A methodology for continuous quality assurance of production data. - Jon Bokrantz; Anders Skoogh; Jon Andersson; Jacob Ruda; Dan Lämkull (WSC, 2015)

A data-driven algorithm to predict throughput bottlenecks in a production system based on active periods of the machines. - Mukund Subramaniyan; Anders Skoogh; Hans Salomonsson; Pramod Bangalore; Jon Bokrantz (Comput. Ind. Eng., 2018)

Data quality problems in discrete event simulation of manufacturing operations. - Jon Bokrantz; Anders Skoogh; Dan Lämkull; Atieh Hanna; Terrence Perera (Simul., 2018)

A data-driven approach to diagnosing throughput bottlenecks from a maintenance perspective. - Mukund Subramaniyan; Anders Skoogh; Azam Sheikh Muhammad; Jon Bokrantz; Björn Johansson 004; Christoph Roser (Comput. Ind. Eng., 2020)

Perspectives on the Future of Maintenance Engineering Education. - Jon Bokrantz; Anders Skoogh (APMS (5), 2021)

Battery Production Systems: State of the Art and Future Developments. - Mélanie Déspeisse; Björn Johansson 004; Jon Bokrantz; Greta Braun; Arpita Chari; Xiaoxia Chen; Qi Fang; Clarissa A. González Chávez; Anders Skoogh; Johan Stahre; Ninan Theradapuzha Mathew; Ebru Turanoglu Bekar; et al. (APMS (4), 2023)

Understanding Stakeholder Requirements for Digital Twins In Manufacturing Maintenance. - Siyuan Chen; Juan Pablo González Sánchez; Ebru Turanoglu Bekar; Jon Bokrantz; Anders Skoogh; Paulo Victor Lopes (WSC, 2023)

Data-Driven Smart Maintenance Decision Analysis: A Drone Factory Demonstrator Combining Digital Twins and Adapted AHP. - Paulo Victor Lopes; Siyuan Chen; Juan Pablo González Sánchez; Ebru Turanoglu Bekar; Jon Bokrantz; Anders Skoogh (WSC, 2023)

Enhancing Digital Twins With Deep Reinforcement Learning: A Use Case in Maintenance Prioritization. - Siyuan Chen; Paulo Victor Lopes; Silvan Marti; Mohan Rajashekarappa; Sunith Bandaru; Christina Windmark; Jon Bokrantz; Anders Skoogh (WSC, 2024)