Conference : Future of Latent Variable Methods in the Process Industry 4.0 [Alberto Ferrer]


Date : October, 20 – 10h00
Room : PLT-3370
Title: Future of Latent Variable Methods in the Process Industry 4.0

Prof. Alberto Ferrer
Multivariate Statistical Engineering Group (GIEM)
Department of Applied Statistics, Operation Research & Quality
Universitat Politècnica de València
Valencia (SPAIN)

Abstract :
A lot of potential information coming from data streams needs to be analysed to give organizations new insights about their products, customers and services. This can be particularly valuable when it is critical to maintain quality and uptime, such as in process monitoring applications, by quickly detecting and diagnosing abnormal activities, or when rapid new products development is critical for company survival.For many industrial companies, the result of Industrial Internet of Things (IIoT) connecting intelligent physical entities (e.g. computers, sensors, devices) to each other, Internet services and applications are leading to the so-called Big Data problem in Industry 4.0. Big data exhibit high volume and correlation, rank deficiency, low signal-to-noise ratio, complex and changing structure, and missing values. Classic statistical techniques are not feasible for analyzing Big Data streams. In this talk we illustrate the potential of latent variable-based multivariate statistical methods to analyze Big Data streams and visualize extracted information in a way that is easily interpreted and that is useful for process understanding, real time process monitoring, fault detection & identification, process improvement and optimization.