Quantitative Supply Chain - DSM

Quantitative Supply Chain Optimization Dorus van der Linden - Competence Manager Process Modeling DSM Advanced Chemical Engineering Solutions (DSM ACES)

DSM Mission

• Our purpose is to create brighter lives for people today and generations to come • We connect our unique competences in Life Sciences and Materials Sciences to create solutions that nourish, protect and improve performance

Slide 1

1

DSM Modeling Competence (Simulation & Optimization) Creating value with integrated advice & knowledge based on quantified analysis, using mathematical process descriptions. Production Process Modeling Process Design Quantification

Batch Schedule & Recipe Modeling

Model Supported Operations

Supply Chain Modeling Advanced Forecast & Market Predictions

Production & Inventory Optimization

Network & Inventory Optimization

Slide 2

DSM Building on History Bioterials / Biologics Life Science Products Performance Materials Petrochemicals Fertilizers Coal 1902

1930

1950

1970

1990

2000

2010

Slide 3

2

Constant Change DSM Setup and Surroundings

Development of profit / EBITDA (€ m)*

Normalized public reported price of 161 products in the DSM value chain

* 2013 EBITDA from continuing activities only Slide 4

Supply Chain Management - Great Impact on Businesses Supply Chain Management has large effect on business results Purchasing and supply management

Manufacturing and operations strategies

Demand planning & sales forecasting

Supply chain logistics

Slide 5

3

Supply Chain Management - Great Impact on Businesses Supply Chain Management is optimization Meet required service level

Minimize supply chain costs

Maximize capacity

Minimize inventory

Minimize logistics cost

Slide 6

Supply Chain Management - Competing Objectives

Meet required service level

Minimize supply chain costs Maximize capacity

Minimize logistics cost

Minimize inventory

Slide 7

4

Difficulty in Balancing Supply Chain

Slide 8

Re-Design Efficient, Flexible & Responsive Supply Chains Existing methods DSM • Stochastic demand • Single echelon • Steady state • Low level of information availability Not applicable to DSM’s market situation DSM Modeling approach • Discrete event simulation based on demand data • Multi echelon approach • Automated scenario analysis • Making use of available data

Slide 9

5

Supply Chain Optimization Toolset • Discrete event simulation based on demand data • Multi echelon systems approach


Network Optimization

• Automated scenario analysis Advanced Forecast & Market Predictions

• Big Data Monte Carlo & Sensitivity

Optimizer

Slide 10

Supply Chain Optimization Toolset Monte Carlo & Sensitivity

Optimizer


Network Optimization

Advanced Forecast & Market Predictions

Slide 11

6

Forecast & Market Prediction Correlations and Early Warning System (1-3 month) Inventory and Demand Modeling (6-18 month)

Time shifted cross-correlations Database solutions for Big Data Market Capacity Modeling (1-8 years)

Upstream demand propagation Systems approach

Monte Carlo Simulation Business Intelligence

Slide 12

Production & Inventory Optimization Challenge

Approach

Multi product Multi echelon Multi line With competition for resources

Discrete event simulation (DES) Balancing KPI’s and $/€ optimization Scale able Discrete Event Model Automated scenario analysis

Setup

Sales Orders

Forecast Slide 13

7

Conclusions – Method successful in DSM supply chain challenges Discrete Event Modeling advantages of scalable models • Flexible (different supply chains) • Scalable (via data, number of products and orders) • Fast & lower cost

Strong Business results • 10-20% increase in perfect order rating • 10-20% reduction in supply chain costs • 20-50% reduction of inventory • More efficient, flexible & responsive supply chains

Further improvement and development needed • Incorporate responsive dynamic market behavior • Expand to more complex network setups Slide 14

Acknowledgements • • • •

Gerben Bas - ISPT & Delft University of Technology Telli van der lei - DSM Ruud Barendse - DSM Willem Godlieb – DSM

8

Integral supply chain simulation tool enables management to make strategic choices based on quantified scenarios and optimization\

[email protected]

9