intelligent e supply chain decision support pdf

University of Minnesota – Digital Technology CenterDecember 2002 Intelligent e-Supply Chain Decision Support Norman M.. Sadeh e-Supply Chain Management Laboratory School of Computer Sci

University of Minnesota – Digital Technology Center

December 2002

Intelligent e-Supply Chain Decision

Support

Norman M Sadeh

e-Supply Chain Management Laboratory

School of Computer Science Carnegie Mellon University

Outline

Supply Chain Management

distribution activities

distribution centers …to retailers and consumers

 Trillions of dollars annually

 Good practices directly impact the competitiveness of companies

 Timely and cost-effective delivery of products to

customers

 Extends to product design and configuration

Why is SCM Difficult?

quantities and due dates, contractual arrangements, transportation constraints, etc

Historical Perspective

Purchasing Production Sales Distribution

Materials Management

Manufacturing Management Distribution CustomersSuppliers

Buyers/

Sellers

Inventory Control

e-Commerce e-Markets/Exchanges e-Supply Chains

Beyond the Early eMarket Hype

Some Open Research Issues

 Multi-attribute negotiation

multiple tiers

 Creating the right incentives for information sharing

MASCOT:

Collaborative Decision Support

 Decisions are evaluated in collaboration with potential business partners

 Supply chains can be dynamically set up in response to changing market requirements

 Emphasis on Mixed Initiative Decision

Support

 Don’t try to automate everything!

MASCOT Supply Chain Agent

Bidding & Order Mgmt.

Planning & Scheduling

Procurement

Business Entity

Enterprise Level Mascot Agent

Tier 1 Suppliers

eMarket

eMarket

eMarket

Site Level Mascot Agent

Site Level Mascot Agent

Prospective Customer

Request for Quote

eMarket

MASCOT: Overall Objectives

decisions :

 Bids & Requests for Quotes

workflow management

A Customizable Agent Wrapper

eMarket Portal

Potential Business Partner

Potential Customer

Bidding/Order Mgmt KS BOM/Flow Config KS Demand Explosion KS

Communication KS Knowledge Sources Contexts

External Systems

Outgoing messages

Incoming Events

Scheduling/CTP KS RFQ/Procurement KS

Current working context

Main Architectural Features

suppliers) and different solutions

Unresolved Issues

of supplies, missed prior delivery commitment

management

Three Levels of Problem Solving

 Knowledge Source Activations

 e.g Demand Explosion (RFQ1)

Mixed Initiative Workflow

U/C:

Select Unresolved Issue to Resolve

U/C:

Select Resolution Method

KS:

Execute Resolution Method

Controller:

Activate Resolution Method

Unresolved Issue

Selected Unresolved Issue

Selected Resolution Method

Activated Agenda Item

machine shop and a tool shop at Raytheon

coordination policies and different order promising policies

Dynamic Supply Chain

Supply chain entity

The Coordination Challenge

promise dates

the benefits of finite scheduling, while offsetting the brittleness of its solutions ?

 Costs & Priorities: order priorities, late delivery penalties, inventory costs, etc

-RTP: Further Refinements

 Profitable-To-Promise

 Selective RTP Validation

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

commitments

gets bumped

Empirical Study:

Multiple RFQ Processing Policies

Empirical Study: Assumptions

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

 Stochastic order arrival

 Finite capacity schedules regenerated daily

 JIT objective: minimize sum of tardiness & inventory costs

 Execution priority in accordance with the latest released schedule

Evaluation Criteria

 Average utilization of the most utilized resource

 Average due-date adjustment (as part of bid negotiation)

 Profit (sales revenue minus costs)

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

 Total tardiness costs

Basic Supply Chain Configuration

Tier3 Tier2 Tier1

Benefits of Dynamic Finite

1000000 2000000 3000000 4000000

Dynamic Supplier Selection

to satisfy

a penalty for missing that date

which suppliers have submitted bids

Supplier Bid Selection

(Price, Delivery Date)

(Delivery Date, Late Penalty)

Trading Agent Competition

tardiness penalty

Office hours Office hours

00:00

Negotiation and planning

a day (24 h)

Production

Negotiation and planning

Production and delivery schedule

Delivery

of PCs to customers

RFQs to suppliers

Responses from suppliers

business practices

functionality

together with the Univ of Michigan

Q&A