Industrial Processes Research Articles

Diagrammatic devices in early to mid-twentieth-century American art pedagogy

ABSTRACT Diagrams demonstrating principles of formal arrangement (what is commonly called composition or design) were pervasive in the production and interpretation of pictorial art in the United States throughout the first half of the twentieth century. This essay surveys three of the most influential: a Japan-inspired design manual written by art educator Arthur Dow and first published in 1899; a WWI-era proportional scheme devised by illustrator and amateur classical archeologist Jay Hambidge, and a series of essays from 1926 on the ‘mechanics of form organization’ by painter (and, at the time, Art Students League of New York instructor), Thomas Hart Benton. These and similar devices were an integral part of the relentless standardization and self-conscious modernization of artists’ methods modeled on industrial processes of mass production and pursued between the Civil War and the Great Depression by educators and policy-makers interested in establishing the teaching of art in the United States on a more practical basis than that provided by the European academic tradition. Despite their once near-ubiquity and pivotal role in the development of several generations of American modernists, including Georgia O’Keeffe, George Bellows and Jackson Pollock, as described here, these hugely popular devices are almost entirely forgotten today.

Exploring auxotrophy and engineering vitamin B 6 prototrophy in the acetogen Clostridium sp. AWRP

ABSTRACT Gas fermentation using acetogenic bacteria requires a chemically defined minimal medium to be established. This approach not only helps in creating a cost-effective medium but also allows for a thorough exploration of their metabolic potential. In this study, the auxotrophy of the acetogen Clostridium sp. AWRP was investigated through genomic analysis and growth performance in formulated media. It was found that the strain needs pantothenate and biotin and that substituting vitamin B 6 from pyridoxine to pyridoxamine or pyridoxal-5′-phosphate is crucial for growth. The determined chemically defined minimal medium supported both heterotrophic (using fructose as a substrate) and autotrophic (using syngas as a substrate) growth of the AWRP strain. To overcome the vitamin B 6 auxotrophy, the pdxST genes responsible for vitamin B 6 biosynthesis were introduced into the AWRP strain using plasmid-based gene expression system and CRISPR/Cas12a genome-editing technology. As a result, the genetically engineered strains were able to grow successfully without vitamin B 6 . This chemically defined minimal medium will enhance the fermentation performance of AWRP. IMPORTANCE The identification of auxotrophy in Clostridium sp. AWRP underpins subsequent investigations into its physiology and metabolism. Additionally, the development of a chemically defined minimal medium specific to this acetogenic bacterium will enable reproducible industrial processes. This innovation is particularly significant for the bioconversion of carbon monoxide and/or dioxide into commercially valuable chemicals through the process of gas fermentation.

THE ROLE OF THE COMMUNITY IN PROTECTING AND PROMOTING THE CULTURAL VALUES OF THE SAN DIU ETHNICITY OF SON DUONG DISTRICT TOWARDS SUSTAINABLE SOCIAL DEVELOPMENT OF TUYEN QUANG PROVINCE

The role of the community in protecting and promoting cultural values has always been studied by managers and scientists. Identifying and properly assessing the role of the community in protecting and promoting ethnic minority values requires an objective and comprehensive view, based on sound scientific arguments. The traditional culture of the San Diu people is the glue that binds the members of the community, creating a strong and united community. However, the socio-economic development in the years of renovation and the process of industrialization and modernization has had a strong impact on the culture of the San Diu people. Cultural changes are taking place in many directions, affecting community life. The current problem with state management agencies and the community in managing, protecting and promoting cultural values of the San Diu people is how to make heritage values permanent and develop. value in contemporary life.

Multi-Criteria Optimization of the Paper Production Process Using Numerical Taxonomy Methods: A Necessary Condition for Predicting Heat and Electricity Output in a Combined Heat and Power (CHP) System

The subject of this study is the optimization of the paper production process in one of Poland’s leading paper mills. In addition to its primary objective of paper production, the company generates heat and electricity for internal consumption and external clients, including the local municipality. Surplus energy may be sold on the power exchange; however, this requires forecasting the quantity of energy to be sold 24 h in advance, which introduces an element of uncertainty. Production stoppages, often caused by random events such as paper breakage, force a power decrease in the CHP system, further complicating energy forecasting. To minimize the occurrence of such events, numerical taxonomy methods were employed to determine the optimal screen speed (Vs) and winding speed (Vn) for two paper machines, based on the type and weight of the paper produced. This analysis utilized detailed daily data collected by the company over the period 2015–2020. The findings contribute to minimizing the occurrence of paper roll tearing, thereby reducing the risk of inaccurate forecasts of the energy and heat produced by the CHP system. Furthermore, the methodology employed in this study may be effectively applied to other optimization problems in industrial processes.

Optimizing the Operation of an Electrolyzer with Hydrogen Storage Using Two Different Methods: A Trade-Off Between Simplicity and Precision in Minimizing Hydrogen Production Costs Using Day-Ahead Market Prices

The potential for hydrogen is high in industrial processes that are difficult to electrify. Many companies are asking themselves at what cost they can produce hydrogen using water electrolysis with hydrogen storage. This article presents a user-friendly and less computationally intensive method (called method 1 in the following) for determining the minimum of the levelized cost of hydrogen (LCOH) by optimizing the combination of electrolyzer size and hydrogen storage size and their operation, depending on electricity prices on the day-ahead market. Method 1 is validated by comparing it with a more accurate and complex method (called method 2 in the following). The methods are applied to the example of a medium-sized industrial company in the mechanical engineering sector with a total natural gas demand of 8 GWh per year. The optimized LCOH of the analyzed company in method 1 is 5.00 €/kg. This is only slightly higher than in method 2 (4.97 €/kg). The article shows that a very good estimate of the LCOH can be made with the user-friendly and less computationally intensive method 1. For further validation of the methods, they were applied to other companies and the results are presented below.

Sustainable Solutions in Gas Separation: Exploring the Potential of Deep Eutectic Solvents

In the face of escalating environmental concerns, particularly related to greenhouse gas emissions, this study delves into the potential of Deep Eutectic Solvents (DESs) as a sustainable alternative in gas separation technologies. Focusing on the significant emissions of CO2, SO2, and H2S from industrial processes, this work reviews the application of DESs for their capture and separation. We investigate the physical properties of DESs, such as solubility and viscosity, which are crucial for their efficacy as sorbents. This review includes a comprehensive analysis of various DES formulations, exploring their roles in CO2 absorption, SO2 removal, and the separation of other gases like H2S. Additionally, we extend our examination to the applicability of DESs in the oil and gas industry, highlighting their effectiveness in removing sulfur and nitrogen impurities, and their potential in the extraction of organic constituents. The study reveals that DESs, characterized by their biodegradability and environmental sustainability, offer promising performance in gas separation, aligning with the principles of green chemistry. However, challenges such as high viscosity and the need for further understanding of their solubility dynamics under different conditions are addressed. This work underscores the importance of DESs as novel sorbents for gas purification and sets a foundation for future research aimed at enhancing their application on a broader industrial scale.

Pairing Oxygen Reduction and Water Oxidation for Dual‐Pathway H2O2 Production

AbstractHydrogen peroxide (H2O2) is a crucial chemical applied in various industry sectors. However, the current industrial anthraquinone process for H2O2 synthesis is carbon‐intensive. With sunlight and renewable electricity as energy inputs, photocatalysis and electrocatalysis have great potential for green H2O2 production from oxygen (O2) and water (H2O). Herein, we review the advances in pairing two‐electron O2 reduction and two‐electron H2O oxidation reactions for dual‐pathway H2O2 synthesis. The basic principles, paired redox reactions, and catalytic device configurations are introduced initially. Aligning with the energy input, the latest photocatalysts, electrocatalysts, and photo‐electrocatalysts for dual‐pathway H2O2 production are discussed afterward. Finally, we outlook the research opportunities in the future. This minireview aims to provide insights and guidelines for the broad community who are interested in catalyst design and innovative technology for on‐site H2O2 synthesis.

Outdoor Performance Monitoring Method for Degradation Studies of Perovskite Modules

ABSTRACTThis paper presents an outdoor performance monitoring method for degradation studies of perovskite modules, focusing on a large‐area perovskite module (81.9 cm2) over a long‐term monitoring campaign. The module underwent an industrial lamination process to prevent long‐term degradation from environmental factors. The characterization procedure involved degradation correction and determining the temperature coefficients and electrical parameters of the module using initial days of measurements. The results demonstrated temperature coefficients for Isc, Voc, and Pm (α′, β′, and γ) of −0.071%·K−1, −0.119%·K−1, and −0.113%·K−1, respectively, indicating a minimal temperature influence on this technology compared with conventional ones. Using this coefficient, the STC electrical parameters were retrieved from 1‐min power output data, resolving the uncertainty of the indoor/outdoor IV curve measurements caused by the curve scan direction (JV hysteresis effect). We also highlight the initial remarkable capacity recovery effect of almost 16% during the first 2 days of operation. Additionally, a procedure that includes the IV curves analysis taken every 10 min and their translation to standard conditions has been implemented to evaluate the degradation of the module over the long‐term outdoor campaign. The results show three different trends over the period.

A novel 3D uniformity measurement method in mechanical stirring systems

AbstractAccurate assessment of mixing uniformity is crucial in industrial mixing processes. This study proposes an evaluation method for three‐dimensional (3D) mixing processes that combines dual‐camera positioning and point pattern density fluctuation (PD) based on disordered hyperuniformity. This study employs a positioning method using dual‐camera to achieve precise capture and reconstruction of tracer particles in 3D space. The 3D reconstruction data is then evaluated for mixing performance using the PD method. A relationship model between |k| and time I values with mixing time was established for λ = 1. The results indicate that mixing time decreases with the increase of |k| and decreases with the decrease of I values. To ensure the accuracy of the PD method, feasibility analysis was conducted using conductometry. Additionally, the superiority of the PD method was validated by comparing it with the 3D‐Q method. The impact of bottom height of stirring paddle and motor speed on mixing effect were also investigated. This study establishes a fundamental groundwork and theoretical framework for optimizing parameters of stirring systems and assessing 3D mixing uniformity. It also offers important references and insights for engineering practices and theoretical research in related fields.

Evaluating stress resilience of cyanobacteria through flow cytometry and fluorescent viability assessment.

Cyanobacteria are prokaryotic organisms characterised by their complex structures and a wide range of pigments. With their ability to fix CO2, cyanobacteria are interesting for white biotechnology as cell factories to produce various high-value metabolites such as polyhydroxyalkanoates, pigments, or proteins. White biotechnology is the industrial production and processing of chemicals, materials, and energy using microorganisms. It is known that exposing cyanobacteria to low levels of stressors can induce the production of secondary metabolites. Understanding of this phenomenon, known as hormesis, can involve the strategic application of controlled stressors to enhance the production of specific metabolites. Consequently, precise measurement of cyanobacterial viability becomes crucial for process control. However, there is no established reliable and quick viability assay protocol for cyanobacteria since the task is challenging due to strong interferences of autofluorescence signals of intercellular pigments and fluorescent viability probes when flow cytometry is used. We performed the screening of selected fluorescent viability probes used frequently in bacteria viability assays. The results of our investigation demonstrated the efficacy and reliability of three widely utilised types of viability probes for the assessment of the viability of Synechocystis strains. The developed technique can be possibly utilised for the evaluation of the importance of polyhydroxyalkanoates for cyanobacterial cultures with respect to selected stressor-repeated freezing and thawing. The results indicated that the presence of polyhydroxyalkanoate granules in cyanobacterial cells could hypothetically contribute to the survival of repeated freezing and thawing.

Orderly Coating of Bilayer Polymer to Tailor Microenvironment for Efficient C−N Coupling Toward Highly Selective Urea Electrosynthesis

AbstractElectrosynthesis of urea from co‐reduction of carbon dioxide and nitrate is a promising alternative to the industrial process. However, the overwhelming existence of proton and nitrate as well as the insufficient supply of CO2 at the reaction interface usually result in complex product distributions from individual nitrate reduction or hydrogen evolution, instead of C−N coupling. In this work, we systematically optimize this microenvironment through orderly coating of bilayer polymer to specifically tackle the above challenges. Polymer of intrinsic microporosity is chosen as the upper polymer to achieve physical sieving, realizing low water diffusivity for suppressing hydrogen evolution and high gas permeability for smooth mass transfer of CO2 at the same time. Polyaniline with abundant basic amino groups is capable of triggering chemical interaction with acidic CO2 molecules, so that is used as the underlying polymer to serve as CO2 concentrator and facilitate the carbon source supply for C−N coupling. Within this tailored microenvironment, a maximum urea generation yield rate of 1671.6 μg h−1 mg−1 and a high Faradaic efficiency of 75.3 % are delivered once coupled with efficient electrocatalyst with neighboring active sites, which is among the most efficient system of urea electrosynthesis.

A Deep Learning-Based Approach for High-Dimensional Industrial Steam Consumption Prediction to Enhance Sustainability Management

The continuous increase in industrialized sustainable development and energy demand, particularly in the use of steam, highlights the critical importance of efficient energy forecasting for sustainability. While current deep learning models have proven effective, they often involve numerous hyperparameters that are challenging to control and optimize. To address these issues, this research presents an innovative deep learning model, automatically fine-tuned using an improved RIME optimization algorithm (IRIME), with the aim of enhancing accuracy in energy forecasting. Initially, the bidirectional gated recurrent unit (BiGRU) exhibited promising results in prediction tasks but encountered difficulties in handling the complexity of high-dimensional time-series data related to industrial steam. To overcome this limitation, a bidirectional temporal convolutional network (BiTCN) was introduced to more effectively capture long-term dependencies. Additionally, the integration of a multi-head self-attention (MSA) mechanism enabled the model to more accurately identify and predict key features within the data. The IRIME-BiTCN-BiGRU-MSA model achieved outstanding predictive performance, with an R2 of 0.87966, MAE of 0.25114, RMSE of 0.34127, and MAPE of 1.2178, outperforming several advanced forecasting methods. Although the model is computationally complex, its high precision and potential for automation offer a promising tool for high-precision forecasting of industrial steam emissions. This development supports broader objectives of enhancing energy efficiency and sustainability in industrial processes.

A numerical investigation on rheological turbulent flow through a 90° mixing elbow

Mixing elbows are widely used in various industrial processes to mix two different Newtonian or non-Newtonian fluids under turbulent flow conditions. This study numerically investigates the fluid flow and mixing characteristics in 90-degree elbows with different bend curvatures (curvature ratios of 3, 6, and 9) and Reynolds numbers ranging from 1 × 104 to 5 × 105 for both fluid types. The Reynolds-Averaged Navier–Stokes equations are solved using the turbulent k-epsilon model in ANSYS Fluent. Results show that the bend curvature creates an adverse pressure gradient that drives secondary flows, which become more pronounced with higher Reynolds numbers and lower curvature ratios. Higher Reynolds numbers improve mixing quality, as indicated by velocity and temperature variations quantified using standard deviations. For Reynolds numbers in the range of 104, velocity fluctuations initially increase, but at higher values (~ 105), they decrease, even by up to 64% as the Reynolds number rises from 1 × 105 to 5 × 105. Similarly, increasing the curvature ratio enhances mixing efficiency, with a 32% reduction in velocity fluctuations when the curvature ratio increases from 6 to 9. Furthermore, shear-thinning fluids (n=0.6\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$n = 0.6$$\\end{document}) exhibit superior mixing performance, with a standard deviation of velocity fluctuations at the outlet of 0.32, compared to 0.54 for shear-thickening fluids (n=1.4\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$n = 1.4$$\\end{document}). In terms of temperature fluctuations also, a similar trend is observed. These findings are valuable for optimizing mixing and fluid transport in industries such as chemical processing and food production, where effective mixing of complex fluids is critical. This study provides insights for improving the design of mixing systems that handle fluids with various rheological characteristics.

Digital twin for decision support system of industrial utility management

Manufacturing and industrial operations rely heavily on energy that is generated mostly from fossil fuels, such as coal, oil, and natural gas, which harm the environment and contribute to climate change. Thus, renewable energy is being integrated into industrial processes to lessen environmental effects and reduce fossil fuel usage. However, the renewable source performance process can be greatly affected by disturbances and constraints, such as ambient air temperature and relative humidity, minimum utility consumption, and the total energy required, making effective control difficult. This study proposes a digital twin built with machine learning regression techniques for load demand forecasting as a decision-support system for industrial utility management. From the results, the ensemble tree (ET) model produced the highest accuracy, based on validation and test dataset root mean squared error values of 23.164 and 27.558, respectively, and R2 values of 0.96 and 0.95, respectively. The digital twin and load demand forecasting approaches effectively created an efficient operating schedule for industrial utility management. The ET model had a total error of 23.86%, substantially lower than the average load demand's total error of 65.29%. Therefore, the ET model with weather conditions in four scenarios could be recommended to optimize energy utilization when creating the operating schedule.

Mapping Research Themes and Trends in Ergonomics within Industry 5.0: A Bibliometric Analysis

Abstract: Industry 5.0, the next stage of development after Industry 4.0, centers around the seamless integration of individuals and technology inside industrial processes to foster innovation that prioritizes human needs and experiences. Industry 5.0 diverges from Industry 4.0 by placing greater emphasis on the collaborative partnership between humans and machines rather than solely focusing on automation and advanced technologies like IoT and AI. The study employs bibliometric analysis to delineate the subjects and research areas in ergonomics within the context of Industry 5.0. The study analyzed literature from the Scopus database to identify trends and gaps in implementing ergonomic principles across different industrial sectors. The study addresses two distinct research inquiries: identifying overarching research subjects and emerging research themes. The results indicate the existence of four primary research clusters: the interaction between humans and advanced technology, the safety of work and collaboration between humans and robots, the optimization of multiple purposes and sustainable development, and the application of augmented reality in industrial design. The report emphasizes the growing importance of human-robot collaboration and artificial intelligence while acknowledging a decline in emphasis on user experience and virtual reality. The findings thoroughly analyze the present condition and development of ergonomics research in Industry 5.0 while providing significant recommendations for future investigations and real-world implementations.

Energy Flexibility in Aluminium Smelting: A Long-Term Feasibility Study Based on the Prospects of Electricity Load and Photovoltaic Production

This paper investigates the economic feasibility of utilising energy flexibility in aluminium production as a viable solution to leverage electricity surpluses arising from the increasing number of photovoltaic (PV) system installations. Future trends suggest that the generation capacity of PV systems will soon surpass consumption, leading to significant electricity surpluses, particularly during the summer. This surplus electricity, which is anticipated to be available at low prices, offers a unique opportunity to evaluate different investment and utilisation scenarios for aluminium production while simultaneously decreasing its environmental impact. The results demonstrate that, despite their high initial investment cost, large-scale PV power plants can potentially deliver maximum economic gains over a ten-year period. Conversely, the direct utilisation of surpluses without substantial investment can yield savings of up to EUR 17 million within the same time frame for Slovenia’s case with an aluminium smelter, which has a maximum power usage of 60 MW. The findings of this study have significant implications in terms of shaping future energy strategies and policies, emphasizing the value of integrating renewable energy sources and industrial processes for enhanced economic and environmental outcomes.

Multisensor feature selector for fault diagnosis in industrial processes

Multisensor feature selector for fault diagnosis in industrial processes

Tapered coreless optical fiber-based refractive index sensor for acetone concentration detection

A fast-response optical fiber sensor is designed and fabricated to detect different concentrations of volatile acetone. The proposed sensor structure was fabricated by splicing a segment of tapered coreless fiber (CLF) amid two single-mode fibers (SMF). Herein, tuned tapered diameters and lengths of CLF’s cladding were immersed in various concentrations of the acetone solutions to sense the effective refractive index (RI) variations. Accordingly, the sensor’s performance with tuned diameters at different lengths of the CLF was optimized to realize the suitable size of amplified evanescent fields. The sensor responded remarkably towards acetone concentrations, with a superior sensitivity of 336.102 nm/RIU, 0.163 nm/%, and 27.531 × 10−5 nm/ppm at 5 cm length and 60 µm taper diameter of CLF. The examined sensor possesses a fast response time with a minimum detection limit of 0.244 RIU, 5.025%vol, and 2.9 ppm. Though the rapid evaporation (volatility) of the acetone compound exempted it from air pollutants, many industrial and human body processes produce acetone which needs to be detected. The examined sensor may have the potential to detect in a non-invasive approach with high accuracy and rapid diabetes in humans, lung cancer, etc.

Antioxidant Potential Evaluation at Various Stages of Black Cumin Oil Production

Nigella sativa L. seeds and their industrial process products, oils, cake, and meal, are valuable sources of bioactive compounds with antioxidant properties. In this work, the effect of technological processes on the antioxidant capacity (AC) and total phenolic content (TPC) in the black cumin oils obtained by cold pressing and solvent extraction, as well as the by-products, were evaluated. The AC values of black cumin seeds (BCS), cold-pressed black cumin oil (BCCPO), black cumin oil extracted from seeds (BCEO-S), black cumin oil extracted from cake (BCEO-C), black cumin cake (BCC), and black cumin meal (BCM) were determined by 2,2-diphenyl-1-picrylhydrazyl (DPPH) and cupric reducing antioxidant capacity (CUPRAC) assays, whereas TPC in these samples was analyzed by the Folin–Ciocalteu (FC) method. Two applied conventional oil extraction methods, screw pressing and solvent extraction, significantly affected the AC and TPC in the obtained black cumin oils and by-products. The solvent-extracted black cumin oils revealed higher antioxidant properties (DPPH = 4041–16,500 μmol TE/100 g, CUPRAC = 1275–4827 μmol TE/100 g) than the cold-pressed black cumin oil (DPPH = 3451 μmol TE/100 g and CUPRAC = 3475 μmol TE/100 g). In addition, the oil yield (20.92–48.86%) and antioxidant properties of BCCPO (DPPH = 2933–5894 μmol TE/100 g and TPC = 135–199 mg GAE/100 g) and BCC (DPPH = 1890–2265 μmol TE/100 g and TPC = 284–341 mg GAE/100 g) closely depended on the nozzle diameters (5, 8, and 10 mm) mounted in a screw press. Although both by-products were a rich source of antioxidants, BCM had significantly lower CUPRAC (1514 μmol TE/100 g) and TPC (92 mg GAE/100 g) values than BCC (CUPRAC = 3397 μmol TE/100 g and TPC = 426 mg GAE/100 g). Nevertheless, acid hydrolysis and alkaline hydrolysis of BCM extracts significantly increased their antioxidant potential. However, the DPPH (35,629 μmol TE/100 g), CUPRAC (12,601 μmol TE/100 g), and TPC (691 mg GAE/100 g) results were higher for the BCM extract after acid hydrolysis than those for alkaline hydrolysate (DPPH = 2539 μmol TE/100 g, CUPRAC = 5959 μmol TE/100 g, and TPC = 613 mg GAE/100 g). Finally, the generated AGREEprep metrics highlighted the sustainability and the greenness of the cold pressing of oil from BCS.

Process Simulation and Technical Evaluation Using Water-Energy-Product (WEP) Analysis of an Extractive-Based Biorefinery of Creole-Antillean Avocado Produced in the Montes De María

The annual increase in the world’s population significantly contributes to recent climate change and variability. Therefore, researchers, engineers, and professionals in all fields must integrate sustainability criteria into their decision-making. These criteria aim to minimize the environmental, social, economic, and energy impacts of human activities and industrial processes, helping mitigate climate change. This research focuses on developing scalable technology for the comprehensive use of avocados, adhering to sustainability principles. This work presents the modeling, simulation, and the WEP (Water-Energy-Product) technical evaluation of the process for obtaining bio-oil, chlorophyll, and biopesticide from the Creole-Antillean avocado. For this, the extractive-based biorefinery data related to water, energy, and products are taken from the material balance based on experimental results and process simulation. Then, eight process parameters are calculated, and eleven technical indicators are determined. Later, the extreme technical limitations for every indicator are demarcated, and an evaluation of the performance of the indicators is carried out. Results showed that the process has a high execution in aspects such as fractional water cost (TCF) and energy cost (TCE), as well as solvent reuse during extraction processes (SRI) and production yield, noting that the mentioned indicators are above 80%. In contrast, the metrics related to water management (FWC) and specific energy (ESI) showed the lowest performance. These discoveries support the use of optimization techniques like mass process integration. The energy-related indicators reveal that the process presents both benefits and drawbacks. One of the drawbacks is the energy source due to the high demand for electrical energy in the process, compared to natural gas. The specific energy intensity indicator (ESI) showed an intermediate performance (74%), indicating that the process consumes high energy. This indicator enables us to highlight that we can find energy aspects that require further study; for this reason, it is suitable to say that there is potential to enhance the energy efficiency of the process by applying energy integration methods.