Nikolai West, M.Sc., studied industrial engineering with a focus on production management at the Technical University of Dortmund with distinction and an additional year abroad at the "National Taiwan University of Science and Technology" in Taipei, Taiwan (R.O.C.). While still a student, he worked for various companies in Germany, India and China. Mr. West works as a research assistant at the Institute of Production Systems at the Technical University of Dortmund and is doing his PhD in the area of networked and integrated application of industrial data analysis in dynamic value networks. Accordingly, his work focuses on solving industrial problems with the help of data analytic tools and methods.

• Networked and integrated application of industrial data analysis
• Value-creating and competence-oriented collaboration in dynamic value networks
• Data-driven design of production systems under the influence of variability

• Supervision of project and final theses
• Execution of lectures of the IPS
• Execution of tutorials to the lectures of the IPS

• Analysis of production data in assembly planning
• Value stream oriented layout and workplace design
• Strategic introduction of Industry 4.0 and IoT technologies

• West, Nikolai; Syberg, Marius; Deuse, Jochen (2021): A Holistic Methodology for Successive Bottleneck Analysis in Dynamic Value Streams of Manufacturing Companies. In: Proceedings of the Changeable, Agile, Reconfigurable and Virtual Production Conference and the World Mass Customization & Personalization Conference (CARV MCPC), 01.-02.11.2021, Aalborg (Denmark), p. 612-619. DOI: 10.1007/978-3-030-90700-6_69
• Schlegl, Thomas; Schlegl, Stefan; West, Nikolai; Deuse, Jochen (2021): Scalable anomaly detection in manufacturing systems using an interpretable deep learning approach. In: Proceedings of the 54th CIRP Conference on Manufacturing Systems (CIRP CMS), 22.-24.09.2021, Athens (Greece).
• West, Nikolai; Hoffmann, Florian; Schulte, Lukas; Moreno, Victor Hernandez; Deuse, Jochen (2021): An Approach for Deep Reinforcement Learn­ing for Production Program Planning in Value Streams. In: Franke, Jörg; Schuderer, Peter (Hrsg.) Tagungsband 19. ASIM-Fachtagung Si­mu­la­tion in Pro­duk­tion und Logistik. Erlangen, 15.-17.09.2021. Göttingen: Cuvillier Verlag, p. 345-356. ISBN: 978-3-7369-7479-1
• West, Nikolai; Gries, Jonas; Brockmeier, Carina; Göbel, Jens C.; Deuse, Jochen (2021): Towards integrated Data Analysis Quality: Criteria for the application of Industrial Data Science. In: Proceedings of the 22nd International Conference on Information Reuse and Integration for Data Science (IRI), 10.-12.08.2021, Las Vegas (Nevada, USA), p. 131-138. 10.1109/IRI51335.2021.00024
• Ostermeier, Frederik; West, Nikolai; Deuse, Jochen (2021): How moderator variables affect scheduling objectives in unpaced mixed-model assembly lines. In: Proceedings of the 26th International Conference on Production Research (ICPR), 18.-21.07.2021, Taichung (Taiwan).
• Deuse, Jochen; West, Nikolai; Syberg, Marius (2021): The Evolution of Scientific Management: From Industrial Engineering to Industrial Data Science. In: Proceedings of the 15th International Conference on Industrial Engineering and Industrial Management and XXV Congreso de Ingeniería de Organización (ICIEIM), 8.-9.07.2021, Burgos (Spain), p. 99-101. Access via Pressbook
• West, Nikolai; Schlegl, Thomas; Deuse, Jochen (2021): Feature extraction for time series classification using univariate descriptive statistics and dynamic time warping in a manufacturing environment. In: IEEE 2nd International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering (ICBAIE), 26.-28.03.2021, Nanchang (China), p. 762-768. DOI: 10.1109/ICBAIE52039.2021.9389954
• Wöstmann, René; Barthelmey, André; West, Nikolai; Deuse, Jochen (2019): Retrofit Approach for Predictive Maintenance. In: Schüppstuhl, T., Tracht, K. et al. (Hg.): Tagungsband des 4. Kongresses Montage Handhabung Industrieroboter. 4. Fachkolloquium der Wissenschaftlichen Gesellschaft für Montage, Handhabung und Industrierobotik (MHI). 26.-27.02.2019, Dortmund (Germany). Wissenschaftliche Gesellschaft für Montage, Handhabung und Industrierobotik. Berlin: Springer Vieweg, p. 94-406. DOI: 10.1007/978-3-662-59317-2_10