“Artificial Intelligence: Deciding like people”
Systems based on Artificial Intelligence have reached levels of competence in decision making that in many areas equal, if not surpass, those of people. They usually incorporate algorithms that, although can increase the capacity and efficiency of people in their respective contexts of action, could also replace them, something that notably worries the whole society. Thus, avoiding possible dysfunctions in these systems, both in terms of operation and substitution of people, is a priority social, scientific, and technological objective, which makes it more necessary than ever to have models that include all the richness and variety of the decision problems to be faced. These models, because their final objective is to be implemented on computers, must incorporate elements and specificities that until now had not been necessary to consider. This talk is devoted to describing all these aspects, as well as the opportunities and threats that the omnipresence of Artificial Intelligence in our lives represents for the future, even in the present.
PhD. José Luis Verdegay – Computer Science and Artificial Intelligence Department, Universidad de Granada, Spain
José Luis Verdegay is a Professor of Computer Science and Artificial Intelligence at the University of Granada (UGR) in Spain, and Director of the Decision Modeling and Optimization Research Group. He has held numerous positions at that University, in different ministerial agencies of the Spanish government and in the TEMPUS Office of the European Union. Between 2008 and 2015 he was a delegate of the Rector of the UGR for ICT. Since 2015 he has been regional director of the Ibero-American University Association for Postgraduate Studies (AUIP). Author of more than 400 scientific publications, he has an h-index of 54. On the other hand, he has the special teaching category of Visiting Professor at the Technological University of Havana, the Central University of Las Villas, and the University of Holguin (Cuba). He is a Fellow of the International Fuzzy Systems Association (IFSA), IEEE Senior Member, Honorary Member of the Academy of Mathematics and Computer Science of Cuba and Distinguished Guest of the National University of Trujillo (Peru). Among his topics of interest are decision and optimization problems in Artificial Intelligence, and the design, implementation, and application of Autonomous Decision Systems in the tourism sector and intermodal transportation.
“Towards the Supply Chain 4.0”
This session will define and address the concept of Industry 4.0 (I4.0) from the perspective of production management and engineering. Concretely, the main factors that facilitate the transformation towards I4.0 as well as the main barriers to its implementation will be identified. Also, the current state of supply chain 4.0 implementations will be considered from the perspective of sustainability but also from the perspective of the main digital and production technologies.
PhD. Josefa Mula – Department of Business Management, Universitat Politècnica de València (UPV), Spain
Professor of the Department of Business Management at the Universitat Politècnica de València (UPV). She is a member of the Research Centre in Production Management and Engineering (CIGIP) of the UPV. Her teaching and research interests focus on production engineering and management, operations research and supply chain optimisation and simulation. She is editor-in-chief of the International Journal of Production Management and Engineering. She regularly serves as an associate editor, guest editor, member of scientific committees of international journals and conferences, and as a reviewer of scientific journals. She is co-author of more than 100 articles published in international books and high-quality journals. Currently, she is principal investigator of the national project “Optimisation of zero-defect enabling production technologies for supply chains 4.0 (CADS4.0)” (RTI2018-101344-B-I00) and investigator of the European H2020 project “Industrial data services for quality control in smart manufacturing (i4Q)” (958205).
“Solar houses of the future: Technical and business aspects”
The solar houses of the future are already a reality. The development of Building Integrated Photovoltaics (BIPV) has made it possible to replace conventional building materials with photovoltaic materials on parts such as roofs, skylights, facades, pergolas, sliding patio doors and terrace floors. Photovoltaic modules are increasingly being incorporated from the earliest stages in the design and construction of new buildings as their primary source of electricity or as an energy-saving strategy. In this talk, you will learn about these photovoltaic materials, their characteristics, and possible applications as a business opportunity.
PhD. Luis Fernando Mulcue Nieto – Universidad Autónoma de Manizales, Colombia
Luis Fernando Mulcue Nieto has a PhD in Physics, a PhD in Engineering, a Master’s degree in Physics, a Master’s degree in Photovoltaic Solar Energy, and is a Physical Engineer. He has more than 20 distinctions in the fields of engineering, physics, renewable energy and teaching, awarded by institutions in the United States, Europe and Latin America. He has research experience in the fields of nanotechnology, renewable energy, solar photovoltaics and the integration of the latter to architecture (Building Integrated Photovoltaics, BIPV). He has developed and published scientific models and technical standards in BIPV. He has also researched the design of more efficient and economical solar cells for BIPV using nanotechnology. He is currently CEO and founder of the consulting firm BIPV Solar Consulting LLC based in Miami, USA (www.bipvsolarconsulting.com)
“The challenges of the automobile to face the decarbonization of transport”
Environmental and legislative requirements, associated with the reduction of greenhouse gases, are leading the automotive industry to a gradual process of orderly transition from conventional internal combustion engine propulsion systems to zero-emission propulsion systems. In this regard, batteries and hydrogen fuel cells are seen as the technologies with the greatest potential for incorporation into zero-emission vehicle powertrains. In December 2019, the European Commission presented the European Green Deal as the new European growth strategy that sets out a clear agenda to make Europe by 2050 the world’s first climate-neutral continent. This fundamental transformation of the European economy into a decarbonized and competitive economy requires fundamental changes and innovative technologies. Thus, clean hydrogen and its energy carriers were identified as a priority area where the European Union (EU) needs resources to develop these technologies and commercial applications.
PhD. José María López Martínez – University Institute of Automobile Research (INSIA), Technical University of Madrid, Spain
PhD in Industrial Engineering, Director of INSIA, Director of the INSIA Environmental Impact Unit and Professor at the Technical University of Madrid (UPM). He has extensive research experience in the field of alternative vehicle propulsion systems (hybrid, electric and fuel cell) and pollutant emissions due to road traffic, as evidenced by his publications, books and conference papers on these topics. His most recent research activity is focused on the development of models of hybrid and electric vehicle propulsion systems and their integration and validation in vehicles, as well as in the field of pollutant emissions and biofuels in diesel and natural gas engines. He is also Director of the Master in Automotive Engineering and the Master in Hybrid and Electric Vehicle Engineering, both INSIA and UPM degrees, and member of national and international automotive technical committees.
“Exploring the value of analytics to improve decision-making in asset management”
Nowadays many companies are shifting their focus from capital expenditure to operation and maintenance (O&M) costs, as such asset management has received increasing attention. The emergence of industry 4.0 contributed to the hype that the large volumes of data obtained with smart sensors are sufficient to create autonomous and effective predictive maintenance algorithms. However, real-world applications have shown the need to combine the new data-driven approaches with the existing engineering knowledge. In fact, asset management is a multidisciplinary field and to provide the required level of service in the most cost-effective manner, engineering, technology and management must work as a whole. In this talk, we present applications of data-driven approaches which leverage the domain expert knowledge in order to tackle real-world asset management challenges. The examples cover: (i) improved fault detection and diagnosis, (ii) accurate estimation of the remaining useful life, and (iii) efficient maintenance policies boosted by analytical-driven insights. We will also highlight the ongoing challenges on this research line at INESC TEC.
PhD. Luis Guimarães – Department of Industrial Engineering, Universidade do Porto, Portugal
Luis Guimarães is a Professor at the Department of Industrial Engineering and Management of the Faculty of Engineering of the University of Porto, senior researcher at the Industrial Engineering and Management group of the research institute INESC TEC and co-founder of LTPlabs a management consulting firm. He’s main area of activity is Operations Research/Computer Science. Most of his research is problem-driven and aims to develop advanced analytic solutions to be applied in real-world problems. In this context, he has collaborated in more than 30 industry-based research and consulting projects with various companies in the areas of process industry, transportation, retail and energy. He is part of the research team of XFLEX a project recently approved in the H2020 program in which he will lead the research on innovative solutions to optimize maintenance plans and decrease the outage time and increase the availability of flexible hydropower plants. Furthermore, he has been the project leader of several industry collaboration projects at INESC TEC in the area of asset management with companies such as EDP Renováveis, EDP Produção, EDP Distribuição and REN Portgás. Author of several publications in international journals in the field of Operations Research.
“Computer vision systems and agriculture 4.0“
The agri-food industry faces the challenge of increasing productivity and food quality while optimizing the use of inputs. Therefore, new technologies such as computer vision are being applied to develop non-destructive methods, precision agriculture, etc., with which to automate and accelerate planting, harvesting and post-harvest operations. These activities form a new branch of Industry 4.0 called Agriculture 4.0; characterized by integrating data collection and processing to decision processes on field activities or the food industry. This talk will address the basics of obtaining and applying different computer vision techniques to the analysis of agri-food products as well as machine learning and big data methods coupled to these techniques.
PhD. Wilson Manuel Castro Silupu – Universidad Nacional de Frontera, Perú
Dr. Wilson Manuel Castro Silupu is Principal Professor and Research Professor of the Faculty of Food Industry Engineering at the Universidad Nacional de Frontera – Sullana – Peru. He obtained his PhD in Food Science, Technology and Management at the Polytechnic University of Valencia – Spain (Cum Laude Mention), as well as a Master’s Degree in Food Science and Engineering from the University Institute of Food Engineering Research for Development (IuIAD) of the Polytechnic University of Valencia (UPV) – Spain (with Honors). Dr Wilson Castro’s research work has focused on the application of non-invasive technologies such as hyperspectral imaging, multispectral imaging, near infrared spectroscopy, among others coupled with machine learning techniques for the chemometric analysis of food. As a result of this research he has more than thirty publications in several journals indexed in Scopus and WoS and three chapters of specialized books. He is reviewer of different Journals such as Scientific Reports, Food Engineering, Food International Research among others.
“Multi-objective computational intelligence for engineering systems”
Processes and systems in the field of engineering are becoming increasingly complex, making their optimization, modelling or simulation difficult under some circumstances. An alternative to deal with such complexities is the use of computational intelligence tools (e.g., artificial neural networks, evolutionary computation, and fuzzy systems). In the use of such tools, it is common to seek satisfying numerous conflicting objectives and requirements by optimizing a single performance indicator. The solution indicated by this performance indicator may sometimes not be satisfactory. In such a case, a multi-objective optimization may be desirable, since it determines a set of solutions with different degree of compromise between the conflicting objectives. In this talk, we will discuss how multi-objective optimization techniques can be implemented in different computational intelligence tools for engineering systems.
PhD. Gilberto Reynoso Meza – Escola Politécnica, Pontifícia Universidade Católica do Paraná (PUCPR), Brazil
Gilberto Reynoso Meza received his PhD in Automation, Robotics and Industrial Informatics from Universitat Politècnica de València (2014), and the degrees of master of science with a specialization in Automation (2005) and Mechanical Engineering Administrator (2001) from Tecnológico de Monterrey. He is an adjunct professor of the Programa de Pós-Graduação em Engenharia de Produção e Sistemas (PPGEPS), form Pontifícia Universidade Católica do Paraná (PUCPR), Brazil. He is an external professor of the Master in Electronics and Automation from Universidad Politécnica Salesiana (UPS), Ecuador. His current research interests are related to the development of multi-objective optimization techniques for engineering design and machine learning for industrial processes. His main research interests are computational intelligence, intelligent control, multi-objective optimization, multi-criteria decision making, evolutionary algorithms and machine learning.
“Reduction of pollutant emissions associated with failures not detected by the On-Board Diagnostic System”
Most of the faults that affect the level of pollutant emissions of the vehicle are reported to the driver by the on-board diagnostic (OBD) system. However, there are faults that are not recognized by this system that imply that the driver, in some cases, operates the car without observing a possible reduction in engine performance and an increase in harmful exhaust gases. Despite its importance, not enough attention has been paid to this problem in the scientific literature. In this context, this talk exposes the methodology and results of previous research that pursued the reduction of pollutant emissions of a spark-ignition engine that was induced to controlled faults not detected by the OBD system, and for which an optimal operating configuration was defined by design of experiments. The exposition also involved a multi-criteria decision analysis using the analytical hierarchy process (AHP) for the selection of the defects and regulations applied to the experiment.
MSc. Jairo Castillo Calderón – Universidad Nacional de Loja, Ecuador
Professor Jairo Castillo Calderón holds a master’s degree in Automotive Systems from Escuela Politécnica Nacional (2016), Automotive Mechanical Engineer from Universidad Politécnica Salesiana (2013), Master Technician in Automotive Electronics from Cise Electronics, and is currently pursuing a Master’s degree in Electric Propulsion Systems at the University of Azuay. Since May 2016, he has been a professor at Universidad Nacional de Loja (UNL) in the Electromechanical Engineering and Automotive Mechanics Engineering careers. He has directed degree projects at the undergraduate and graduate level. He was responsible for the technological careers of the Faculty of Energy, Industries and Non-Renewable Natural Resources of the UNL during 2017 and 2018. He was a promoter and author of the design of the Automotive Engineering career at UNL where he currently serves as academic manager. He has participated in and directed research projects in the field of automotive engineering, artificial intelligence, mechanical design, and fluid mechanics, in addition to publishing works of high academic and scientific value in the form of scientific articles and book chapters in the same area.