PhD Defence

On the 10th of June I successfully defended my PhD thesis "Short-term Underground Mine Scheduling: An Industrial Application of Constraint Programming". The faculty opponent was Docent Mats Carlsson (RISE) and the decision committee consisted of Lecturer Micah Nehring from University of Queensland, Docent Elina Rönnberg from Linköping University, and Professor Zdeněk Hanzálek from Czech Technical … Continue reading PhD Defence


If you are attending the IEEE International Conference on Emerging Technologies and Factory Automation (ETFA20) either online or on-site, and have an interest in automatic scheduling, then consider listening to a narrated presentation of my most recent work (teaser in video). We present a scheduling approach particularly suitable for industries where activities do not only … Continue reading ETFA2020

Scheduling using discrete-event simulation

Last couple of years, we have during several R&D projects (e.g. the SIMS project) integrated the SimMine discrete-event mine simulator with our production scheduling system. It has been extended beyond a long-term mine simulator by including more logic related to detailed simulation of mining activities. By integrating with our scheduling system, the production in this … Continue reading Scheduling using discrete-event simulation

New poster from WASP Winter Conference

WASP is funding a lot of interesting development within autonomous systems and artificial intelligence. I recently had a poster presentation at the annual internal WASP conference, presenting research on automatic mine scheduling using Constraint Programming and Large Neighborhood Search. The poster can be accessed here: link.

Mine scheduling: an important piece in the pursuit of autonomous mining

A high level of automation is necessary for mines as they go deeper. We have developed a method for automatic mine scheduling1 that contributes towards the vision of a fully automated mine operation. In an autonomous mine, machines are used more efficiently and workers can be moved from potentially dangerous underground environments. A visual illustration … Continue reading Mine scheduling: an important piece in the pursuit of autonomous mining

Reinforcement learning for grinding – New publication!

About a year ago, me and my colleague Mattias Hallén started investigating the use of reinforcement learning in controlling grinding circuits in mineral processing. The work has been done in collaboration with the mining company Boliden, and it has currently been showcased at various avenues: IEEE Conference on Emerging Technologies and Factory Automation 2019 in … Continue reading Reinforcement learning for grinding – New publication!

Licentiate degree

On November 23rd I successfully defended my licentiate thesis, where Christian Schulte acted as opponent. Besides giving tons of valuable feedback on my approach, he summarized my thesis with the following bullets: Convincingly demontrates that short-term underground mine scheduling can be understood as a flow-shop problem can be elegantly modelled using constraint programming can be … Continue reading Licentiate degree

2018 Conference on Control Technology and Applications

I presented at the 2018 IEEE Conference on Control Technology and Applications in Copenhagen on the industrial session "Indoor positioning in mines". The presentation was called "Applications based on positioning in underground mines" and was based on presenting how indoor positioning is currently used in control systems, autonomous machines, and production optimization.

Optimized Medium-range Mine Scheduling (OMMS)

The Optimized Medium-range Mine Scheduling project (OMMS) was an opportunity for ABB, Boliden, Luleå University of Technology, and Nordic Rock Tech Center to discuss shortterm mine scheduling in its proper context and surroundings. The main outcome from this project is an integration between a system for automatic shortterm mine scheduling and a third-party discrete event … Continue reading Optimized Medium-range Mine Scheduling (OMMS)