Maintenance in digitalised manufacturing: Delphi-based scenarios for 2030 J Bokrantz, A Skoogh, C Berlin, J Stahre International Journal of Production Economics 191, 154-169, 2017 | 285 | 2017 |
Smart Maintenance: an empirically grounded conceptualization J Bokrantz, A Skoogh, C Berlin, T Wuest, J Stahre International Journal of Production Economics 223, 107534, 2020 | 175 | 2020 |
Identification of maintenance improvement potential using OEE assessment T Ylipää, A Skoogh, J Bokrantz, M Gopalakrishnan International Journal of Productivity and Performance Management 66 (1), 126-143, 2017 | 152 | 2017 |
Smart Maintenance: a research agenda for industrial maintenance management J Bokrantz, A Skoogh, C Berlin, T Wuest, J Stahre International journal of production economics 224, 107547, 2020 | 144 | 2020 |
A methodology for input data management in discrete event simulation projects A Skoogh, B Johansson 2008 Winter Simulation Conference, 1727-1735, 2008 | 136 | 2008 |
A data-driven algorithm to predict throughput bottlenecks in a production system based on active periods of the machines M Subramaniyan, A Skoogh, H Salomonsson, P Bangalore, J Bokrantz Computers & Industrial Engineering 125, 533-544, 2018 | 114 | 2018 |
Input data management in simulation–Industrial practices and future trends A Skoogh, T Perera, B Johansson Simulation Modelling Practice and Theory 29, 181-192, 2012 | 104 | 2012 |
An intelligent approach for data pre-processing and analysis in predictive maintenance with an industrial case study ET Bekar, P Nyqvist, A Skoogh Advances in Mechanical Engineering 12 (5), 1687814020919207, 2020 | 70 | 2020 |
Data quality problems in discrete event simulation of manufacturing operations J Bokrantz, A Skoogh, D Lämkull, A Hanna, T Perera Simulation 94 (11), 1009-1025, 2018 | 70 | 2018 |
Handling of production disturbances in the manufacturing industry J Bokrantz, A Skoogh, T Ylipää, J Stahre Journal of Manufacturing Technology Management 27 (8), 1054-1075, 2016 | 70 | 2016 |
A generic hierarchical clustering approach for detecting bottlenecks in manufacturing M Subramaniyan, A Skoogh, AS Muhammad, J Bokrantz, B Johansson, ... Journal of Manufacturing Systems 55, 143-158, 2020 | 67 | 2020 |
Automated input data management: evaluation of a concept for reduced time consumption in discrete event simulation A Skoogh, B Johansson, J Stahre Simulation 88 (11), 1279-1293, 2012 | 65 | 2012 |
Symbiotic simulation system: Hybrid systems model meets big data analytics BS Onggo, N Mustafee, A Smart, AA Juan, O Molloy 2018 Winter Simulation Conference (WSC), 1358-1369, 2018 | 64 | 2018 |
Discrete event simulation to generate requirements specification for sustainable manufacturing systems design B Johansson, A Skoogh, M Mani, S Leong Proceedings of the 9th Workshop on performance metrics for intelligent …, 2009 | 64 | 2009 |
A test implementation of the core manufacturing simulation data specification M Johansson, B Johansson, A Skoogh, S Leong, F Riddick, YT Lee, ... 2007 Winter Simulation Conference, 1673-1681, 2007 | 63 | 2007 |
Input data management methodology for discrete event simulation N Bengtsson, G Shao, B Johansson, YT Lee, S Leong, A Skoogh, ... Proceedings of the 2009 winter simulation conference (WSC), 1335-1344, 2009 | 60 | 2009 |
An algorithm for data-driven shifting bottleneck detection M Subramaniyan, A Skoogh, M Gopalakrishnan, H Salomonsson, ... Cogent Engineering 3 (1), 1239516, 2016 | 51 | 2016 |
Effects of information content in work instructions for operator performance D Li, S Mattsson, O Salunkhe, Å Fast-Berglund, A Skoogh, J Broberg Procedia Manufacturing 25, 628-635, 2018 | 50 | 2018 |
Quantifying the effects of maintenance–a literature review of maintenance models C Lundgren, A Skoogh, J Bokrantz Procedia CIRP 72, 1305-1310, 2018 | 50 | 2018 |
Machine criticality assessment for productivity improvement: Smart maintenance decision support M Gopalakrishnan, A Skoogh, A Salonen, M Asp International Journal of Productivity and Performance Management 68 (5), 858-878, 2019 | 47 | 2019 |