Next steps in (liquid) Chemicals Value chain optimization  – Shell

 Overview

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

The student will become part of the central business optimisation team of Shell Chemicals in Europe.

This project forms a great opportunity for a student that wants to learn about real time value chain optimisation and how this drives the business.

The goal of the value chain optimisation at Shell Chemicals is to generate value (margin) from assets and selling the right products in our markets.

The supply chain includes processing raw materials (Naphtha) to produce intermediate products, further processing the products in combinations of other products to get secondary products, and even further processing the secondary products to get other products. In all steps it can be decided to sell the intermediate product to the market or to process further into different (secondary) products. Depending on production capabilities and market demand & prices these optimisation decisions are made with the objective to achieve the highest margin overall in operating the supply chain.

Currently, deterministic Linear Programming tools are used to find the optimal solution: The highest total margin of operating the value chain.

There are multiple uncertainties that can influence the actual margin delivered. Examples of the types of uncertainties are: Feedstock availability & prices, energy costs, product demand & prices and production asset performance (reliability).

These uncertainties are currently not modelled, and the aim of the project is to incorporate the uncertainties in the decision making to further increase the business value (margin) of running the value chain.

Goals of the Project

This project aims to determine how to incorporate all the uncertainties in the supply chain into the optimisation to get:

• Multiple optimisation outcomes on how to optimally run the value chain
• Associated value and risks to the multiple optimisation outcomes

The above output should allow incorporating uncertainties effectively into the decision making process.

Deliverables

• Tested concept that provides outcomes (scenarios) that can be used for decision making taking uncertainties into account.

Suggestions how to incorporate such a concept into our existing optimisation models 

Essential Student Knowledge

Supply Chain, Optimisation models (e.g. Linear programming), programming, modelling.

More information: escf@tue.nl