Process Systems Research Articles

Analysis of constraints to urban expansion in the city of M’Sila using the Analytic Hierarchy Process (AHP) and Geographic Information Systems (GIS)

The presented study aims to deepen the understanding of urban expansion and land resource management to meet growing urbanization needs and identify constraints associated with this phenomenon. The main objective is to propose a model that integrates the Analytic Hierarchy Process (AHP) and Geographic Information Systems (GIS) – a method recognized for addressing complex spatial issues. By defining the criteria related to the targeted objectives and by mapping attribute and geographic data at the municipal level of M’sila, we have prioritized the identified indicators, quantitatively evaluated the phenomenon, and compared various development scenarios for the studied areas. This quantitative evaluation was carried out through spatial simulation, including data intersection and multicriteria aggregation based on the AHP method, which allowed participatory modeling of factors according to their respective importance. Moreover, this process facilitated the identification of optimal land use for urbanization, while assisting specialists in choosing the most appropriate urban planning orientations and objectives for the studied areas.

A novel dynamic machine learning-based explainable fusion monitoring: application to industrial and chemical processes

Abstract The complexity and fusion dynamism of the modern industrial and chemical sectors have been increasing with the rapid progress of IR 4.0–5.0. The transformative characteristics of Industry 4.0–5.0 have not been fully explored in terms of the fundamental importance of explainability. Traditional monitoring techniques for automatic anomaly detection, identifying the potential variables, and root cause analysis for fault information are not intelligent enough to tackle the intricate problems of real-time practices in the industrial and chemical sectors. This study presents a novel dynamic machine learning based explainable fusion approach to address the issues of process monitoring in industrial and chemical process systems. The methodology aims to detect faults, identify their key causes and feature variables, and analyze the root path of fault propagation with the time and magnitude of one cause variable to another impact. This study proposed using a time domain multivariate granger-entropy-aided dynamic independent component analysis (DICA)—distributed canonical correlation analysis approach, incorporating the dynamics time wrapping supported time delay-signed directed graph. The proposed methodology utilized the application to industrial and chemical processes and verified using the continuous stirred tank reactor and Tennessee Eastman process as practical application benchmarks. The framework’s validations and efficiency are evaluated using established techniques such as classic computed ICA and DICA as standard model scenarios. The outcomes and results showed that the newly developed strategy is preferable to previous approaches regarding explainability and robust detection and identification of the actual root causes with high FDRs and low FARs.

Software-Defined Value Stream Process Systems

The increasing volatility of the markets and the growing demand for customized products are challenges for future production to ensure maximum flexibility and adaptability. This paper introduces software-defined value stream process systems (SVPSs), a novel approach that extends the concept of software-defined manufacturing into autonomous, reconfigurable production systems. SVPSs establish a cyber–physical chain that links product features to requirements, enabling their fulfillment through modular machine and process hardware. A modular construction kit of individually combinable hardware and associated software modules is presented. These modules are coordinated via a digital process chain that enables holistic simulations, optimizations, and planning based on a Digital Twin. This system is based on software-defined manufacturing but extends it into autonomous reconfigurable machines. By enabling virtual planning and commissioning of entire production lines, the SVPS concept provides an efficient and adaptable solution to meet the demands of volatile markets.

Factor Analysis of the Effects of Education Systems During the Covid-19 Pandemic Process on Manisa Celal Bayar University Students

This study aims to examine the opinions and thoughts of students studying at Manisa Celal Bayar University Faculty of Economics and Administrative Sciences in the 2022-2023 academic year regarding distance and face-to-face education systems during and after the Covid-19 pandemic process, by factor analysis.The findings obtained as a result of the factor analysis were examined and interpretations were made. The data used in the study was collected by survey technique. Analyzes were carried out using the SPSS-22 statistical package program and results were obtained using explanatory factor analysis, one of the multivariate statistical techniques.The number of students who will participate in the survey was determined by taking into account their departments using the stratified sampling technique, provided that they took courses with the distance education model during the Covid-19 pandemic and continued their education with the face-to-face education model after the pandemic. In this way, 342 of the 4518 students studying at the faculty were determined as the sample and the study was conducted with 342 students who fully responded to the survey. The findings obtained as a result of the explanatory factor analysis applied Accordingly, it has been observed that the effects of the Covid-19 pandemic process and subsequent education systems on students are explained by two factors. The first of these two factors is named "Positive Effects of Face-to-Face Education" and the second is called "Negative Effects of Face-to-Face Education". These named factors explain 69% of the total variance.

Intelligent Control Systems for Mechanical Engineering Technology Tasks

The article is devoted to solving the main tasks set in the work with the aim of analyzing and substantiating the implementation of intelligent control systems in technological processes of mechanical engineering, with an emphasis on increasing efficiency, accuracy, and reliability of production. The use of multi-agent systems and decentralized control systems, which significantly enhance the flexibility and adaptability of production, is analyzed. Special attention is paid to the role of physics-informed neural networks in fault diagnosis, which ensures increased reliability and reduced maintenance costs for equipment. The effectiveness of applying machine learning algorithms to optimize production processes, particularly in material processing and equipment maintenance, is evaluated. The impact of integrating intelligent control systems on production performance and quality, especially in the processes of milling and bonding large parts, is considered. Practical recommendations have been developed for the implementation of an adaptive intelligent production management system (AIPMS), which combines multi-agent systems, neural networks, digital twins, and innovative materials. The implementation of the artificial intelligence concept in production processes will contribute to the further development of mechanical engineering from a technological perspective, enabling enterprises to adopt innovations more rapidly, increase automation, and enhance the adaptability of technological processes, which in turn will lead to significant improvements in product quality and competitiveness. The use of such systems allows optimizing technological processes, reducing the number of defects, lowering energy consumption, and improving environmental efficiency

Challenges in Transitioning from Industry 4.0 to Industry 5.0: A Multicriteria Analysis

In this study, we evaluate the transition from Industry 4.0 (I4.0) to Industry 5.0 (I5.0) using a multicriteria approach that integrates the Analytic Hierarchy Process (AHP) and Fuzzy Inference Systems (FISs). Key criteria identified through a comprehensive literature review include sustainability, human factors, resilience and organizational management, which are critical for the successful implementation of I5.0. AHP is utilized to rank these criteria and assign relative weights, reflecting their importance in the overall evaluation. FIS is employed to manage the inherent uncertainty and imprecision in decision-making within the context of I5.0. The results provide a holistic view of how companies navigate this transition, highlighting their strengths and weaknesses. This study offers valuable insights into the challenges and opportunities associated with adopting I5.0, emphasizing the utility of combining multicriteria approaches for strategic decision-making in dynamic industrial environments. These findings aim to support organizations in making informed decisions, fostering a more innovative, sustainable and human-centric industry. The combination of these methodologies provides a robust foundation for future research and practical applications in advancing I5.0.

Mesterséges intelligencia alapú döntéstámogató és döntéshozó rendszerek kockázatai a vállalatok vezetői szintű döntéshozatalában

The study examines the risks associated with artificial intelligence (AI) based decision-making and decision-support systems in the decision-making processes of company executives, as well as small and medium-sized enterprises. Due to global trends and digital advancements, company management increasingly faces complex decisions, which AI-based decision-making and decision-support systems may well be suited to support. However, this carries several risks, and the study aims to identify the legal, ethical, and business risks associated with the use of such AI systems, with a particular focus on the decisions made by company executives. The analysis is based on a literature review, which will ultimately be compared with survey responses found in the AI Index Reports published annually by Stanford University.

Digital supply chain: An industrial perspective

AbstractThis perspectives article outlines and discusses the future of supply chains. The existing challenges and flaws in supply chains design and management are described, motivating the need for the next‐generation supply chains. We present a holistic paradigm for viewing and analyzing supply chains as networks of networks with various dimensions, hierarchies, and players with their various forms of decision‐making. Cyber‐Physical Systems is offered as a key enabler to obtain a digital supply chain exhibiting the features of heterogeneity, interoperability, modularity, customizability, decentralization, autonomy, and cooperativity. The role of virtual assistants is described, along with research directions to create the technology for establishing true digital supply chains. The role of Process Systems Engineering (PSE) is outlined with the hope that the ideas discussed will motivate the PSE community to become active participants in attaining the next‐generation supply chains.

Biochemical Properties of the Acid Ectophosphatase Activity of Phytomonas serpens Involved in Cell Proliferation

Phytomonas is the only kinetoplastid that can parasitize plants, causing economically relevant issues. Phytomonas serpens share similarities with pathogenic trypanosomatids, including surface enzymes that are involved in adhesion to the salivary gland of their experimental host, the insect Oncopeltus fasciatus. Ectophosphatases are cell surface enzymes involved in host–parasite interactions that are widely distributed among microorganisms. This work aimed to perform the biochemical characterization of P. serpens ectophosphatase activity, investigating and discussing its possible physiological role. This activity presented an acidic profile, and its kinetic parameters Km and Vmax were calculated as 1.57 ± 0.08 mM p-NPP and 10.11 ± 0.14 nmol p-NP/(h × 108 flagellates), respectively. It was stimulated by cobalt, inhibited by zinc, and insensitive to EDTA, a divalent metal chelator. The inhibitor sodium orthovanadate was able to decrease P. serpens ectophosphatase activity and growth, suggesting its involvement in cell proliferation. Given that P. serpens can uptake inorganic phosphate (Pi) from the extracellular medium, it is likely that its ectophosphatase activity acts together with the transport systems in the Pi acquisition process. The elucidation of the molecular mechanisms involved in this process emerges as a relevant perspective, providing new strategies for controlling Phytomonas infection.

Hazard Identification of Ammonia FSS for Ammonia Fuelled Ammonia Carrier

Ammonia is a zero-carbon fuel that has attracted considerable interest. The compound has high volumetric energy density and is easy to store and transport. Despite this, a proper study is necessary to ensure safety because ammonia fuel will likely be applied first to ammonia carriers. In this study, hazard identification (HAZID) was performed to identify the risk of the ammonia fuel supply system and preventive/mitigation measures were suggested to minimize the risk. The analyzed system scope was the ammonia fuel supply system from a fuel service tank on the deck to the front of the engine. The nodes with the most scenarios were the fuel service tank and the fuel supply line. The main factors included internal factors, such as design defects, malfunctions, and operational errors, and external factors, such as impact, thermal stress, hogging, and sagging. Recommendations are provided to reduce the risk of accident scenarios, including safety devices/alarm devices in process systems, system layout configurations, and heat and gas dispersion analysis. The results are expected to help predict/minimize damage regarding ammonia fuel supply system design, operational safety, and potential risks.

Comparative Study of Intelligent and Classical MPPT Techniques Applied to Solar Battery Charger

Renewable solar energy is an excellent alternative to conventional energy sources and, recently, it has shown remarkable growth on electrical power grid in various countries around the world. Maximum power point tracking (MPPT) has critical importance in solar energy generation since it increases the system's efficiency in many scenarios. Photovoltaic modules (PV) are influenced by environmental factors such as temperature and solar irradiation density, changing the amount of energy generated throughout the day. In order to extract the maximum available power from a PV, it’s necessary to use the MPPT technique, which considers the system’s nonlinearities. Maximum power tracking (MPP) is done by tuning the duty cycle of the DC-DC converter, so that the PV's terminal voltage is modulated to match the environmental conditions. This tuning, generally, is dependent on sensor readings. Normally, only the module’s voltage and current sensors are used, due to the low cost and ease of acquisition of these signals. However, intelligent techniques demand the usage of temperature and irradiation sensors, increasing the complexity of the system’s implementation. The use of intelligent control techniques applied to the energy generation system has had a notable presence in recent publications. The high efficiency obtained from its application demonstrates that the use of intelligent systems in the decision-making process is a useful tool in obtaining maximum generation power. The objective of the present study is the development and simulation via MATLAB/SIMULINK of a battery charging system with solar energy, which consists of a PV, a Buck converter, a 12V battery, and the MPPT controller. The intelligent fuzzy logic MPPT technique (FLS) and the classical incremental conductance technique (INC) will be compared, both techniques using only voltage and current measurements.

Editorial: Process and energy systems engineering: advances in modeling, and technology

Editorial: Process and energy systems engineering: advances in modeling, and technology

Features of damage to the central nervous system and mental sphere in patients with comorbid post-COVID syndrome

The prevalence of post-COVID syndrome in patients treated on an outpatient basis ranges from 10 to 35 %; it can reach 80 % in patients with severe coronavirus infection. It is currently hypothesized that long-COVID may be due to both the direct effects of the SARS-CoV-2 virus and the biopsychosocial effects of COVID-19.The aim. To study the characteristics of damage to the central nervous system and mental sphere in patients with comorbid post-COVID syndrome.Materials and methods. To study the clinical features of the course of post-COVID syndrome, 98 patients who had suffered COVID-19 were examined. Of these, 18 (18.4 %) were men, 80 (81.6 %) were women. The mean age in the group was 56.05 ± 1.27 years. The examination program included a questionnaire, clinical examination, pulse oximetry, and assessment of exercise tolerance using the Borg scale. Statistical processing was carried out using the Statistica software package, version 6 (StatSoft Inc., USA). The results of the study are presented as a median, upper and lower quartiles. After analyzing the compliance of the studied indicators with the law of normal distribution (Shapiro – Wilk test), the groups were compared using the Wilcoxon test for pairwise comparison of related samples. Differences were considered statistically significant at p < 0.05.Results. Our studies of comorbidity and complications after COVID-19 infection revealed the most frequent involvement of three systems in the pathological process: cardiovascular, nervous and endocrine. Metabolic syndrome was detected in 67 % and involvement of the cardiovascular system was detected in 48.8 % of those examined.One of the main manifestations of post-COVID syndrome is damage to the central nervous system and mental sphere in the form of mild cognitive and emotional-volitional disorders with asthenodepressive and anxiety-depressive disorders.Conclusion. The health status of patients after COVID-19 is significantly lower than that of the general population. The study results indicate an urgent need to study the pathogenesis of long COVID and develop effective interventions to reduce the risk of its development.

A systematic process-oriented approach to the implementation of the enterprise's information security management system

In the context of ensuring information security (cybersecurity) of enterprises and critical infrastructure institutions, which include state enterprises (institutions) providing services for metrological support, conformity assessment, and standardization, the development of systemology and the implementation of an information security management system (ISMS) based on the principles of system process-oriented approach is a highly relevant task. The article concludes with the need for further substantiated research in this direction based on a critical analysis of well-known scientific studies (publications) of domestic and foreign scientists. First of all, this concerns the solution to the problem of identifying a set of information security objects in enterprises' managerial and technological processes systems. Since this system belongs to the «complex system» category, it becomes relevant to study the systemology of the enterprise ISMS as a systematic combination of its information and organizational resources. In this regard, the basis of the conducted research is the conceptual system statement that ISMS is an integral part of the enterprise's general management system. In the context of this statement, the author's vision for implementing the requirements of the current DSTU standard ISO/IEC 27001:2023 regarding the construction of ISMS based on the principles of system and process approach is outlined. For this, a number of system definitions and corresponding models are proposed, making it possible to implement the specified requirements of the standard within the framework of the proposed pyramid model of process-oriented enterprise management. Within the framework of the specified model, the author's interpretation of the definition of the concept «Enterprise Information field» is formulated, on the basis of which a structural task-solving staging model of ensuring enterprise information security is proposed.

“Other(ed)” Ocean Knowledges: Unlearning Integration in Ocean Governance for Recognitional Justice

There is an increasing call for the need to “integrate” Indigenous and local knowledge systems in ocean governance processes, on national and global scales. However, the knowledge systems, epistemes, and practices of different Indigenous and local coastal communities, whose stewardship of the planet sustains and protects marine ecosystems, pre‐date the institutionalised ocean sciences and governance with which they are meant to be integrated. The concept of integration often perpetuates othering and devaluation of various ocean knowledges that should not be subject to these problematic practices. Much of the current knowledge informing ocean governance is underpinned by colonial, military, and financial projects, in direct juxtaposition to epistemes and practices that are deeply interconnected with marine life. Writing from a marine social sciences perspective, we explore the inherent problems and limitations of integration approaches and propose reversing how we frame “knowledge” and its othering by suggesting that our scientific and governance practices are, in fact, “other” to longstanding ways of coexisting with the ocean. Without attempting to represent Indigenous knowledge systems or categorise these as unaware of scientific developments, we argue that researchers and scientists need to actively unlearn what is taught in prominent ocean sciences. By focusing on global governance through the International Seabed Authority and national ocean governance in South Africa, respectively, we explore knowledge othering and the process of unlearning what ocean governance teaches as knowledge integration to better critically consider how the ocean is, has been, and should be valued.

Model-Based Assessment of Energy Efficiency in Industrial Pump Systems: A Case Study Approach

Outdated, oversized variable speed pump drives (VSDPs) in industry lead to sub-optimal energy efficiency and considerable energy losses. This paper proposes methods to develop 2D efficiency maps for motors, converters, and pumps using polynomial surface fitting, which enables efficiency evaluation in a wide operating range. The method was applied to an oversized VSDP in an industrial chilled water supply system, comparing the original system with five alternative VSDP combinations with high-efficiency motors and pumps. The five VSDP variants demonstrated average energy savings of around 30%, with the synchronous reluctance motor (SRM) configurations outperforming the induction motor (IM) configurations by up to 7 percentage points, particularly at low loads. The high-efficiency SRM-based 252-IE5 variant delivered the best overall energy performance, highlighting the benefits of optimised system sizing and motor selection for energy savings. The proposed method can be used in both industrial and residential applications and offers great advantages in process systems that require variable flow and pressure of water or other fluids during operation, such as HVAC, water supply and wastewater treatment, district heating, etc. The development of a VSDP drive with efficient energy optimisation is an interdisciplinary problem of mechanical and electrical engineering, and without the interaction of engineers from both fields the result will not be optimal. We try to present our method so that it can be a reliable tool for mechanical, electrical, and other engineers or researchers to assist them in finding possible energy savings, performing energy audits, and selecting the most suitable components when modernising existing or developing new systems.

A thermo-economic comparison on new and conventional alternatives of pressurization of CO2 in CCS systems

The final stage of carbon capture and storage processes involves the pressurization of CO2 by a suitable method which is conventionally carried out through a series of compressors with intercoolers in between them. In the present study, the idea of liquefying the captured CO2 is considered. Four different systems for the liquefaction process are evaluated and compared Thermo-economically with the benchmark system of direct carbon dioxide compression. The results indicate that the EPLS system outperforms the others, with a product cost 5.89% lower than the benchmark system. Evaluations show that most of the costs are imposed by the initial compression stage in each system. A detailed investigation of the sensitivity analysis shows that the benchmark and claude systems have the largest dependency on pressure ratio and intercooling temperature, respectively. Additionally, evaluation of the economic parameters indicates that the changes in unit cost of power have the most effect on the benchmark system while the interest rate affects the results of claude and DEBARS more than other options. Detailed evaluations reveal that the EPLS layout has the advantage of less dependency on the changes of operating parameters and on the other hand, the cost of input heat, the maintenance factor, and the generator and evaporator temperatures make a high difference in the final product cost of the DEBARS. Finally, the effect of pressure drops in heat exchangers is investigated and results reveal that the consideration of pressure drops leads to power penalties ranging from 0.97 to 8.52 $/hr in different systems.

Spherical magnetic MgO-CeO2-Fe3O4@JB heterojunction for enhanced photodegradation of pesticide and complex anionic dyes: Understanding the degradation process and diverse water systems

Clothianidin (CLO) is a widely utilized pesticide recognized as an emerging pollutant capable of contaminating surface and subsurface water sources. Utilizing nanoparticles for photodegradation is a very ecological and cost-effective method for water treatment. This study involves the creation of a MgO-CeO2-Fe3O4@JB (Jute-Biochar) heterojunction with a mesoporous structure using hydrothermal process. The purpose of this design is to explore its potential for photocatalytic applications. PXRD (Powder X-ray Diffraction), FTIR (Fourier Transform Infrared), UV–DRS (Ultraviolet–Visible Diffuse Reflectance Spectroscopy), PL (Photoluminescence), TEM (Transmission Electron Microscopy), EDX (Energy Dispersive X-ray), XPS (X-ray Photoelectron Spectroscopy), VSM (Vibrating Sample Magnetometry), BET (Brunauer Emmett Teller), and SEM (Scanning Electron Microscopy) analysis confirmed the formation of a mesoporous MgO-CeO2-Fe3O4@JB heterojunction with preferred interface between MgO, CeO2, and Fe3O4 phases, extending the light-absorption insights to 700 nm. The photocatalytic performance of MgO-CeO2-Fe3O4@JB heterojunction was evaluated under visible-light using CLO as the target molecule. The degradation performances of CLO on MgO-CeO2-Fe3O4@JB were determined to be 95.24 ± 1.18 % after 35 min of exposure to light. The calculated rate constants for the degradation of CLO in presence of light using the MgO-CeO2-Fe3O4@JB composite were determined to be 0.0924 min−1. Furthermore, two complex dyes, Niagara Blue (NB) and Reactive Red (RR), photodegrade to 99.45 ± 1.24 % and 97.23 ± 1.41 % within 25 and 30 min, respectively. The excellent photocatalytic characteristics of the MgO-CeO2-Fe3O4@JB heterojunction was suggested to be primarily caused by the larger photo-response, aligned band-structure, and useful use of the photo-induced charge carriers of the photocatalyst. In addition, the recycling experiments have verified the exceptional photostability of the MgO-CeO2-Fe3O4@JB photocatalyst due to incorporation of nanoparticles into the biochar matrix. This leads to a synergistic mechanism for effectively eliminating these pollutants.

Penerapan Model Incremental Delivery pada Pengembangan Aplikasi Sistem Informasi Hotel Cipta Jakarta

Along with the development of the times, we see many hotels experiencing changes. A change that is rarely reviewed as a news topic is the software overhaul that occurs in hotels from offline to online systems. Lay people only see changes in hotels from a visible perspective, without having to know whether the hotel's system and system applications have changed. One of the factors in system development at Hotel Cipta is the need for hotel management to prioritize the development of system applications from offline to online systems, even web-based. It is not easy to overhaul an existing system application compared to creating a new system application. There are several software engineering methods and models that are commonly used to analyze system needs and design systems in the software development process. One of them is the incremental delivery model. This makes it interesting to try to apply the incremental delivery model to the development of the Hotel Cipta information system application by taking place at the Hotel Cipta on KH. Wachid Hasyim Street, Central Jakarta. In this study, the object of research is the Front Office department.

Faculty experiences in publishing in Scopus-indexed journals: Challenges and strategies among higher education institutions in the Philippines

Research is a cornerstone of education, with publication output often used as a key metric for research performance. This study investigates the experiences of Philippine Higher Education Institution (HEI) faculty as they work to publish in Scopus-indexed journals. By exploring faculty members' challenges, strategies, and perspectives, this research aims to inform how HEIs can enhance support for faculty in contributing to global scholarship and advancing academic careers. Using Husserl’s descriptive phenomenology, 12 faculty members from HEIs in Eastern Visayas, Philippines, were purposively selected as participants, with theoretical saturation guiding the sample size. Data was gathered through in-depth interviews and analyzed using Colaizzi's method. The study reveals four primary themes regarding the publication journey: motivation for publishing, preparation and publication process, challenges faced, and support systems. Faculty perceptions of publishing centered around five themes: career advancement and promotion, increased visibility and credibility, personal and professional satisfaction, institutional expectations, and incentives. Key challenges included financial barriers, the rigorous peer review and revision process, submission and formatting requirements, and emotional strain. To address these, participants highlighted strategies involving financial and personal investment, mentorship and collegial support, institutional resources, continuous learning, strategic journal selection, and maintaining resilience. Findings indicate that publishing in Scopus-indexed journals requires a blend of motivation, planning, and resilience, as faculty strive to contribute to knowledge and further their careers. Yet, they face substantial barriers, especially high publication fees and stringent formatting standards. Institutional support—especially through funding, mentorship, and workshops—is vital to overcoming these obstacles. For greater faculty success, institutions should cultivate a supportive research culture that recognizes and addresses the logistical and emotional demands of academic publishing.