Reinforcement Learning (RL) is a machine learning (ML) technique to learn sequential
decision-making in complex problems. RL is inspired by trial-and-error based human/animal …

In recent years, reinforcement learning (RL) has attracted significant attention from both
industry and academia due to its success in solving some complex problems. This paper …

Prognostics and health management (PHM) is an enabling technology used to maintain the
reliable, efficient, economic and safe operation of engineering equipment, systems and …

Abstract Process Systems Engineering (PSE) is the scientific discipline of integrating scales
and components describing the behavior of a physicochemical system, via mathematical …

This paper provides a novel intelligent scheduling strategy for a real-world transportation
dynamic scheduling case from an engine workshop of general motor company (GMEW) …

The field of machine learning is comprised of techniques, which have proven powerful
approaches to knowledge discovery and construction of 'digital twins' in the highly …

Recently, the availability of extensive catalysis-related data generated by experimental data
and theoretical calculations has promoted the development of machine learning (ML) …

This “white paper” is a concise perspective of the potential of machine learning in the
process systems engineering (PSE) domain, based on a session during FIPSE 5, held in …

Deep reinforcement learning (RL) is an optimization-driven framework for producing control
strategies for general dynamical systems without explicit reliance on process models. Good …

Given the steep rises in renewable energy's proportion in the global energy mix expected
over several decades, a systematic way to plan the long-term deployment is needed. The …