Industry 4.0: The Power of Data

1. PROTOCOL - Assessing the transversal competence of teamwork in bachelor's and master's degree by means the competency-based interview.- 2. A managerial approach to Industry 4.0 training.- 3. NetLogo teaching tool to illustrate the cooling process in simulated annealing using the Metropolis model.- 4. Fostering Youth Entrepreneurship in STEM Students for Industry 4.0 Era.- 5. Distributed ledger technology in Industry 4.0: an implementation.- 6. A bibliometric analysis of the Time Driven Activity Based Costing system. The power of cost accounting in organisations.- 7. Using data mining to analyse occupational accidents in the construction and manufacturing sector.- 8. Concept for Deployment Design of Machine Learning Models in Production.- 9. A MILP model for the lot-sizing/scheduling of automotive plastic components with raw materials and packaging availability.- 10. Design of a simulation environment for training or testing algorithms to solve the workshop sequencing problem.

Luis R. Izquierdo is a Professor in Industrial Organization, with a background in Computer Modelling, Economics and Mathematics. His main area of expertise is Evolutionary Game Theory and the analysis of Complex Systems. Most of his research lies at the interface between Economics and Computer Science and it has led to the publication of more than 30 papers in journals such as Theoretical Economics, Journal of Economic Theory, Games and Economic Behavior, JASSS, and Journal of Evolutionary Economics. He is also an associate editor of the JCR journal JASSS. Finally, Luis is the author of more than 30 open-source computational programs, which are freely available online, together with comprehensive user guides. These programs are used by many scholars all around the world both for research and for teaching purposes.

José I. Santos Martín is an Associate Professor in Industrial Organization, with a background in Computer Modelling, Information Systems, and Economics. His main area of expertise is the modeling of Complex Systems. Most of his research focuses on the application of methods and techniques for the study of complex systems, mainly agent-based modeling, complex network theory, and also, machine learning techniques that facilitate the analysis of simulation models that generate large data sets. He has collaborated in more than 20 papers in journals such as PloS One, Scientific Reports, Royal Society Open Science, and Journal of Artificial Societies and Social Simulation.

Juan J. Lavios is an Associate Professor in Industrial Organisation at the Higher Polytechnic School of Universidad de Burgos. His main research interests include distributed systems, coordination mechanisms, scheduling and multi-agent systems. He has taken part in several research projects regarding social and organizational modelling and production management: Multi-agent systems for the control of distributed job shop manufacturing systems