A functional data-driven approach to monitor and analyze equipment degradation in multiproduct batch processes

Abstract

Equipment degradation is ubiquitous in the Chemical Process Industry (CPI), causing significant losses in efficiency, controllability, and plant economy, as well as an increased environmental fingerprint and additional operational safety risks. The case of fouling in heat exchangers, in particular, is well-known and pervasive but still hard to cope with, given the complexity of the underlying mechanisms and the difficulty of assessing its extension in real-time. This problem becomes even more complex in batch processes producing different products, where multiple recipes are used, bringing additional variability and new challenges to the analysis. In this work, we propose a functional data-driven approach for streamlining the analysis and monitoring of the progression of fouling taking place in heat exchangers in multiproduct batch processes. With the approach developed and presented in this paper, process analysis can be efficiently conducted by integrating historical data with engineering knowledge. Furthermore, a surrogate measure of fouling extension in heat exchangers is proposed, that can be readily implemented as an equipment health indicator (EHI) leading to a safer operation of the heat exchanger.