Norman M. Sadeh e-Supply Chain Management Laboratory School of Computer Science

University of Minnesota – Digital Technology CenterDecember 2002

Intelligent e-Supply Chain Decision Support

Norman M. SadehNorman M. Sadeh

e-Supply Chain Management Laboratorye-Supply Chain Management LaboratorySchool of Computer Science School of Computer Science Carnegie Mellon UniversityCarnegie Mellon University

Copyright ©2002 Norman Sadeh

Outline Supply Chain Management: New ContextSupply Chain Management: New Context Agent-Based Collaborative Decision SupportAgent-Based Collaborative Decision Support

MascotMascot Available-To-Promise/Capacity-To-Promise Available-To-Promise/Capacity-To-Promise

FunctionalityFunctionality Empirical ResultsEmpirical Results Dynamic Supply Chain Management PracticesDynamic Supply Chain Management Practices

Early ResultsEarly Results TAC’03: A Supply Chain Trading CompetitionTAC’03: A Supply Chain Trading Competition

Summary and Concluding RemarksSummary and Concluding Remarks


Supply Chain Management

Planning and coordinating procurement, production and Planning and coordinating procurement, production and distribution activitiesdistribution activities From raw material suppliers to manufacturers …to From raw material suppliers to manufacturers …to

distribution centers …to retailers and consumersdistribution centers …to retailers and consumers Trillions of dollars annuallyTrillions of dollars annually Good practices directly impact the competitiveness of Good practices directly impact the competitiveness of

companiescompanies Timely and cost-effective delivery of products to Timely and cost-effective delivery of products to

customerscustomers Extends to product design and configurationExtends to product design and configuration


Why is SCM Difficult? Involves multiple organizationsInvolves multiple organizations Each organization tries to satisfy multiple objectives Each organization tries to satisfy multiple objectives

Cost, timeliness, quality, market share, etc.Cost, timeliness, quality, market share, etc. Each organization operates subject to:Each organization operates subject to:

Internal ConsiderationsInternal Considerations::Finite capacity, existing inventory, etc.Finite capacity, existing inventory, etc.

External ConsiderationsExternal ConsiderationsAvailable suppliers and their capacities, order quantities and due Available suppliers and their capacities, order quantities and due

dates, contractual arrangements, transportation constraints, etc.dates, contractual arrangements, transportation constraints, etc. Numerous sources of uncertaintyNumerous sources of uncertainty

Capacity, supplies, demand, etc.Capacity, supplies, demand, etc.


Historical Perspective

Purchasing Production Sales Distribution

MaterialsManagement

ManufacturingManagement

Distribution CustomersSuppliers

SuppliersInternal

Supply ChainCustomers

Buyers/Sellers

Buyers/Sellers

Buyers/Sellers

Buyers/Sellers

InventoryControl

e-Commercee-Markets/Exchanges

e-Supply Chains

Functional Silos

EnterpriseIntegration

Dynamic Internet-enabled

Supply Chain

Supply ChainIntegration


Beyond the Early eMarket Hype Dynamic business practices are mainly confined to Dynamic business practices are mainly confined to

MRO MRO Suppliers don’t like being evaluated solely based on Suppliers don’t like being evaluated solely based on

pricepriceCovisint, E2open exchanges: more emphasis Covisint, E2open exchanges: more emphasis

on supporting collaborationon supporting collaborationRequires richer environmentsRequires richer environments

• Multiple attributes – not just priceMultiple attributes – not just priceLack of adequate standardsLack of adequate standards

Lack of adequate decision support toolsLack of adequate decision support tools Evaluate a large number of optionsEvaluate a large number of options

Standardization efforts are taking timeStandardization efforts are taking time


Some Open Research Issues

Long vs. Short term contractsLong vs. Short term contracts Information exchangeInformation exchange Collaborative decision supportCollaborative decision support Multi-attribute negotiationMulti-attribute negotiation Peer-To-Peer/local view vs. more lobal viewPeer-To-Peer/local view vs. more lobal view

P2P ChallengeP2P Challenge: Coordinating negotiation across : Coordinating negotiation across multiple tiersmultiple tiers

Challenge for the Global ViewChallenge for the Global View: : Creating the right incentives for information sharingCreating the right incentives for information sharing How global? How often do you clear? etc.How global? How often do you clear? etc.


MASCOT: Collaborative Decision Support

Decisions are evaluated in Decisions are evaluated in collaborationcollaboration with with potential business partners potential business partners

Supply chains can be Supply chains can be dynamicallydynamically set up in set up in response to changing market requirementsresponse to changing market requirements

Emphasis on Mixed Initiative Decision Emphasis on Mixed Initiative Decision SupportSupportDon’t try to automate everything!Don’t try to automate everything!


MASCOT Supply Chain Agent

Bidding & Order Mgmt.

Planning & Scheduling

Procurement

BusinessEntity

EnterpriseLevel

MascotAgent

Tier 1Suppliers

eMarket

eMarket

eMarket

Site Level MascotAgent

Site Level MascotAgent

ProspectiveCustomer

Request forQuote

eMarket


MASCOT: Overall Objectives Leverage benefits of finite schedulingLeverage benefits of finite scheduling Rapid and accurate evaluation of partner-dependent Rapid and accurate evaluation of partner-dependent

decisions :decisions :Bids & Requests for QuotesBids & Requests for Quotes

• including real-time ATP/CTPincluding real-time ATP/CTPAlternative product/subcomponent designsAlternative product/subcomponent designsMake-or-buy decisionsMake-or-buy decisions

Customizable mixed-initiative functionalityCustomizable mixed-initiative functionalityCollaborative solution development, workflow Collaborative solution development, workflow

managementmanagement Facilitate integration with legacy systemsFacilitate integration with legacy systems


A Customizable Agent Wrapper

Blackboard

Control KB

Agenda

ControllerControlProfile

GUI

Event Queue

EnterpriseSystem

eMarketPortal

PotentialBusinessPartner

PotentialCustomer

Bidding/Order Mgmt KS

BOM/Flow Config. KS

Demand Explosion KS

Communication KS

Knowledge Sources

Contexts

ExternalSystems

Outgoing messages

Incoming Events

Scheduling/CTP KS

RFQ/Procurement KS

Currentworkingcontext


Main Architectural Features Blackboard Blackboard ContextsContexts: “What-if”: “What-if”

Different assumptions (e.g. demand, resources, Different assumptions (e.g. demand, resources, suppliers) and different solutionssuppliers) and different solutions

Unresolved issues Unresolved issues Extensible set of Knowledge SourcesExtensible set of Knowledge Sources (KSs) (KSs)

Allows for modular & reusable KSsAllows for modular & reusable KSs Provides for easy integration with legacy systemsProvides for easy integration with legacy systems

Mixed Initiative ControlMixed Initiative Control Customizable user profileCustomizable user profile


Unresolved Issues Help keep track of Help keep track of incomplete, inconsistent and incomplete, inconsistent and

unsatisfactoryunsatisfactory aspects of a context solution aspects of a context solution Examples: unprocessed RFQ, insufficient availability Examples: unprocessed RFQ, insufficient availability

of supplies, missed prior delivery commitmentof supplies, missed prior delivery commitment Automatically updatedAutomatically updated as the solution is modified as the solution is modified Supports flexible mixed initiative Supports flexible mixed initiative workflow managementworkflow management

Associated with KS activations, scripts and goalsAssociated with KS activations, scripts and goals


Three Levels of Problem Solving Knowledge Source ActivationsKnowledge Source Activations

e.g. Demand Explosion (RFQ1)e.g. Demand Explosion (RFQ1) ScriptsScripts

e.g. Evaluate (RFQ1) e.g. Evaluate (RFQ1) 1. Copy_Current_Context2. Incorporate(RFQ1)3. Demand_Explosion (RFQ1)4. Reoptimize_Schedule_with_Net_Demand (RFQ1)5. Procure_Subcomponents_Net_Demand(RFQ1)6. etc.

• Goals: Search among multiple options


Mixed Initiative Workflow Management

U/C:Incorporate event

into Context

Blackboard:Update

Unresolved Issues

U/C:Select UnresolvedIssue to Resolve

U/C:Select Resolution

Method

KS:Execute

Resolution Method

Controller:Activate

Resolution Method

U/C:Modify Assumptions

within Context(“What-if”)

ModifiedContext

ModifiedContext

UnresolvedIssue

SelectedUnresolved

Issue

SelectedResolution

Method

ActivatedAgenda

Item

ModifiedCopy ofContext

U/C = User or Controller


Status Customized to support coordination between a machine Customized to support coordination between a machine

shop and a tool shop at Raytheonshop and a tool shop at Raytheon Over 150 machine centers & over 100 peopleOver 150 machine centers & over 100 people 50% of incoming orders require new tools50% of incoming orders require new tools

alternative BOM & process planning optionsalternative BOM & process planning options Reduced tardiness by 23 percentReduced tardiness by 23 percent

Integration of process planning & schedulingIntegration of process planning & schedulingTighter coordinationTighter coordination

Used to study the benefits of different supply chain Used to study the benefits of different supply chain coordination policies and different order promising policiescoordination policies and different order promising policies


Dynamic Supply Chain Coordination

•orders•requests for bid•bid acceptance/rejection•order cancelation/modification

•products•bid submissions•revised delivery dates

Supply chainentity

Supply chainentity

Supply chainentity

Supply chainentity


The Coordination Challenge Generate Generate robust yet competitive and cost-effective robust yet competitive and cost-effective

promise datespromise dates Multi-tier “capacity-to-promise” functionalityMulti-tier “capacity-to-promise” functionality

Sources of Sources of uncertaintyuncertainty are both internal and external are both internal and external incoming orders, supplies, internal capacity, etc.incoming orders, supplies, internal capacity, etc.

Is it possible, through dynamic coordination, to reap Is it possible, through dynamic coordination, to reap the benefits of the benefits of finite schedulingfinite scheduling, while offsetting the , while offsetting the brittlenessbrittleness of its solutions ?of its solutions ?


Real-Time Promising(RTP):General Considerations Net DemandNet Demand: Inventory Allocation & Demand Explosion: Inventory Allocation & Demand Explosion SchedulingScheduling

Available vs. modified capacityAvailable vs. modified capacity Schedule around prior commitments vs. reoptimizationSchedule around prior commitments vs. reoptimization Schedule ReoptimizationSchedule Reoptimization

Assess impact on prior commitmentsAssess impact on prior commitmentsCosts & Priorities: order priorities, late delivery Costs & Priorities: order priorities, late delivery

penalties, inventory costs, etc.penalties, inventory costs, etc.Other Tradeoff: Speed versus “optimality”Other Tradeoff: Speed versus “optimality”

Assess desirability & decide whether to submit quoteAssess desirability & decide whether to submit quote Micro-Boss RTP moduleMicro-Boss RTP module: real-time reoptimization - : real-time reoptimization - user user

specifies desired response time specifies desired response time (Sadeh et al. ‘94-99)(Sadeh et al. ‘94-99)


RTP: Further Refinements

Profitable-To-PromiseProfitable-To-Promise Selective RTP ValidationSelective RTP Validation


Profitable-To-Promise Overall Profit = Total_Revenue - Total_CostsOverall Profit = Total_Revenue - Total_Costs

Total_Revenue: Total_Revenue: Sum over all ordersSum over all orders Total_Costs: Total_Costs: Production costs, inventory costs (raw Production costs, inventory costs (raw

materials, in-process, finished goods), late delivery materials, in-process, finished goods), late delivery penalties, etc.penalties, etc.

Takes into account impact on prior commitmentsTakes into account impact on prior commitmentse.g. late delivery penalty when another order gets e.g. late delivery penalty when another order gets

bumpedbumped Bid only if overall profit increasesBid only if overall profit increases

Other variations can be considered Other variations can be considered e.g. strategic customers, market share considerationse.g. strategic customers, market share considerations


Empirical Study: Multiple RFQ Processing Policies

Response:Response: Always bid - no due date negotiationAlways bid - no due date negotiation Only submit a bid if overall profit increasesOnly submit a bid if overall profit increases Bid conditional on acceptance of possibly relaxed Bid conditional on acceptance of possibly relaxed

promise datepromise date Capacity-To-Promise ComputationCapacity-To-Promise Computation

Leadtime-basedLeadtime-based Local finite capacity scheduling & supply Local finite capacity scheduling & supply

leadtimesleadtimes Coordinated finite capacity schedulingCoordinated finite capacity scheduling


Empirical Study: Assumptions A lot-for-lot make-to-order environmentA lot-for-lot make-to-order environment

Internal sources of uncertainty at each tier due to resource Internal sources of uncertainty at each tier due to resource breakdowns and variations in processing timesbreakdowns and variations in processing times

Stochastic order arrivalStochastic order arrival

Finite capacity schedules regenerated dailyFinite capacity schedules regenerated daily

Micro-Boss scheduling system Micro-Boss scheduling system

JIT objective: minimize sum of tardiness & inventory costsJIT objective: minimize sum of tardiness & inventory costs

Execution priority in accordance with the latest released Execution priority in accordance with the latest released scheduleschedule


Evaluation Criteria

Number of bids refused or rejectedNumber of bids refused or rejected Number of tardy orders Number of tardy orders Average utilization of the most utilized resourceAverage utilization of the most utilized resource Average supply chain leadtimesAverage supply chain leadtimes Average due-date adjustment (as part of bid negotiation)Average due-date adjustment (as part of bid negotiation) Profit (sales revenue minus costs)Profit (sales revenue minus costs)

Total in-system inventory costs (WIP and finished goods)Total in-system inventory costs (WIP and finished goods) Total tardiness costsTotal tardiness costs

Promise date accuracyPromise date accuracy


Basic Supply Chain Configuration

Agent 1

Agent 2

Agent 3

Agent 4

Agent 5

Agent 9

Agent 10

Agent 6

Agent 7

Agent 8

Externalcustomers

Supply chain

Tier3 Tier2 Tier1


Benefits of Dynamic Finite Capacity Coordination

0

3

6

9

12

15

18

Leadtime-based Local FCS Coordinated FCS

Av

era

ge

le

ad

tim

e (

da

ys

) (i

n b

ars

)

-2000000

-1000000

0

1000000

2000000

3000000

4000000

Pro

fit

(in

hig

h-l

ow

-lin

es

)

Case with competition and negotiable promise dates


Benefits of Dynamic Coordination - Contd.

-6000000

-4000000

-2000000

0

2000000

4000000

6000000

0,40 0,60 0,80 1,00 1,20

Nominal load

Av

era

ge

pro

fit

Leadtime-basedLocal FCSCoordinated FCS


Dynamic Supplier Selection

A manufacturer has a given set of customer orders A manufacturer has a given set of customer orders to satisfyto satisfy

Each order has a required delivery date along with Each order has a required delivery date along with a penalty for missing that datea penalty for missing that date

The manufacturer’s capacity is finiteThe manufacturer’s capacity is finite Each order requires a number of components for Each order requires a number of components for

which suppliers have submitted bidswhich suppliers have submitted bids Supply bids include a price and delivery dateSupply bids include a price and delivery date


Supplier Bid Selection

Component 11

Order 1

Order 2

Component 12

Component 21

Component 22

Component 23

Supplier BidSupplier BidSupplier Bid





(Price, Delivery Date)

(Delivery Date, Late Penalty)


Trading Agent Competition

TAC Classic: Travel Agent ScenariosTAC Classic: Travel Agent Scenarios About 20 entries in the pastAbout 20 entries in the past

TAC’03: Supply Chain Trading CompetitionTAC’03: Supply Chain Trading Competition Agents compete for supplies and demandAgents compete for supplies and demand Fixed Assembly CapacityFixed Assembly Capacity RFQs from customers – delivery date and RFQs from customers – delivery date and

tardiness penaltytardiness penalty RFQs to suppliersRFQs to suppliers Interests on money borrowed from the bankInterests on money borrowed from the bank


Office hoursOffice hours

00:00 00:0000:00

Negotiationand planning

08:00 17:00 08:00 17:00

a day (24 h)

Production

Negotiationand planning

Production Production

Productionand delivery

schedule

Deliveryof PCs to

customers

RFQsto

suppliers

Responsesfrom

suppliers

RFQs andorders fromcustomers

Componentsfrom

suppliers

14 game seconds Zero game seconds

A TAC Day


Summary e-SCM is about more open and more dynamic business practices e-SCM is about more open and more dynamic business practices Mascot: Mascot:

Rapid evaluation of partner-dependent decisionsRapid evaluation of partner-dependent decisions Mixed initiative decision supportMixed initiative decision support Coordinated real-time Profitable-To-Promise functionalityCoordinated real-time Profitable-To-Promise functionality

Ongoing work: Ongoing work: Combine e-SCM and multi-attribute negotiation – together Combine e-SCM and multi-attribute negotiation – together

with the Univ. of Michiganwith the Univ. of Michigan Dynamic Supplier SelectionDynamic Supplier Selection Trading Agent CompetitionTrading Agent Competition


Q&A

Documents

Norman M. Sadeh e-Supply Chain Management Laboratory School of Computer Science