AI-assisted supply chain planning – Shell



Company Name / Department Shell
Contact Person Martijn Vermunt
 Location Rotterdam – Delftse Poort
Optional remote work Yes (on the agreement)
Travel expenses (own account or reimbursed by the company) Reimbursed
Housing arranged by company No
Housing expenses (how much per month, own account or subsidized by the company) Own account
Internship compensation  €550,- per month
Study program Operations Management and Logistics
ESCF community

Full member

Start date

February 2024


Company Description

We are a global group of energy and petrochemical companies with more than 80,000 employees in more than 70 countries. We use advanced technologies and take an innovative approach to help build a sustainable energy future.


Project Description

Project description:

The student will become part of the central Supply & Optimization team of Shell Chemicals in Europe.

This project forms a great opportunity for a student that wants to learn about supply chain planning and value chain optimization and how this drives value in Shell’s Chemicals business.

The supply chain includes processing raw materials (for example naphtha or bio naphtha) to produce base chemicals and further processing these chemicals in combinations of other products into derivative chemicals. Across each of these steps there are choice-points to either sell or continue to produce the derivative chemical. The goal of the value chain optimization at Shell Chemicals is to generate value (margin) from assets and selling the right products in our markets. This is driven by the monthly Supply and Operations Planning (S&OP) cycle which is led by the Optimization team and produces the plan for the upcoming three months. The Supply teams operationalize this monthly plan and (as part of the natural working team for the value chain) deliver the daily and weekly (optimization) decisions to deliver to our customers, handle disruptions and maximize value. Currently this is a process which is partly automated with quite a few manual steps.

Our vision is that we will move towards AI assisted (or even autonomous) planning in the future to support the many optimization decisions that this entails (and which are partly based on past scenarios and events, and the experience of the supply planners). AI would be a powerful instrument to help in this decision making and to safeguard the organizational experience in an environment where planners move more quickly to new roles. This project is to take the first step toward this ambitious goal.  The student will develop a data-driven planning tool that can use historical data/past scenarios to provide robust production plans and mitigations in supply scenarios to support the supply chain operations. This tool will enable a proof of concept (PoC) for AI assisted planning / decision making in supply chain operations.

Goals of the project:

Deliver a proof of concept (PoC) for AI assisted planning in supply chain operations. To achieve this the student will develop a data-driven planning tool which can (1) use historical data/past scenarios to provide robust production plans and mitigations in supply scenarios, and (2) can be incorporated in our ways of working.


  • Tested concept that deploys a data-driven approach to assist with decision making and can be used in Supply Planning
  • Suggestions on how to use such a concept into our existing planning tool

Essential student knowledge:

Supply Chain, Data Analytics, Optimization Models, Modelling.



More information:  


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