Assignment type: Graduation/Internship
Start date: February 2025
Assignment Duration: 6 to 9 months
Location: Veghel
Educational Level: Master
Desired Study: Data Science or related studies
Language: Dutch / English
Assignment
Can raw data be converted into valuable insights about the asset health, to drive and optimize maintenance? Vanderlande systems produce a lot of data, which can be a goldmine for data scientists to transform into insights. The focus of this internship is loopsorters, complex logistic sorting machines with many sub-components that need to work together seamlessly. Loopsorters generate a significant amount of log data and there is a vast amount of untapped data that can provide a broader perspective on asset health.
The goal of this assignment is to identify what value the logfiles offer in terms of finding potential issues, interact with SMEs to understand their meaning and potential, create and fine-tune appropriate ML models, validate the outcomes with SMEs and possibly end-users, and deliver the developed solution to the Predictive Maintenance team to productize and integrate it as part of the existing product.
Department
The intern will work in the Digital Service Platform department, responsible for driving Vanderlande digital transformation through the creation of Digital Services. He or she will be working in the Predictive Maintenance team, a multidisciplinary, multicultural and distributed team focused on converting data into insights to drive and optimize Maintenance. The team has data science, data engineer, software development and frontend development capabilities.
The student will have ample support and access to the existing knowledge within the team. If the internship is successful, their work will be used by the team to improve and enlarge the existing product.
Your responsibilities
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The student will be trained on the loopsorter functioning, and will be provided a few data sets to choose from. The student is expected to:
- Interact with SMEs to fine-tune their loopsorter understanding and define potential of the chosen data set(s)
- Develop a model that based on the acquired data can provide insights on the loopsorter health
- Validate the model outcome (and possibly improve the model) with SMEs and end-users
- A successful internship will deliver a model that can be productized and integrated with the existing Predictive Maintenance solution
Your profile
- Data science and ML knowledge
- Python knowledge
- (Preferred) Familiarity with Azure and Databricks
- Mandatory enrolment in a Dutch Education System and resident of The Netherlands*
Contact
Do you recognize yourself in this challenging profile? And are you looking for an internship/graduation assignment in our organization?
Please fill out the application form and upload your resume and cover letter. For more information, contact us by e-mail: internship@vanderlande.com