Assignment type: graduation
Start date: ASAP
Assignment duration: 6 months
Educational level: WO
Desired study: Data science
Language: Dutch and/or English
Modern Baggage Handling systems transport bags partly in so-called tubs – medium-sized open containers that can take in one bag and that are transported via conveyor belts. However, bags are not placed in tubs throughout the entire system: there are various points where a bag has to be placed into an empty tub or taken out of a tub. The empty tubs are moved forward to a location where they are needed next. Efficient system performance requires that empty tubs are managed correctly: whenever a bag needs to be placed into a tub an empty tub has to be available at the location where the bag needs it. If the tub is not available, the bag has to wait until the tub arrives. A system-wide control software predicts where tubs are needed next and dynamically routes empty tubs to the next location where they are needed.
The objective of this project is to provide insights into how the tub management and routing can be improved to reduce waiting time of bags for empty tubs, and to reduce the number of unnecessary tub movement in the system. Data about baggage movement and tub movement is available in standardized data format. The goal is to develop a technique to:
– Integrate both datasets to understand and reason about baggage movement and tub movement in an integrated way through the use of graph-based data models and graph databases.
– To develop a technique to visualize tub and bag movement and to visualize and automatically detect possible problems in tub management.
The expected outcome of this project is a pipeline for integrating, processing, and visualizing the baggage and tub movement data, and to evaluate the visualization in its feasibility to identify problems in tub management.
Life-cycle Services accounts more than 20% of the total sales at Vanderlande and is growing steadily. The department of Digital, IT and Product Management which is a part of the Global Services organization manages the life cycle of our products and the customer’s installed base. In this process we heavily rely on data. Therefore there is a dedicated Data Service Development & Data Science team within the department that is responsible for the further digitalization of Life-cycle Services.
You will be part of the Data Service Development & Data Science team within Global Services. The team is working on fundamental descriptive and diagnostic solutions and challenging use cases such as models that predict operational behaviour of the logistics systems or failure of physical system components. You will be part of this growing, autonomous team of data scientists, data engineers and data architects that is driving the digitalization of Vanderlande life-cycle services. In our team experiments and entrepreneurial spirit are highly valued.
Tasks / responsibilities
• Analyze the movement of tubs in the material handling system
• Relate the availability of tubs and requirements for a bag at different locations
• Develop techniques that can visualize these relations and suggest improvements
• Build a dashboard to report the analyze and report findings
• Pro-active and independent.
• Affinity with data and able to introduce new approaches / new data sources.
• Experience with process mining techniques.
• Experience in visualizing results from data science techniques.
Do you recognize yourself in this challenging profile? And are you looking for an internship/graduation assignment in an organization that has been elected as “Best Employer” for years in a row? Please fill out the application form and upload your resume and cover letter. For more information, contact us by e-mail: firstname.lastname@example.org or Jasper Pijnenburg (Campus Recruiter) by phone: +31 413 49 44 08.