Jonathan Gaudreault is the director of CRISI, a research consortium dedicated to Industry 4.0 systems engineering. Over the last fifteen years he has led a number of key projects related to operations planning and scheduling, bringing together ideas from the artificial intelligence and operations research fields. He previously worked as an R&D manager in the software industry and was awarded as "One to watch" by the Federation de l'Informatique du Québec (OCTAS award). Pr. Gaudreault and other researchers from the FORAC Research Consortium were recognized with the Brockhouse Canada Prize for Interdisciplinary Research in Science and Engineering, Canada’s premier award for interdisciplinary research.

Conference abstract: Intelligence artificielle en contexte industriel 4.0 : un monstre de données

Capturing industrial data and turn them into a gold is often considered an easy task. However, in practice, data are going to make you sweat! During this talk, professor Gaudreault will give you an overview of the most common problems (and solutions) for this kind of projects.

Sebastien Guerard has a bachelor’s degree in chemical engineering and a master’s degree in engineering, which he completed in 2010 at the Université du Quebec à Chicoutimi. After that he worked for one year at Hatch, where he specialized in CFD modeling. He then started working at Rio Tinto in 2011. His main areas of expertise include cell design and the optimization of the process control algorithms. He has developed several models on different aspects of the reduction process, some based on the finite element or volume methods, others on various types of mathematical, physical and statistical modeling. More recently, he has been involved in the design and application of new sensors to the reduction cells.

Conference abstract: Modeling the aluminum reduction process – approaches, strategies and examples

Modeling the aluminum reduction process is notoriously difficult: it includes a vast range of interrelated physical phenomena (electrical, thermal, mechanical, electrochemical, magnetohydrodynamics, etc.) taking place in an industrial environment where measurements are limited and imperfect.

The objective of this training is to present some examples of modeling that were successfully applied in the industry. We will discuss a model of the distribution of the ACD and current, an algorithm to detect as early as possible the anodes that were set at the wrong height, and a model of the CO₂ bubbles underneath an anode. Beyond the examples themselves, we will try to emphasize the best strategies to use when developing a model: how to represent accurately the physical phenomena under consideration, how to aim for the right level of complexity, how to combine models, and how to integrate efficiently all the new data which is now available.

Prof. Chartrand obtained his engineering diploma in Materials Science in 1994, and his Ph.D. degree in Metallurgical engineering from Polytechnique Montréal in 2000. He is professor at the Department of Chemical Engineering at Polytechnique Montréal since 2003. He is co-director of the Center for Research in Computational Thermochemistry (CRCT) where he is co-developing the FactSage Thermochemical Software with his team since 1995. FactSage is licensed in more than 400 industrial and governmental research centres and by more than 400 universities around the world. The research interests of prof. Chartrand are the development of thermodynamic and physical property models for mixtures of molten salts and oxides and for light metal alloys. Prof. Chartrand is directing, since 2004, the NSERC project “A Virtual Laboratory for the Aluminum Industry” in partnership with Alcoa, Constellium, Elysis, Hydro Aluminium and Rio Tinto. He was co-investigator in the RDCell1 and RDCell2 projects on the sideledge formation and alumina dissolution in Hall-Heroult cells (CRSNG – UQAC – Poly - Rio Tinto). He received the Grand Prix Alcan 2007 of the French Académie des Sciences for his modeling work on molten cryolite, and the 2013 Léo-Derikx Synergy Award from NSERC for his industrial collaborations. Prof. Chartrand published more than 130 scientific papers in peer-reviewed journals and more than 60 other articles and reports, including a book chapter and two licences. He is supervising and co-supervising around ten graduate students and several research associates.

Conference title: Thermodynamic Modeling of Molten Salts and Metal Phases for the Production of Aluminum Alloys

Bernard Clément, PhD, is a full professor at the Mathematics and industrial Engineering Department of Polytechnique Engineering School affiliated with the Université de Montréal. He has more than 40 years of experience in teaching advanced and applied statistical methods and quality management to engineers and scientists. His partial list of clients included IBM, Sidbec-Dosco, Noranda Research Center, Bolting Technology Council, Nortel, Institut de Recherche en Biotechnologie, Compagnie Générale des Eaux (Vivendi), Bell, Postes Canada, DALSA semiconducteurs, Cardianove, Camoplast and many research organizations. He is an elected member of the International Statistical Institute (ISI) and member of the American Statistical Association (ASA). He was vice-president of the Canada Quality Council, administrator of the Association Québécoise de la Qualité (Mouvement Québécois Qualité). He was president de la Société Statistique de Montréal and a member of the ISO committee of the Standard Council du Canada. He created Genistat Conseils Inc., a consulting firm specialized in design and analysis of statistical studies. His main product is the transfer of knowledge, expertise and management applied to the improvement of design and quality of products.

Conference title: Planification et analyse statistique d’expériences : méthode scientifique incontournable pour comprendre et optimiser un processus

Dr Alexandre Bois-Brochu is the R&D Group Leader for Additive Manufacturing and has been working at the Quebec Metallurgy Center (CMQ) since 2012. He has completed his Ph.D. in 2017 in Material and Metallurgical Science from Laval University on the “Effects of crystallographic texture on static mechanical properties of Al-Li aerospace alloy 2099 T83”. He graduated in Metallurgical and Material Engineering in Laval University. At CMQ, he is responsible for AM projects, including projects related to directed energy deposition (DED) such as Optomec and Hybrid Manufacturing systems, laser powder bed fusion SLM 125 and ultrasonic additive manufacturing from Fabrisonic, as well as heat treatment development and NDT associated with AM

Conference abstract: Additive Manufacturing of Aluminium – Considerations and Potential

Aluminium and its alloys present great potential for additive manufacturing, but possess however some intrinsic constraint. The presentation will cover aluminium alloys characteristics which govern their usage in additive manufacturing. The different AM processes will then be presented in relation to their capability to produce aluminium parts. Microstructural characteristics as a function of the process, the mechanical behaviour of Al alloys and non-destructive testing considerations will also be covered.

Jean-François Béland has been a research officer at the National Research Council of Canada for 14 years. He works on various metal forming processes at temperatures ranging from room to high temperature, specializing in computer-aided techniques, such as finite element and meshless methods, to study and optimize the forming, failure and joining behavior of aluminum.

Conference abstract: Prediction of damage and failure of extruded components for crash applications

The design of extruded aluminum crash structures including crash rails, crash cans, bumpers and structural body components is dependent on specific requirements such as the stored energy level, maximum allowable crush force and space available. Above all, the mechanical behavior of the materials used will establish the extruded section dimensions to meet these criteria. However, at the design phase, it is challenging to evaluate accurately the crash performance of a given material due to the inherent complex states of stress and strain paths. Know-how is typically used for selection of the alloy, temper and processing conditions. Even then, this choice often needs to be modified after extrusion trials in order to reach the required level of ductility, usually with a trade-off in strength. This training describes the development of a virtual tool to more accurately predict the crash performance of a given material/processing route combination, upstream at the design phase.