cost, availability)
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Looking at the Locating of NewFacilities:
Most organization compare several alternatives
They identify weighting factors for the characteristicsthen narrow choices 1st consider regions 2nd narrow search to communities
3rd consider specific sites
Done by collecting data addressing the various factors understudy
After data is collected and weighted, make selection(typically by starting with quantitative decision followwith qualitative analysis)
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Lets Consider an Example:
DC 1
Store C
Store E
Store G
Store FDC 2
Store D
Store A
Store B
(where should we put ournew Distribution Center?)
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Given this information:
Store Location (X,Y) C. Sales
A (2.5, 2.5) 5
B (2.5, 4.5) 2Ca (5.5, 4.5) 10
D (5, 2) 7
E (8, 5) 10Fb (7, 2) 20
G (9, 3.5) 14
a
Site of Possible DC 1;b
Site of Possible DC 2
S l ti i T f T t ti
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Solution is a Type of TransportationMinimization:Using Either Euclidian or Recta-linear offsets
Euclidean Distance:
Recta-Linear (RL) Distance:
2 2
: X's or Y's are map coordinates
of stores or Distribution Center
j jeuclid i DC i DC d X X Y Y
here
j jRL i DC i DCd X X Y Y
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Now What?
Best Location is the one that minimizes thesum of the total needs of all Demands times
the travel distances involved:
i
for all Sinks
and each possible new Source
ji euclid
all
D d
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Leading to this analysis:
DC 1 5.5 4.5
DC 2 7 2
STORE X Location Y Location D Euclid 1 D Euclid 2 D RL 1 D RL 2 Demand D*DE 1 D*DE 2 D*Drl 1 D*Drl 2
A 2.5 2.5 3.605551 4.527693 5 5 5 18.02776 22.63846 25 25
B 2.5 4.5 3 5.147815 3 7 2 6 10.29563 6 14
C 5.5 4.5 0 2.915476 0 4 10 0 29.15476 0 40
D 5 2 2.54951 2 3 2 7 17.84657 14 21 14
E 8 5 2.54951 3.162278 3 4 10 25.4951 31.62278 30 40
F 7 2 2.915476 0 4 0 20 58.30952 0 80 0
G 9 3.5 3.640055 2.5 4.5 3.5 14 50.96077 35 63 49
176.639 142.711 225 182
From the Analysis: DC 2 minimizes costs
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But is this the Optimal location?
Perhaps we could place the Center at theMedian of all the current demand locations?
In an RL sense, form the CumulativeWeighting (Cum. Demand)
1st: order each target location in increasinglevel of X and then Y
Determine the average of this CumWt for X &Y and place location the is the same as thesite that first exceeds this value
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C. Wt. Average is 34
Store Dem. Xcoor
C.Wt.
Sel. Store Dem. Ycoor
C.Wt.
Sel
A 5 2.5 5 D 7 2 7
B 2 2.5 7 F 20 2 27
D 7 5 14 A 5 2.5 32 *
C 10 5.5 24 * G 14 3.5 46 **
F 20 7 44 ** B 2 4.5 48
E 10 8 54 C 10 4.5 58
G 14 9 68 E 10 5 68
Locate at: 7 (in X) and 3.5 (in Y) as a rule*
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Optimization using Euclidian Distances:
1st Compute the Center of Gravity:
for each location i
i i
i
i i
i
D x
X D
D y
Y D
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Optimization:
Start with X*, Y* determined above as Xcur, Ycur
Compute:
Stop iteration when X and Y stop changing
2 2,
:
,
,
,
,
ii
cur i cur i
i i
new
i
i i
new
i
Dg x y
x x y ythen
x g x yx
g x y
y g x yy
g x y
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Trends in Supply Chain Management
Outsourcing of the logistics function(example: Saturn outsourced their logistics
to Ryder Trucks. Outsourcing ofmanufacturing is a major trend these days)
Moving towards more web based
transactions systems Improving the information flows along the
entire chain
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Global Concerns in SCM
Moving manufacturing offshore to savedirect costs complicates and adds
expense to supply chain operations, dueto:
increased inventory in the pipeline
Infrastructure problems Political problems
Dealing with fluctuating exchange rates