About the thesis
Are you a master’s student within engineering, finance or law looking for an innovative company to collaborate with on your master’s thesis during the spring semester of 2025? Look no further.
ASSA ABLOY is the global leader in access solutions and provides the latest technologies to give access to physical and virtual spaces for millions of people every day. Joining ASSA ABLOY means being part of a fast-moving and highly innovative company with diverse opportunities in more than 70 countries worldwide.
What can you expect as a master’s thesis intern at ASSA ABLOY? Cutting edge technology, a steep learning curve, dedicated supervisors from within the enterprise, a group of fellow master's thesis students to share the experience with – and much more.
We have an exciting range of subjects. Please remember to indicate in your application if you're interested in other subjects as well, and mark them in your order of preference. Please also let us know your thoughts on how you would approach the subject.
While we aim to support all proposed thesis subjects, we may need to change or cancel a project due to unexpected circumstances.
Master thesis nr 1. Predictive Maintenance Model for Battery Replacement in Locks
Lifetime prediction model for predictive maintenance of battery replacements and elaborate a little bit on its potential for locks.
Service and maintenance of locks and doors are crucial for ensuring product reliability and availability. Unexpected faults or failures can lead to significant costs or even catastrophic outcomes. Various maintenance strategies exist, including reactive maintenance (replacing components after failure), preventative maintenance (replacing components at regular intervals before failure), and predictive maintenance, which optimizes by predicting and replacing components just before failure using advanced prediction methods and AI-driven optimization.
This project aims to explore predictive maintenance strategies, identifying the necessary technologies, tools, and methods to achieve optimal maintenance efficiency. A key aspect of predictive maintenance is accurately forecasting the remaining lifespan of components. In particular, this work will focus on investigating a battery lifetime prediction model for electronic locks or sensors, contributing to more effective and timely maintenance practices.
Investigate the current maintenance strategies employed by ASSA ABLOY for their products.
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Develop a deep understanding of the toolchain necessary to simulate different maintenance strategies and evaluate profit potential using AI-driven maintenance solutions. Identify the required inputs, processes, and review cutting-edge academic research to uncover the latest tools and methodologies. Address key challenges and highlight critical areas of expertise essential for successful execution.
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Explore a battery lifetime prediction model, considering various battery types (Alkaline, Primary Lithium, and rechargeable) alongside battery monitoring functions and other relevant data from locks or sensors.
We look forward to receiving your application with your resumé and university grades and hearing your ideas on how you would approach this subject
We are the ASSA ABLOY Group
Our people have made us the global leader in access solutions. In return, we open doors for them wherever they go. With nearly 61,000 colleagues in more than 70 different countries, we help billions of people experience a more open world. Our innovations make all sorts of spaces – physical and virtual – safer, more secure, and easier to access.
As an employer, we value results – not titles, or backgrounds. We empower our people to build their career around their aspirations and our ambitions – supporting them with regular feedback, training, and development opportunities. Our colleagues think broadly about where they can make the most impact, and we encourage them to grow their role locally, regionally, or even internationally.
As we welcome new people on board, it’s important to us to have diverse, inclusive teams, and we value different perspectives and experiences.
