Using AI to support value stream mapping- Royal Haskoning DHV
Overview
| Company Name / Department |
Royal Haskoning DHV |
| Contact Person |
Jack Pool |
| Location | Hybrid – main office in Amersfoort, but we also have offices in Eindhoven, Rotterdam, Amsterdam. |
|
Optional remote work |
Yes, at least two days per week at the office. Preferably, three days per week. |
| Travel expenses (own account or reimbursed by the company) | Own account |
| Housing arranged by company | No |
| Housing expenses (how much per month, own account or subsidized by the company) | Not applicable |
| Internship compensation | € 550 per month |
| Study program | Operations Management & Logistics or Innovation Management |
| ESCF community |
Full member |
| Start date |
Default February ’25. Earlier or later start date can be discussed if preferred by student. |
|
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Company Description
Royal HaskoningDHV is an international engineering firm that is committed to enhancing society together. With over 140 years of engineering expertise and a focus on digital technologies, sutainable solutions and design knowledge, we are dedicated to creating a positive impact on the world through our work.
One of the markets we are active in is Industry and Buildings. Here, we actively contribute to reshaping the industry, ensuring it continues to bring health, prosperity, food and goods to society while using and re-using resources with minimal environmental impact. In addition, we develop flexible and sustainable buildings that can effectively meet present and future needs.
As part of RoyalHaskoning DHV, Districon provides specialized knowledge in the field of Supply Chain & Logistics. We believe that applying the right technology enables our customers to improve their supply chain processes and planning. With over 85 highly educated consultants and 5 offices across the globe we support customers in a variety of sectors.
One of the focus areas of Districon is warehouse design with a large mechanization factor. Through data, industry expertise and business understanding, create warehouse layout designs.
Project Description
Our customer is a global leading producer and distributor of beer (and others) in cans, kegs and bottles, both one way and returnables.
Sourcing of new glass, especially for returnable bottles, is expensive and puts pressure on yearly Capex investments.
Next to Capex, sourcing of new glass puts pressure on scope 3 emissions, while our customer pushes on improving circularity / re-use.
RHDHV supports the customer in many different countries globally by executing value stream assessments to identify root causes behind high circulation times, high market losses or high possession.
Circulation Time: time between shipping full bottle and receiving empty bottles
Market losses: difference between #bottles shipped and received back at brewery
Our challenge:
• We have diffferent data sources
• Avaliabality differs per country
• Quality of data is always a challenge
• All data sources tell a piece of the puzzle
• But data sources are not connected and hardly match
Our master thesis question: What AI techniques can support our Value Stream Mapping approach and what could they bring our customer?
We for instance think of proces mining as a method to generate:
• Data driven insights in bottle behavior in the market to increase grip
• A more holistic view on net zero: what is the impact of empty bottle management on scope 1, 2 and 3
Goal of the Project
Assessment and fact based value validation of AI techniques that can support our Value Stream Mapping approach
Deliverables
Situation assessment Report showing relevant AI techniques and their value for the customer Fact based use case for one or more countries
Essential student knowledge
Supply Chain understanding Data science techniques knowledge and experience
More information: escf@tue.nl
