Integrated Supply Chain Event Management Data Mining – Dow Chemicals

 

 Overview

Company Name / Department Dow Chemicals
Contact Person Zarinka Berkouwer
 Location Terneuzen
Optional remote work Yes, to be discussed
Travel expenses (own account or reimbursed by the company) Reimbursed by the company
Housing arranged by company No
Housing expenses (how much per month, own account or subsidized by the company) NA
Internship compensation  +/- 500 euro per month
Study program OML / Information Systems
ESCF community

Full member

Start date

September, 2023

 

Company Description

Multinational chemical company with focus on safety and sustainability, offering great career opportunities in a global and international environment.

 

Project Description

Project description:

Dow’s Integrated Supply Chain is a customer-driven network of services and capabilities that together ensure the highest level of performance from demand planning all the way through to order fulfillment. ISC operates across the end-to-end value chain to deliver a world-class customer experience. The ISC team is made of more than 4,600 professionals across different locations, and it provides transport management services to 45,000 customer locations in 170 countries, and it drives demand and supply planning for the company. Additionally, the ISC team is responsible to create, manage and execute Order to Cash (OTC) work processes to handle orders, ship and deliver products and receive payments.

Supply Chain Event Management (SCEM) is a globally standardized six-step work process that provides leadership and stakeholders with visibility of external events that are or could potentially disrupt the Supply Chain and threaten the ability to service internal or external customers. SCEM drives actions being taken to mitigate risk and assesses customer impact (actual or potential).

Within Supply Chain Even Management we have identified an improvement opportunity related to our global data mining process within ISC Event Management to be able to find and examen patterns and other relationships within large data sets to discover critical insights (problem) and with that to maximize the value of our enterprise data (value)

Goals of the project:

This project has two goals:

  1. Create a structured database from past event data (more than 10 years data) and use modelling and predictive analytics to detect trends and anticipate risks.
  2. Create a new SCEM submission form to collect data for future events in a structured way.

If you are interested to support Dow in finding new ways to tackle Digital Science challenges in our Integrated Supply Chain, join our team in Terneuzen!

    Deliverables:

    Create a structured database from past event data (more than 10 years data) and use modelling and predictive analytics to detect trends and anticipate risks Create a new SCEM submission form to collect data for future events in a structured way.

    Essential student knowledge:

    • Study related to Data Science / Computer Science
    • Good overall command of English
    • Preferably experience with data mining and modelling

     

     

     

    More information: escf@tue.nl  

     

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