ENBIS 2021 Spring Meeting
from
Monday, 17 May 2021 (09:00)
to
Tuesday, 18 May 2021 (18:00)
Monday, 17 May 2021
09:00
Welcome
Welcome
09:00 - 09:20
09:20
Galvanising inter-disciplinary cooperation in process analysis and control in the process industries
-
David Littlejohn
Galvanising inter-disciplinary cooperation in process analysis and control in the process industries
David Littlejohn
09:20 - 09:55
Modern process analysis and control generates a lot of data, especially in the high technology “Chemistry-using” industries. Optimising production of chemicals, drugs, food etc. requires multiple contributions across different disciplines to make sure that data from in situ analysers are correctly obtained, and that the data are used along with other process information to allow intelligent performance monitoring and real-time control. The Centre for Process Analytics and Control Technology (CPACT) was formed in 1997 to provide a forum where the inventers, vendors and users of monitoring and control hardware and software could meet, exchange knowledge, do research and promote best practice. One of the thought-leaders and champions of CPACT was Professor Julian Morris FREng who sadly died in 2020. This talk will describe how the founding principles of CPACT have evolved to serve the current community of 45 international member organisations, and it will reflect on the contributions that Julian Morris made in the fields of multivariate statistical process control, process performance modelling and soft sensors. Given the increasing profile of the Industry 4.0 initiative, it is timely to reflect on how key components of this initiative are not new and were researched by Julian and his peers 20-30 years ago. David Littlejohn is the Philips Professor of Analytical Chemistry at the University of Strathclyde. He was a founding member of the Centre for Process Analytics and Control Technology (CPACT) and is currently the Operations Director.
10:00
10:00 - 11:00
Contributions
10:00
Are all data analytics techniques equally useful for process optimization in Industry 4.0?
-
Alberto J. Ferrer Riquelme
(
Universitat Politècnica de València
)
10:20
Data driven modelling and optimisation of a batch reactor using bootstrap aggregated deep belief networks
-
Jie Zhang
(
Newcastle University
)
10:40
Local batch time prediction based on the mixture of local batch experts: a case study on a polymerization process
-
Francisco Souza
(
Radboud University
)
10:00 - 11:00
Contributions
10:00
Structural Equation Modeling of Coupled Twin-Distillation Columns
-
Laura Castro-Schilo
(
SAS Institute
)
Chris Gotwalt
(
SAS Institute
)
Markus Schafheutle
(
Schafheutle Consulting
)
10:20
Inference and Design Optimization for a Step-Stress ALT under a Log-Location-Scale Family
-
Aruni Jayathilaka
10:40
Order-Restricted Bayesian Inference and Optimal Designs for for the Simple Step-Stress ALT
-
Crystal Wiedner
11:00
Coffee break
Coffee break
11:00 - 11:15
11:15
11:15 - 12:15
Contributions
11:15
Optimal designs for hypothesis testing in the presence of heterogeneous experimental groups
-
Marco Novelli
11:35
Robust strategies to address the uncertainty of the response variable in Optimal Experimental Design
-
Sergio Pozuelo-Campos
(
University of Castilla-La Mancha
)
11:55
Adding points to D-optimal designs
-
Carlos de la Calle-Arroyo
(
Universidad de Castilla-La Mancha
)
11:15 - 12:15
Contributions
11:15
Fleet analytics to avoid unplanned maintenance
-
Franz Langmayr
(
Uptime Engineering
)
11:35
Uncertainty Analysis of Railway Track Measurements
-
Stefan Müllner
(
Consulting in Industrial Statistics
)
11:55
Control Chart for Monitoring a Multiple Stream Process based on Multilayer Perceptron Neural Network, with an Application to HVAC Systems of Modern Trains
-
Guido Cesaro
(
Maintenance & System Engineer, Operation Service and Maintenance Product Evolution, Hitachi Rail Group
)
Gianluca Sposito
(
Department of Industrial Engineering, University of Naples Federico II
)
12:15
Lunch
Lunch
12:15 - 13:00
13:00
13:00 - 14:00
Contributions
13:00
Problem solving session: analysis of batch process data from multiple sources for process improvement and for reduction in testing costs
-
Jacqueline Asscher
(
Kinneret College and Technion
)
13:00 - 14:00
Contributions
13:00
Finite-sample exact prediction bands for functional data: an application to mobility demand prediction
-
Simone Vantini
(
MOX - Dept of Mathematics, Politecnico di Milano, Italy,
)
13:20
Analysis of train and platform occupancy in the railway system of Lombardy: a Functional Data Analysis approach
-
agostino torti
(
politecnico di milano
)
13:40
Safari Njema Project: a multidisciplinary analysis of paratransit mobility in Sub-Saharan countries from GPS data
-
Anna Calissano
(
INRIA Sophia-Antipolis
)
14:05
14:05 - 15:05
Contributions
14:05
Detection of transient changes in urban air pollution by PM10
-
Fatima Ezzahra MANA
(
Université de Technologie de Troyes / Laboratoire Informatique et Société Numérique
)
14:25
Change-point detection in an high-dimensional model with possibly asymmetric errors
-
Nicolas DULAC
14:45
Big DoE: Sequential and Steady Wins the Race?
-
Ben Francis
(
JMP
)
14:05 - 15:05
Contributions
14:05
Monte Carlo methods for Fredholm integral equations
-
Francesca Romana Crucinio
(
Department of Statistics, University of Warwick
)
14:25
Empirical copula methods for short-term temperature forecasting in Austria
-
Elisa Perrone
(
Eindhoven University of Technology
)
14:45
Persistent Homology for Market Basket Analysis
-
Sara Scaramuccia
(
Politecnico di Torino
)
15:05
Coffee break
Coffee break
15:05 - 15:20
15:20
15:20 - 16:20
Contributions
15:20
Physics-based Residual Kriging for oil production rates prediction
-
Riccardo Peli
(
MOX, Department of Mathematics, Politecnico di Milano
)
15:40
Video/Image Statistical Process Monitoring in Additive Manufacturing via Partial First Order Stochastic Dominance
-
Panagiotis Tsiamyrtzis
(
Politecnico di Milano
)
16:00
Application of Simplicial Functional Data Analysis to Statistical Process Control in Additive Manufacturing
-
Riccardo Scimone
(
Politecnico di Milano
)
15:20 - 16:20
Contributions
15:20
Reinforcement Learning for Batch Optimization
-
Ricardo Rendall
(
Dow Inc.
)
15:40
Combined tests for high-dimensional industrial data
-
Marco Marozzi
(
Ca' Foscari University of Venice (Italy)
)
16:00
Investigation of the Condition-Based Maintenance under Gamma Degradation Process
-
David Han
16:25
16:25 - 17:25
Contributions
16:25
Designing conjoint experiments for industrial and business research
-
Eric Nyarko
(
University of Ghana
)
16:45
How can we help managers
-
Roland Caulcutt
(
Caulcutt Associates
)
16:25 - 17:25
Contributions
16:25
Making better decisions based on simulation workshop
-
Erik Flores
(
KTH University, Sweden
)
Hassanein Sater
(
Astra Zeneca, UK
)
JONATHAN SMYTH-RENSHAW
(
JSR Business Consultancy
)
Omar McCarthy
(
Astra Zeneca, UK
)
19:00
Evening social: The conference site will be open throughout the event. Grab yourself a real-life drink (water, tea, coffee, beer, wine,….. whatever!) and meet and chat with other conference attendees in the virtual coffee area. You may also like to visit the poster hall and sponsor booths or leave your comments and suggestions in the Information Kiosk.
Evening social: The conference site will be open throughout the event. Grab yourself a real-life drink (water, tea, coffee, beer, wine,….. whatever!) and meet and chat with other conference attendees in the virtual coffee area. You may also like to visit the poster hall and sponsor booths or leave your comments and suggestions in the Information Kiosk.
19:00 - 21:00
The conference site will be open throughout the event. Grab yourself a real-life drink (water, tea, coffee, beer, wine,….. whatever!) and meet and chat with other conference attendees in the virtual coffee area. You may also like to visit the poster hall and sponsor booths or leave your comments and suggestions in the Information Kiosk.
Tuesday, 18 May 2021
09:00
Welcome to day 2
Welcome to day 2
09:00 - 09:20
09:20
Using AI to improve our understanding of waste-water processing
-
Stephen McGough
Using AI to improve our understanding of waste-water processing
Stephen McGough
09:20 - 09:55
Waste-water treatment is an energy intensive process leading to many environmental concerns. It is very important to remove chemical compounds such as oestrogen from the effluent before it can be safely released into the environment. With increased restrictions on the amount of certain chemical compounds which can be tolerated in the released water there is a need to identify how to efficiently remove enough of these compounds. Compounds are removed by bacteria which exist in the processing system. Current approaches to identifying the best bacteria are based around lab-based experiments on small volumes of waste-water or computer simulations of small volumes of bacteria. However, there is a disconnect between these experiments and what happens in a full-scale wastewater treatment plant. In this talk I shall explain how we’re using AI to scale up and make more realistic simulations of bacterial systems to meet new effluent restrictions. Stephen McGough is a Senior Lecturer in the School of Computing at Newcastle University. He heads up a team of data scientists working in the application and development of Machine Learning techniques to solve real-world challenges.
10:00
10:00 - 11:00
Contributions
10:00
Outlier detection using robust random cut forest
-
Basiru Usman
(
NC State University
)
10:20
Efficient Accounting for Estimation Uncertainty in Coherent Forecasting of Count Processes
-
Christian Weiß
(
Helmut Schmidt University
)
10:40
Bootstrapping, cross validation and SVEM: Differences and similarities with applications to industrial processes
-
Ron Kenett
(
KPA Group & Samuel Neaman Institute, Technion, Israel
)
Chris Gotwalt
(
JMP Division, SAS, Research Triangle
)
10:00 - 11:00
Contributions
10:00
High-dimensional copula-based classification using truncation and thresholding
-
Max-Carl Wachter
(
University of Wuerzburg
)
10:20
Portfolio optimisation in very high dimension based on copula association modelling
-
Philipp Haid
(
University of Wuerzburg
)
10:40
High-purity processes GLR control charts for composite change-point scenarios
-
Caterina Rizzo
(
Dow Inc.
)
11:00
Coffee break
Coffee break
11:00 - 11:15
11:15
11:15 - 12:15
Contributions
11:15
A permutation-based solution for Machine Learning model selection
-
Riccardo Ceccato
(
University of Padova
)
11:35
Applications of Design of Experiments and Machine Learning in Product Innovation
-
Luca Pegoraro
(
University of Padova
)
11:55
Consumers’ satisfaction with a product analysed through the lens of fuzzy theory
-
Nicolò Biasetton
(
Università degli Studi di Padova
)
11:15 - 12:15
Contributions
11:15
Statistical Engineering: Finding Our Identity
-
Caleb King
(
JMP Division, SAS Institute Inc.
)
11:35
Statistical Engineering. Thoughts on the current situation and proposals for the future
-
Xavier Tort-Martorell
(
Universitat Politècnica de Catalunya. BarcelonaTECH
)
11:55
Enabling Scientists and Engineers to deploy and exploit Data Science in the Process Industries
-
Hadley Myers
(
JMP
)
12:15
Lunch
Lunch
12:15 - 13:00
13:00
13:00 - 14:00
Contributions
13:00
Artificial Intelligence-based Autonomous Control for Process Industry Improvement: A Case Study for Chemistry Control for Tissue Mill
-
Kamran Paynabar
(
ProcessMiner
)
13:20
Modeling and forecasting fouling in multiproduct batch processes
-
Joel Sansana
(
University of Coimbra
)
13:40
Predictive Control Charts (PCC): A Bayesian Approach in Online Monitoring of Short Runs
-
Konstantinos Bourazas
(
Athens University of Economics and Business
)
13:00 - 14:00
Contributions
13:00
Experimental designs and Kriging modelling: the use of strong orthogonal arrays
-
Nedka Dechkova Nikiforova
(
Department of Statistics Computer Science Applications "G. Parenti", University of Florence
)
13:20
Statistical learning methods for Predictive Maintenance in plasma etching processes
-
Diego Zappa
(
Università Cattolica del Sacro Cuore - Milan
)
13:40
Non-parametric local capability indices for industrial planar artefacts
-
Riccardo Borgoni
(
Università di Milano-Bicocca
)
14:05
14:05 - 15:05
Contributions
14:05
Towards Robust process design. The sensitivity analysis using machine learning methods
-
Tina Sadat DANESH ALAGHEHBAND
(
Chemical Engineering Laboratory, Université de Toulouse, CNRS, Toulouse, France, LGC UMR 5503
)
14:25
Review of Quantum Algorithms and Quantum Information for Data Science
-
David Han
14:45
Process Monitoring – Fundamentals, Experiences and Use-Cases
-
Raino Petricevic
(
iNDTact GmbH
)
14:05 - 15:05
Contributions
14:05
Use of Functional Data Explorer in a mixture design for tribological performance prediction
-
Victor GUILLER
14:25
Interpretability and Verification in AI
-
PIERRE HAROUIMI
14:45
21st Century Screening Designs
-
Bradley Jones
(
SAS Institute
)
15:05
Coffee break
Coffee break
15:05 - 15:20
15:20
15:20 - 16:20
Contributions
15:20
Robust MCUSUM for Phase II Linear Model Profile Monitoring
-
Abdel-Salam Abdel-Salam
(
Associate Professor of Statistics
)
15:40
Space-Time Monitoring of Count Data for Public Health Surveillance
-
Arda Vanli
Nour Alawad
(
Florida State University
)
16:00
Signed sequential rank CUSUMs
-
Corli van Zyl
(
North-West University
)
15:20 - 16:20
Contributions
15:20
Signed Sequential Rank Shiryaev-Roberts Schemes
-
Corli van Zyl
(
North-West University
)
15:40
Dynamically synchronizing production data for industrial soft-sensors
-
Tim Offermans
(
Radboud University
)
16:00
An investigation of the utilisation of different data sources in manufacturing with application in injection moulding
-
Georg Rønsch
(
DTU Compute, Department of Applied Mathematics and Computer Science Statistics and Data Analysis
)
Murat Kulahci
(
DTU Compute, Department of Applied Mathematics and Computer Science Statistics and Data Analysis
)
16:25
Closing Session
Closing Session
16:25 - 16:55