Analyzing Supply Chain Performance under Different Collaborative Replenishment Strategies

AIT Masters Theses Competition

Wijitra NaowapadiwatIndustrial Systems Engineering

Asian Institute of Technology

May 18, 2009

Outline

Problem Statement

Collaborative Replenishment Operation Flow

Model Development

Results Analysis

Conclusion and Future Work

Problem Statement

• Fulfill the requirements between CPFR guideline and supply chain collaboration practice

• Study different collaborative replenishment strategies and address mechanism analysis

• Learn impacts of three strategies to the system performance

CPFR® Model (VICS Published 2004)

Collaborative Planning, Forecasting and Replenishment ( CPFR) is guideline that helps the collaborations between supply chain partners

Contribution of this thesis

Develops the sequential diagram which represents the operation flow of collaborative replenishment

Gives an analysis mechanism to approach different collaborative levels

Shows the impact of three strategies to the system performances and provides a better understanding of the supply chain collaboration

1. Develop Time Sequencing Diagram to address operation tasks >> HQ replenishment collaboration >> DC replenishment collaboration >> Store replenishment collaboration

2.Identify Analysis an Input and Expected Output data

3. Develop of the Simulation Model

4. Run the experiment on ARENA under the considered conditions

5.Analyze the impact of Supply chain performance under three Replenishment collaboration strategies on ANOVA

6.Conclusions and Recommendations for future study

Methodology

Simulation ModelProcess flowSequential diagram

Sequential diagrams for collaborative replenishment

HQ_CR DC_CR Store_CR

Three levels of replenishment collaboration between seller and buyer are demonstrated on main collaborativetasks including:Sale forecasting, order forecast, and order generation.

Supply Chain Performances

Customer Service Back Order and Fill rate Shortage Rate

Total Supply Chain Cost Inventory Cost + Transportation Cost

Carrying Shortage

Experiment Design

Experiment 1. The impact of supply chain performances under different CR

Experiment 2. The impact of supply chain performances under economic transportation consideration

Independent Variables Supply Capacity ( Cap) Lead time (LT) Demand Variation ( DV)

Parameters and Variables design

Independent factor Level

1 2 3

CR HQ DC St

CAP μ* bμ* aμ*

DV 0 2 4

LT 1 days 1 week 4 weeks

Note * : a>b>1 and μ is averaging of Customer demand

General Parameters and Basic assumptions Number of product and supplier (single product item, 1 supplier) Number of retailer store ( 1 retailer,2 DCs, 4 stores) Sale Forecast method (Exponential Moving Average, α= 0.2 ) Inventory Policy ( Periodic review weekly, Up-to-level) Simulation run length ( 2800 days, 400 wk 30 replications)

Supply Network

Lead time vs. Impact of supply chain performances under three CR Strategies

Demand Variation vs. Impact of supply chain performances under three CR Strategies

Supply Capacity vs. Impact of Supply chain performances under three CR Strategies

Summary

Level of valued information sharing during order replenishment shows significant impact for supply chain performance

Over all Store CR shows lower total supply chain cost and higher order fulfill rate from simulation results

When limited supply capacity and short lead time, the practitioner may better investment for DC_ CR

Demand uncertainty is high , Store CR is a better choice Regional DC is needed for a cluster Store replenishment

when economic of transportation influences

Future Work

Complexity with replenishment collaboration such as multiple manufacturers collaboration for multiple items

Collaborative Forecasting in supply chain network IT in Order collaborative replenishment

Q&A THANK YOU