Special Issue on “Process Systems Engineering—Incubating Sustainability for Industrial Revolution 4.0”

Process systems engineering (PSE) plays a crucial role in enhancing the efficiency and sustainability of industrial systems by employing advanced methodologies to optimize processes. PSE allows for the meticulous design, modeling, and control of complex industrial systems, ensuring that every component operates at peak efficiency. With the advent of artificial intelligence (AI), these capabilities have been significantly augmented. AI-driven modeling and analysis tools enable more accurate predictions, better decision-making, and seamless integration of various subsystems, leading to improved overall performance [1]. By leveraging AI, PSE can now tackle increasingly complex challenges, making it possible to manage and optimize large-scale industrial operations with unprecedented precision and efficiency.

In an era defined by rapid technological advancement and global sustainability imperatives, the role of engineering and scientific innovation has become increasingly central to shaping a resilient, intelligent, and environmentally responsible future. The industrial landscape of the 21st century demands not only efficiency and productivity but also sustainability, adaptability, and ethical responsibility. Hence, the research contributions presented in this Special Issue embody the evolving intersection of advanced technologies, sustainable practices, and safety-driven design philosophies. Together, these works reflect the essence of transformative research—bridging theory and application, human and machine, science and society [2]. Simultaneously, the global push towards carbon reduction has intensified the focus on environmental considerations within industrial operations. As industries are being held to stricter environmental standards, there is a growing need to evaluate and optimize processes not just for economic gain but also for their environmental impact. This holistic approach requires the analysis of industrial systems through multiple approaches, including energy consumption, waste generation, and emissions. PSE provides the tools to perform such multi-faceted analyses, enabling industries to balance economic performance with environmental responsibility. By integrating these methodologies, PSE not only helps industries to meet their carbon reduction targets but also ensures that these efforts are economically viable and technologically feasible. This systemic approach is essential for driving the transition towards more sustainable industrial practices while maintaining competitiveness in a rapidly evolving market [3].

This Special Issue brings together a carefully selection from the collection of studies presented at the PSE ASIA 2024—11th Asian Symposium on Process Systems Engineering at Penang, Malaysia, representing the diverse and interconnected fields that define modern engineering and industrial evolution. The featured articles traverse three overarching groups: (i) sustainability and environmental engineering, (ii) digitalization and Industry 4.0 transformation, and (iii) artificial intelligence, safety, and risk management. Each theme contributes to a shared goal—to redefine the future of industrial systems through innovation that is both intelligent and sustainable.

The first set of papers highlights the importance of environmental sustainability and resource optimization as foundational pillars of future-ready industries. The article “Analyzing the Impact of Orifice Size and Retention Time in Private Tanks on Water Quality Indicators” provides critical insights into chlorine decay in water distribution networks which is significantly affected by the presence of storage tanks, particularly due to the orifice size and retention time, which influence both hydraulic flow behavior and water residence time. This study introduces a novel simulation framework that integrates pressure-driven analysis with a first-order kinetic model for chlorine decay, implemented using the WQnetXL tool and validated through simulations in EPANET. Complementing this, “Esterification of Kenaf Core Fiber as a Potential Adsorbent for Oil Removal from Palm Oil Mill Effluent (POME)” explores the potential of esterified kenaf core (EKC) fiber as an oil adsorbent for oil removal from POME, optimized using a full central composite design (CCD) within the response surface methodology (RSM) framework. The optimum conditions achieved 76% oil removal efficiency, with a 1:0.5 ratio of mercerized kenaf core to stearic acid (MKC:SA), 15 wt% of catalyst, and 1 h reflux time during the esterification process. On the other hand, the paper “Scaling Up a Heater System for Devulcanization of Off-Spec 2 Latex Waste: A Two-Phase Feasibility Study” explores the feasibility of devulcanizing off-spec latex waste using a two-phase approach comprising laboratory and pilot-scale trials. Findings from the laboratory phase guided the design and operation of a pilot-scale process using a retrofitted waste rubber machine. Results showed comparable devulcanization efficiency at both scales, with gel contents of 52.5% (lab) and 55.2% (pilot). GPC analysis indicated increased molecular weight and reduced polydispersity index (2.266 to 1.7601), signifying more uniform molecular weight distribution and effective crosslink scission. The successful scale-up demonstrates the potential for industrial application of latex waste devulcanization. Meanwhile, “Emerging Advances in Sustainable Manufacturing” is a systematic review of the latest trends in sustainable manufacturing over the past five years, exploring future developments in technologies, methods, and strategies. Utilizing the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology, adapted to engineering, this review ensures transparency and reproducibility throughout the identification, screening, eligibility, and inclusion stages of the review process. Collectively, these papers reinforce the importance of sustainability—not as an auxiliary consideration, but as the vital framework through which future industrial and environmental systems to evolve.

The second cluster of papers focuses on digital transformation and intelligent automation, capturing the essence of Industry 4.0. The paper “Implementation of a Sustainable Framework for Process Optimization Through the Integration of Robotic Process Automation and Big Data in the Evolution of Industry 4.0” demonstrates the integration of Robotic Process Automation (RPA) and Big Data within a sustainable framework for process optimization in the context of Industry 4.0. As industries strive to enhance operational efficiency while maintaining sustainability, the need for innovative solutions has become crucial. The research applies the PICO methodology (Population, Intervention, Comparison, Outcome) to assess the impact of combining these technologies on process optimization and sustainability. “Trends in Sustainable Inventory Management Practices in Industry 4.0” further extends this narrative to examine 52 recently published papers on sustainable inventory management in Industry 4.0, intending to bridge theory and practice through a comprehensive literature review. By analyzing the latest advancements discussed over the past two years, covering 2024 and 2025, key trends shaping the field are identified, highlighting existing gaps that may require further exploration. Focusing on this time frame is particularly relevant because it reflects how companies have recently started using artificial intelligence more practically to support sustainability goals. Adding a human-centered perspective, “Prototype of a Multimodal Platform Including EEG and HRV Measurements Intended for Neuroergonomics Applications” offers an innovative approach to understanding human–machine interaction through physiological measurements. This work introduces prototype testing to demonstrate the system’s ability to detect stress and drowsiness. Along with other indicators such as body temperature, heart rate (HR), and SpO₂ levels, the system incorporates electroencephalography (EEG) and heart rate variability (HRV). Together, these contributions present a compelling vision of how digitalization and human intelligence can be harmonized—forming the foundation of smart, adaptive, and sustainable industrial ecosystems.

The third research group brings into focus artificial intelligence, cybersecurity, and safety management—domains that are increasingly critical as industries become more interconnected and data-driven. The study “A Type-2 Fuzzy Logic Expert System for AI Selection in Solar Photovoltaic Applications” integrates fuzzy logic and AI to support energy decision-making, illustrating how intelligent systems can guide sustainable energy adoption. The review provides details on the advantages, limitations, and optimal use cases of various review techniques, such as Artificial Neural Networks, Fuzzy Logic, Convolutional Neural Networks, Long-Short Term Memory, Support Vector Machines, Decision Trees, Random Forest, k-Nearest Neighbors, and Particle Swarm Optimization. “MAL-XSEL: Enhancing Industrial Web Malware Detection with an Explainable Stacking Ensemble Model” addresses the growing challenge of cybersecurity in industrial networks, emphasizing the importance of transparency and explainability in AI-driven detection systems. MAL-XSEL explicates the model predictions through Shapley additive explanations (SHAP) and local interpretable model-agnostic explanations (LIME), which enable security analysts to validate how the detection logic works and prioritize the features contributing to the most critical threats. Evaluated on two benchmark datasets, MAL-XSEL outperformed conventional machine learning models, achieving top accuracies of 99.62% (ClaMP dataset) and 99.16% (MalwareDataSet). The paper “Artificial Intelligence in Manufacturing Industry Worker Safety: A New Paradigm for Hazard Prevention and Mitigation” pioneers the application of AI for proactive safety management, highlighting the potential of machine learning in protecting human lives in industrial environments. Meanwhile, “A Comparative Review of IG-541 System Use in Total Flooding Application for Energized Electrical Fire” and “A Two-Level Facility Layout Design Method with the Consideration of High-Risk Facilities in Chemical Industries” underscore the critical role of design optimization and fire safety strategies in managing industrial risks. Another notable paper focuses on “Multi-objective Large-scale ALB Considering Position and 2 Equipment Conflicts Using an Improved NSGA-II”. An improved NSGA-II algorithm is developed by incorporating artificial immune algorithm concepts and neighborhood search. A dominance rate and concentration-based selection strategy, along with refined crossover and mutation operators, enhances search efficiency. Case studies show that the improved algorithm achieves the same optimal number of workstations as the traditional NSGA-II but improves workload balance by 5%, reduces costs by 2%, and yields 76% higher hyper-volume and 133% more Pareto front solutions. Collectively, these studies represent the emerging paradigm of intelligent safety systems—where automation not only enhances productivity but also safeguards people, assets, and the environment.

Taken together, these papers illustrate a shared vision: the integration of sustainability, intelligence, and safety as the new triad of engineering excellence. They collectively reflect how research communities are responding to the challenges of climate change, industrial safety, and digital transformation—not in isolation, but through interconnected innovation. The convergence of environmental science, artificial intelligence, and human-centered design marks a profound shift toward the holistic evolution of industrial systems.

In conclusion, this Special Issue stands as the spirit of innovation and collaboration that defines today’s engineering research. The diversity of topics—spanning water quality, renewable energy, process automation, human–machine interfaces, and safety systems—reflects the multidisciplinary fabric of sustainable industrial development. On behalf of the editorial team, we extend sincere appreciation to all authors, reviewers, and conference organizers for their invaluable contributions. It is our hope that this collection of works will inspire further interdisciplinary research, foster meaningful collaborations, and ignite new ideas toward building an intelligent, safe, and sustainable future for all.