Appropriate maintenance of industrial equipment keeps production systems in good health
and ensures the stability of production processes. In specific production sectors, such as the …

Abstract Machine Learning (ML) algorithms are emerging in various industries as a powerful
complement/alternative to traditional data regression methods. A major reason is that, unlike …

In this article, we develop a generalized and scalable statistical model for accurate
prediction of fouling resistance using commonly measured parameters of industrial heat …

Maintenance is a crucial aspect of the process industry affecting economic and efficiency
losses. Among different approaches, predictive maintenance allows for anticipating failure …

Deposition of undesired materials on the heat transfer surface is one the most challenging
problems for application of heat exchangers. Experimental measurements of degree of …

The production of phosphoric acid by dehydrated process leads to the precipitation of
unwanted insoluble salts promoting thus the crystallization fouling build-up on heat transfer …

Fouling in refinery preheat trains causes major energy inefficiencies, resulting in increased
costs, greenhouse gas emissions, maintenance efforts, and safety hazards. Fouling …

Fouling in crude preheat trains is a major cause of thermal inefficiency in petroleum
refineries. The limited fundamental understanding of its causes and mechanisms led to …

In this study, a conceptual procedure based on the computational fluid dynamic (CFD)
technique has been developed to predict fouling rate in an industrial crude oil pre-heater …

Many of the data sets extracted from real-world industrial environments are time series that
describe dynamic processes with characteristics that change over time. In this paper, we …