Preventing Slow Moving Inventory – A Predictive Modelling Approach – Dow
Overview
Company Name / Department | Dow Inc. |
Contact Person |
Aram de Ruiter |
Location | Terneuzen |
Study programme(s) | Operations Management |
Community | ESCF |
Start Date | February 2023 |
Housing arranged by company | Yes |
Compensation |
450 EUR per month |
Company Description
www.dow.com; Our company | Dow Corporate
Dow Inc.’s ambition is to become the most innovative, customer-centric, inclusive and sustainable materials science company. Our goal is to deliver value growth and best-in-class performance. The Company’s portfolio comprised of six global business units, organized into three operating segments: Performance Materials & Coatings, Industrial Intermediates & Infrastructure and Packaging & Specialty Plastics. Its products serve different applications, including coatings, home and personal care, durable goods, adhesives and sealants, and food and specialty packaging.
Project Description
Making the right product at the right time in the right place is the aim, however a significant part of our produced materials end up in Slow Moving Inventory (SMI), meaning they are not consumed for 270/360+ days.
This project would look based on (Historic) Batch Number data, what can be learned from the data that we have on the batches of products that end up in SMI. Especially using what variables looked like at the time of manufacturing, to develop predictive models and allow for:
- Corrective actions at an earlier moment
- Identify variables that can be used to create measurements that confirm the right product was made at the right time in the right place
Goals of the Project
- Find predictable variables for fast/slow moving product batches (directly after being made)
- Compare results of different predictive models (incl. Machine Learning)
Deliverables
- Predictive Model for batches becoming Slow Moving Inventory
- Model comparison analysis
- Thesis report including advice to Dow on how to use the model to make statements on the quality of scheduling
Essential Student Knowledge
- Supply Chain Management
- Coding Skills (Python, R, MATLAB, etc.)
- Data analysis
Unique Opportunity
Dow is offering you a great inclusive international learning environment where you will be collaborating with a team of Dow experts in Supply Chain and Procurement. You will have the opportunity to work with external logistics partners and participating in sustainability conferences and meetings.
More information: escf@tue.nl
