School of Engineering Science
I am the leader of the research group Production & Automation Engineering which consists of approx. 40 researchers working within the area of virtual engineering. The group’s research is to a large extent applied and carried out in close cooperation with industrial partners, mainly within the manufacturing industry. The research covers various areas such as simulation, optimization, robotics, decision-support systems and continuous improvements.
My own research is focused on solving complex real-world optimization problems through soft computing approaches, and on the development of IT-tools for supporting executing optimized solutions in practice. The problems my research is targeting is usually related to production or logistics and found within both the private and the public sector. I am leading several research projects and supervise ten PhD students.
An Interpretive Structural Modeling of Teamwork Training in Higher EducationFathi Masood, Ghobakhloo Morteza, Syberfeldt AnnaEducation Sciences, 2019, 9(1), 1-20.
An optimization model for balancing assembly lines with stochastic task times and zoning constraints
Fathi Masood, Nourmohammadi Amir, Ng Amos H. C. et al.IEEE Access, 2019, 7, 32537-32550.
A holistic solution for integrating a simulated twin of an automation system during the system’s entire life-cycleSyberfeldt Anna, Ayani Mikel, Holm MagnusAdvances in Manufacturing Technology XXXII: Proceedings of the 16th International Conference on Manufacturing Research, incorporating the 33rd National Conference on Manufacturing Research, September 11–13, 2018, University of Skövde, Sweden (405-410). Amsterdam: IOS Press, 2018.
A New Algorithm Using the Non-dominated Tree to improve Non-dominated Sorting
Gustavsson Patrik, Syberfeldt AnnaEvolutionary Computation, 2018, 26(1), 89-116.
A Review of Simulation Based Life Cycle Assessment in Manufacturing Industry
Liu Yu, Syberfeldt Anna, Strand MattiasAdvances in Manufacturing Technology XXXII: Proceedings of the 16th International Conference on Manufacturing Research, incorporating the 33rd National Conference on Manufacturing Research, September 11 – 13, 2018, Skövde, Sweden (381-386). Amsterdam, Berlin, Washington,DC: IOS Press, 2018.
A two-step multi-objectivization method for improved evolutionary optimization of industrial problems
Syberfeldt Anna, Rogström JoelApplied Soft Computing, 2018, 64, 331-340.
An optimization model for material supply scheduling at mixed-model assembly lines
Fathi Masood, Syberfeldt Anna, Ghobakhloo Morteza et al.Procedia CIRP, 2018, 72, 1258-1263.
Human-robot collaboration – towards new metrics for selection of communication technologies
Gustavsson Patrik, Holm Magnus, Syberfeldt Anna et al.Procedia CIRP, 2018, 72, 123-128.
Operators perspective on augmented reality as a support tool in engine assembly
Danielsson Oscar, Syberfeldt Anna, Holm Magnus et al.Procedia CIRP, 2018, 72, 45-50.
Simulation-based Optimization for Facility Layout Design in Conditions of High Uncertainty
Flores Garcia Erik, Ruiz Zúñiga Enrique, Bruch Jessica et al.Procedia CIRP, 2018, 72, 334-339.