Logistics for Projects and Pull Production

09/09/2004


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Summary

Logistics for Projects and Pull Production

Plan

Pulling Logistics?

I. General concepts

Four definitions for project management

Definition for production

The four kind of resources

The three kind of stock

Definition for pull production

Four definitions for Logistics

The five kind of flux

Flux logistics chain

II. Definition & Comparison

Two definitions for quality

Plan

PDCA

Goals of logistics

Market constraints

What companies have to do?

Situation

Improve logistics chain performances

How measure logistics performances ?

Indicator categories

How measure global performance ?

How measure global performance ?

Control & reduce delays

Stock optimisation

Stock indicators

Stocks

Traditional production

Push production organization

Pull production organization

Push & Pull production

Concepts used by pull model

Differences Pull/Push models for firms

Differences Pull/Push models for firms

Differences Pull/Push models for firms

Pull vs. Push

Production/Quantity and repetitiveness

Production/Quantity and repetitiveness

Client Relationship

Production by stock

Production by command

Kind of production (1/2)

Kind of production (2/2)

Production/variety & volume

III. Traditional methodologies

Plan

Plan

Logistics

What is operational research?

Steps of a RO project

Introduction to Linear programming

Logistics

Terminology

Canonical form of a linear program

Standard form of a linear program

From canonic form to standard form

Transformation rules (1)

Transformation rules (2)

Example : Resource allocation problems

What has to produce the company in order to maximize its weekly sales turnover?

Resource allocation problem: model

Geometric interpretation

Basic solutions

Example

LP basic solution

Decision Variables

Decision Process

Solution Acceptance

Logistics

Logistics

Swivelling matrices

Tables

Table Use 1/2

Table Use 2/2

Example

Basic solution

Basic Solution Values

Swivellings in a table

Geometric interpretation swivelling

Logistics

How to maximise Z thanks to swivelling

Tables

Hypotheses

Simplex primal algorithm

Simplex primal algorithm

Problem of the shortest way

Modeling

Modeling (2)

Example

Critical path algorithm

Algorithm of the critical path

Example

Terminology

Example Critical Works

Logistics

Planning of production

Planning of production

Objective of planning

Information types

Information (1)

Information (2)

Planning tools

Estimated planning

Temporality of the decisions

Temporality of the decisions

Planning tools

Scheduling

Scheduling

PERT : Example

PERT : Example (2)

PERT : Example (3)

PERT : Example (4)

PERT : Example (5)

Scheduling

Stock management

Stock evolution in time

Annual level of restocking is :

Variation of the storage cost according to Q

Variation of the storage cost according to Q (2)

Variation of the storage cost according to Q (3)

Calculation of a safety stock

Logistics

Stakes of quality management

Quality management

Quality management

Various methods to improve quality

Quality Steps

Approach continuous improvement (1)

Approach continuous improvement (2)

The total management of quality

IV. Evolution & Innovation

Plan

Logistics

History

History

History

History

Introduction

Introduction

Stakes of SCM

Production in SCM

Production in SCM

Production on demand

Production on demand

Logistics

Enabling technologies

Enabling technologies

Enabling technologies

Enabling technologies

Enabling technologies

Enabling technologies

Enabling technologies

Enabling technologies

Enabling technologies

Enabling technologies

Enabling technologies

Logistics

Enabling technologies

Enabling technologies

Enabling technologies

Enabling technologies

Enabling technologies

SCEM

Enabling technologies

Enabling technologies

Enabling technologies

Enabling technologies

Enabling technologies

Enabling technologies

Enabling technologies

Enabling technologies

Enabling technologies

Enabling technologies

V. Innovative Techniques

Plan

Logistics

PROSIM - Plan

PROSIM - Application Description (1/4)

PROSIM - Application Description (2/4)

PROSIM - Application Description (3/4)

PROSIM - Application Description (4/4)

PROSIM - Problem Definitions (1/2)

PROSIM - Problem Definitions (2/2)

PROSIM - Quantitative Input Data (1/2)

PROSIM - Quantitative Input Data (2/2)

PROSIM - Technique Used (1/9)

PROSIM - Technique Used (2/9)

PROSIM - Technique Used (3/9)

PROSIM - Technique Used (4/9)

PROSIM - Technique Used (5/9)

PROSIM - Technique Used (6/9)

PROSIM - Technique Used (7/9)

PROSIM - Technique Used (8/9)

PROSIM - Technique Used (9/9)

PROSIM - Quantitative Result Obtained (1/11)

PROSIM - Quantitative Result Obtained (2/11)

PROSIM - Quantitative Result Obtained (3/11)

PROSIM - Quantitative Result Obtained (4/11)

PROSIM - Quantitative Result Obtained (5/11)

PROSIM - Quantitative Result Obtained (6/11)

PROSIM - Quantitative Result Obtained (7/11)

PROSIM - Lesson Learned (1/2)

PROSIM - Lesson Learned (2/2)

Logistics

LASS - Plan

LASS - Application Description (1/3)

LASS - Application Description (2/3)

LASS - Application Description (3/3)

LASS - Problem Definitions (1/2)

LASS - Problem Definitions (2/2)

LASS - Quantitative Input Data (1/2)

LASS - Quantitative Input Data (2/2)

LASS - Technique Used (1/5)

LASS - Technique Used (2/5)

LASS - Technique Used (3/5)

LASS - Technique Used (4/5)

LASS - Technique Used (5/5)

LASS - Quantitative Result Obtained (1/2)

LASS - Quantitative Result Obtained (2/2)

LASS - Lesson Learned

Logistics

PUMA / COUGAR - Plan

PUMA - Application Description (1/5)

PUMA - Application Description (2/5)

PUMA - Application Description (3/5)

PUMA - Application Description (4/5)

PUMA - Application Description (5/5)

PUMA Problem Definition (1/3)

PUMA Problem Definition (2/3)

PUMA Problem Definition (3/3)

PUMA Quantitative Input Data (1/6)

PUMA Quantitative Input Data (2/6)

PUMA Quantitative Input Data (3/6)

PUMA Quantitative Input Data (4/6)

PUMA Quantitative Input Data (4/6)

PUMA Quantitative Input Data (5/6)

PUMA Quantitative Input Data (6/6)

PUMA Technique Used (1/3)

PUMA Technique Used (2/3)

PUMA Technique Used (3/3)

COUGAR Evolution/Adaptation of PUMA System (1/5)

COUGAR Evolution/Adaptation of PUMA System (2/5)

COUGAR Evolution/Adaptation of PUMA System (3/5)

COUGAR Evolution/Adaptation of PUMA System (4/5)

COUGAR Evolution/Adaptation of PUMA System (5/5)

PUMA / COUGAR - Lesson Learned (1/2)

PUMA / COUGAR - Lesson Learned (2/2)

VI. Industrial cases study

Plan

Logistics

Schuman - Customer Overview

Schuman - Highlights

Schuman The challenge

Schuman The solution

Bibliography

Bibliography

Bibliography

Bibliography

Bibliography

Bibliography

Bibliography

Aknoledgements

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