Overview

With a progressively more demanding global market, the digitalization of industrial processes is becoming increasingly essential for companies to maintain a competitive advantage. These new challenges have had a profound impact on the industrial paradigm, with a growing need for the acquisition, monitoring and processing of data from multiple stages of the manufacturing cycle in a computationally sustainable and efficient way. However, it is not uncommon for there to be gaps in the management and interpretation of these large volumes of data due to mathematical training gaps, leading to a waste of resources. This advanced course aims to introduce basic mathematical concepts and good practices for the successful integration of data analysis techniques and other intelligent algorithms into industrial processes. The ultimate goal of the course will be to provide participants with a global vision of the digital transformation of the industry from the perspective of the most relevant algorithms and their fundamental role in technologies such as Machine Learning, Internet-of-Things (IoT) and Digital Twins. The training program will is adapted to practical and real case studies arising from the NEXUS Agenda.

Learning outcomes

• Identify common challenges in industrial data processing.
• Identify and apply the best mathematical strategies for analyzing and extracting information in a given industrial context.
• Identify industrial problems where the application of intelligent algorithms can be beneficial.
• Apply intelligent algorithms to industrial problems and critically evaluate the results obtained.
• Understand the basic principles of factory floor digitalization and evaluate the most appropriate methods for each industrial scenario.