Master Thesis: Optimising rig test planning using data and experimental design

Master Thesis: Optimising rig test planning using data and experimental design

Transport is at the core of modern society. Imagine using your expertise to shape sustainable transport and infrastructure solutions for the future. If you seek to make a difference on a global scale, working with next-gen technologies and the sharpest collaborative teams, then we could be a perfect match.

Thesis Background

Volvo Penta has a vested interest in utilizing and understanding vast amounts of data as well as in ensuring product quality to reinforce the trust of its customers.

To that end, extensive test in local rigs and field applications is conducted to ensure performance and compliance with legislation, generating huge amounts of data. The test facility management team conducting these tests and evaluates them with support from us at Volvo Penta Data Science & Engineering (VPDS&E) to include new technologies and improve efficiency working with the data.

During this endeavour, a lot of costly and complex tests are conducted and analysed, generating a lot of data of which a lot can be assumed to be superfluous or redundant.

We at VPDS&E together with Test Facility Development are now looking to utilize all the data and knowledge to reduce the number of tests needed to fulfil requirements and speed up the testing processes through exploitation of the existing data and appropriate statistics techniques.

What you will do?

Our purpose with this thesis is to gather the testing processes, definitions and available data to analyse and optimize the testing process and remove unnecessary tests. We see possibilities to detect redundant tests automatically and cover all requirements through the smart combination of test aspects utilising intelligent experiment design and data analysis.

This thesis will focus on identifying superfluous tests, combining existing tests and developing the analysis to ensure all requirements are met with as few physical tests as possible.

Which tests can be combined to test different variable settings?

How can we analyse them to still get the necessary testing outcomes?

Which clutter can be removed through the efficient use of the existing data?

From Volvo Penta’s perspective, this research represents a significant opportunity to enhance our testing processes and reduce both time to market and environmental impact while ensuring reliable quality and compliance.

What We Use: Tools and Technologies in Our Daily Operations

In our daily operations, we rely on a diverse set of tools and technologies to manage and process data effectively. Python is central to our scripting and automation tasks. While we are working on migrating data into Azure databricks, some data is only available in on prem storage.

Who will you work with?

This thesis is a collaboration between the Data Science & Engineering and Test Facility Development teams and thus there will be a mentor from each team to ensure that you understand both the domain and test processes correctly and you get the necessary support with data and analytics questions.

Qualifications for this role

We are looking for 2 master students in any of the following fields or related disciplines:

• Artificial Intelligence
• Computer Science
• Data Science
• Machine Learning
• Physics
• Knowledge of statistics and big data analysis
• Some programming proficiency

Ready for the next move?

Are you excited to bring your skills and disruptive ideas to the table? We can’t wait to hear from you. Apply today!

The last application date is the 30th of October

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