Chapter 6-SCM S06

7/30/2019 Chapter 6-SCM S06

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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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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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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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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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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

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Chapter 6-SCM S06