CTM

CapableToMatchDr. Joachim AltmeyerRalph SchneiderSAP AG

SAP AG CTM / Dr. Joachim Altmeyer 3/5/99 Slide no. 1

The Inputprioritizeddemands

categorizedsupplies

1.

attributes

attributes

product

2.

product

availability date available quantity

3.

due date required quantity

origin location

5.

4.6.

priority

7.

category

8.

(e.g. nearobsolete,normal, ...)

9.10.11.


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destination location priority

The Application Modelprioritizeddemands

categorizedsuppliesSupply Chain Network

1.2.3.4.5.6.7.8.9.10.

Production Master Data

11.


The Solutioncategorizedsupplies

Capable-to-Match

prioritizeddemands1.2.3.4.5.6.7.8.9.10.

multi-site capacity checkand check of transportation capabilities


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11.

CTM Engine: Capacity / Supply Constraints

demand

no capacityt

no supply

success


CTM Engine: Determination of the Solution Treez

Search by tree exploration using backtracking

z

Constraint Propagation truncation of thesearch tree toreduce the search space

t


Page 3

Data


APO Production Process Model (PPM)zzz

processes

PPM summarizes routing and BOMTime-Phased and Lot-PhasedAlternative Input Components

co-productsR

alternatives in time product procurement

R

(production / external procurement)

z

Co-Products

z

Resources

z

possibility to model bin splitsR

time-continuos (single-activity/multi-activity) bucket resources

Yield for production lines (sequences of process steps )


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R

Time-Dependent Process Parameterz

Time-dependent process parameters for

process

yield duration of an activity

yield 100%

capacity consumption of an activity quantities of input / output components

yield 50%yield 70%

yield 100%

100 %50 %0%

yield (learning curve)

t


Multi-Site Planningz

Transport Lanes directed between two locations time-phased product-dependent transport time transport calendar

May 1999310172330


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1 24 5 6 7 8 911 12 13 14 15 1618 19 20 21 22 2325 26 27 28 29 3031

CTMProcess SAP AG CTM / Dr. Joachim Altmeyer 3/5/99 Slide no. 11

Demand Prioritizationz

prioritizeddemands

Demands from liveCache forecasts

1.

(from APO Demand Planning)

z

2.

sales orders

3.

Prioritization

4.5.

based on

z

6.

demand type

7.

customer priority

8.

product priority

9.

due date

10.11.

Pre-processing step


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demands

Supply Categorizationz

Supplies from liveCache inventory procurement orders

supplies

categorizedsupplies

purchase orders/requisition

excess

manufacturing orders

z

production ordersnormal

planned orders

Categorization based on supply limits for each location

z

target

for each product

Pre-processing step


CTM Engine: Constraint Programmingz

Huge amount of data and largesearch space dedicated server each demand is treated separately

strategiesstrategies

pull approach

zz

constraintconstraintmodelmodelbasicsearchbasic searchgoalsgoals

based on customer needsdownstream

Approach constraint programming goal-oriented programming

Based on ILOGs C++ OptimizationLibraries


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CTMCTMApplicationApplicationModelModel

CTM Engine: Search Strategiessearch

zz

Search Strategies for each supply category

supplies

Usage ofCategorized Supply before production

safetystock

excess

(production) after production

target

normal

beforeproduction

production

afterproduction


CTM Engine: Partial Shipment/Partial Satisfactionz

partial shipment

Partial shipment a demand can be partiallysatisfied (shipped)in time (rest: late demand)

t

time frame can be specified

z

max: 3 days

Partial satisfaction

partial satisfaction

a demand can only be partiallysatisfied

minimum and maximum

min: 50% max: 110%

percentage can be specified

t


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CTM Engine: Late Demand Strategiesz

domino effect

Domino effect

1.

planning immediately with

2.

postponed due date

3.

possible result:

4.

each postponed demand caninfluence the due date of the nextdemand

z

t

airline reservation

Airline reservation

1.

shift to the end of the demand list

2.3.4.5.

t


CTM Engine: APO Decision Cubez

decisions

Three different decisions beingapplied recursively ... consume supply production transport

supply

directassignment

virtualdemand

... build theAPO Decision Cube BOM explosion versusconsuming supply

plant B

demand

plant A

APO Decision Cube

alternative products alternative plants


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demandproduction

virtualdemandtransport

z

demand

Outlook 99


Selection of the Process Flowz

Alternatives for processes production plants

z

transport lanes

In many business scenarios, a complexSupply Chain Network of alternative flowsis built out of the huge amount of decisionalternatives ...

Restricted Supply Chain Network

Supply NetworkConstraints restrictions ofproduction sites(determination ofqualified sites)

... but can be reduced bySupply Network Constraints


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Preferences Based on QuotasNorthNorthAmericaAmericaRouteRoute

z

Possibility touse quotasSouthSouthAmericaAmericaRouteRoute

80 % North America Route

80 %20 %

20 % South America Route


Product / Plant Substitution by Rules

especiallyespeciallyforforcustomercustomerAAproduct substitutionplant substitution

zzz

Product substitution

1.

sequences of substitutions demand dependent

1.

Plant substitution sequences of substitutions demand dependent

2.2.

Combination of Product /Plant Substitution3.3.


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Solution Constraintsz

Supply Network Constraints restrict the set of possible

supply networksupply network constraints

production sites

zz

customer constraints

based on customer

rules

Customer Constraints influence the demand handling based on customer

Rules define production/plansubstitutions

based on demand


BusinessProcess SAP AG CTM / Dr. Joachim Altmeyer 3/5/99 Slide no. 24

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solutions

CTM Complements SNPzzz

z

CTM writes SNP ordersUse of SNP PPMsComplements theSNP with PP/DS features demand tracking time-dependent process parameter

Application generation of constraint forecasts

release DP to SNPCTM planning runrelease SNP to DP

re-planning and incremental planning


CTM as Mid-Term PP/DSzzz

CTM writes PP/DS ordersUse of PP/DS (restricted) PPMsComplements theAPO Supply Network Planning withPP/DS enhancements focus on production planningwith capacity check on activity level

z

Application use of PP/DS resources CTM solution can be used as an initial genomefor the genetic algorithm of the APO PP/DSoptimizer


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CTM Customer Profilez

CTM focus on grading and assemblyproduction processes small set of components High-Tech industries(e.g. semiconductor companies, wafer)

z

steel and paper laptop and PC

Solution for companies which want high customer satisfaction with many constraints finite capacity planning focus on production


Demo


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CTM Demo: Standard ExamplePhone

CTM1Frankfurt

CoreShip

CTM3Austin

Die


CTM Demo: Standard Examplezzzzz

Master DataCTM ScreenDemand PrioritizationSupply CategorizationCTM Run Master Data Checker Demand Prioritization Supply Coordination CTM Engine CTM Messages CTM Result


Page 15

CTM2Madrid

CTM4PaloAlto

CTM

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