Process Industries have been an important part of Industrial Statistics for many years. Process industry data includes real-time, multivariate measurements as well as operations data relating to quality of finished output. Machine learning, artificial intelligence and predictive modelling are increasingly important and will enrich the statistical toolbox in industry. Future IoT and Industry 4.0 need these methods to develop and be successful. With the upsurge of interest in data science there are new opportunities for even greater focus on analysis of process industry data. This ENBIS Spring meeting aims to showcase new ideas and motivate further research and applications in the future.
Topics include but are not limited to:
- Artificial intelligence
- Bayesian adaptive design
- Data quality
- DoE and product design
- Forecasting technologies
- Importance of domain knowledge
- Machine learning
- Maintenance
- Multivariate analysis in industry
- Predictive modelling
- Process monitoring in Industry 4.0
- Reliability, robustness
- Role of statistical thinking in process industries
- Simulation, emulators and metamodels
- Speed & demand vs quality
Co-chairs
Shirley Coleman – Technical Director NUSolve, Newcastle University
Andrea Ahlemeyer-Stubbe – Director Strategic Analytics, Servicepro Agentur für Dialogmarketing und Verkaufsförderung GmbH
Program Committee
Nikolaus Haselgruber -CEO CIS consulting of industrial statistics GmbH
Kristina Krebs – Co-Founder and Business Development Director of prognostica, Würzburg
Marcus Perry – Professor of Statistics, University of Alabama
Marco Reis – Professor of Chemical Engineering, University of Coimbra
Eva Scheideler – Professor of Simulation, Physics and Mathematics, OWL University of Applied Sciences and Arts
Jonathan Smyth-Renshaw – JSR Training & Consultancy
Grazia Vicario – Prof.ssa, Department of Mathematical Sciences, Politecnico di Torino
Registration
Registration is free – donations are welcome.
Publication
A special issue of the Wiley Journal Applied Stochastic Models in Business and Industry on Data Science in Process Industries is being planned.
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