Anders Skoogh

Anders Skoogh

Associate Professor, PhD

Affiliation: Chalmers tekniska högskola

Associate Professor with expertise in data management for Production Service and Maintenance Systems.

Anders Skoogh (PhD) is an Associate Professor at Chalmers and the Department of Product and Production Development. He earned the degree of Licentiate of Engineering in 2009 and his PhD in Production Systems in 2011, both from Chalmers. Before starting his research career, he accumulated industrial experience from being a logistics developer at Volvo Cars. His main research area is efficient management of production data. These data are important in development of sustainable production systems and as well as for decision support in Production Service and Maintenance Systems.


Swedish manufacturing industry utilizes approximately 55% of existing production resources. Anders Skoogh means that companies increasing their resource utilization will gain profitability substantially, e.g. by reduced investments to meet higher market demands. He also highlights the connection between reduced waste in production resources and sustainability. Most companies have problems with machine downtime and that other resources have to wait in idle or blocked states, so called system losses. Anders’ research focuses on automating the management of production data such as repair times and breakdown frequencies. These data are then used as decision support in Production Service and Maintenance Systems and in simulation of production flows to increase reliability and reduce unnecessary downtime. In his PhD thesis, Anders developed a concept for automated management of production data and an associated software demonstrator (GDM-Tool). The concept has proven very efficient in several case studies at international companies in the automotive and aerospace industries. The reduced time-consumption enables real-time priorities of service and maintenance activities as well as more frequent use of virtual tools for development of production flows, e.g. discrete event simulation.


Streamlined Modeling and Decision Support for Fact-based Production Development (StreaMod)

The integration of data management systems, simulation software and optimization algorithms have been shown to increase throughput in existing production but also allow expanded use of virtual tools in the preparation phases. This in turn leads to shorter development times for new production systems and products. The project has also contributed to greater understanding and concrete improvements in the processes of collecting and assure the quality of production data. This in turn increases the quality in both simulations and direct data-driven analyzes.

2013 – 2017


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