Speaker: Dr Ann Smith
Title: Predictive Maintenance in the Digital Era
Abstract:
In this seminar, "Predictive Maintenance in the Digital Era," I'll explore the essentials of modern predictive maintenance. We'll cover condition monitoring, data acquisition and management, parameter selection strategies, and model potential. We'll start by dissecting condition monitoring, focusing on managing sensor data from large-scale engineering systems. I'll discuss effective parameter selection methods, including both manual inspection and genetic algorithms. While real-time monitoring is valuable, it's a retrospective methodology and at best give instantaneous information on process conditions so typically stops at detection and diagnosis, lacking in prognosis. However, I'll highlight the potential for future advancements in this area. We'll also briefly touch on Functional Principal Component Analysis (FPCA) and its possible role in modeling, as well as the potential of the Sparse Identification of Nonlinear Dynamics (SINDy) algorithm for creating digital twins. If system dynamics can be reliably recovered from data along with insights into the complexities of predictive maintenance this will pave the way for a more reliable future.