Industrial PhD student Adam develops AI for SCA

Industrial PhD student Adam develops AI for SCA

Fri 29 Jan 16:25

Meet Adam Lundström, new industrial PhD-student at SCA. He will develop machine learning to predict maintenance in the industry.

Adam Lundström, industridoktorand SCA företagsforskarskolan Smart industry sweden

Tell me a little about your background?

I’m originally from Skellefteå but moved to Sundsvall five years ago to study and decided to stay after I graduated last year. I have a master’s degree in industrial engineering and management at Mid Sweden University and a master’s degree in computer and system sciences at Stockholm University. During my education I have worked at an IT company as a developer for data storage solutions and taken part in an internship at Sundsvall’s municipal were I programmed voice and visual solutions as support tools for people with autism spectrum disorder or intellectual disabilities.

Why did you choose to apply for the position as an industrial PhD-student at SCA?

I’ve always enjoyed to examine things that interest me at depth which is why I strongly considered postgraduate studies after I graduated. However, I’ve been somewhat afraid of drifting too far from the problems that exist within the industry today. Therefore, the possibility to become an industrial PhD-student at SCA has really been the perfect option for me as it allows me to both examine and find solutions to existing problems.

What is it that you are going to investigate as a PhD-student?

My research area is going to be predictive maintenance with a highlighted focus on machine learning. The overall goal of predictive maintenance is to perform maintenance based on the actual conditions of the different items in the factory were one of the key benefits is the possibility to reduce the unplanned downtime. In light of this, I aim to define central aspects that are important to consider when implementing a data driven predictive maintenance system but also to develop state of the art machine learning models that are capable of supporting maintenance decisions from real time data.

You started in this autumn. What have you done so far and what is your experience?

So far I have conducted a literature review on the topic but also examined some of the cases available at SCA. I have already come to realize the potential for machine learning solutions but also that, in contrast to available data sets online, several cases lack classified data which is going to be an interesting challenges to overcome.

Anything else you like to add?

I feel privileged to be able to spend the following five years in a position where I have the opportunity to provide scientific knowledge and solutions to a field which has a growing importance in the changes following industry 4.0.

Contact

Adam Lundström

Doktorand|Doctoral Student