Process Industries Research Articles

Assessment of supply chain efficiency through a sustainable supply chain management strategy in the textile sector

The textile industry processes fiber into yarn or fabric. Problems often faced by textile companies are delays in raw materials, which result in the production and distribution of fabrics not reaching the target, so consumers are unsatisfied and switch to competing companies. In addition, solid waste from the production process is still disposed of, potentially polluting the environment. This study uses the Green Supply Chain Operation Reference (Green SCOR) approach to evaluate the performance of green supply chain management (GSCM) in textile companies located in Yogyakarta. The findings of this study could significantly impact the textile industry as they provide a comprehensive evaluation of GSCM performance. Twenty-two performance indicators have been validated using the Item-Content Validity Index (I-CVI) method and weighted using the Analytical Hierarchy Process (AHP) method. Based on the calculation results, the GSCM performance value is 60.208. Improvement recommendations are given for three indicators that need to be prioritized based on Importance Performance Analysis (IPA) matrix mapping and the actual condition of the company. Improvements can be made by using the Vacuum Flash Evaporation method so that recycled PVA can be reused, using natural materials or alternative auxiliary materials that are more environmentally friendly, increasing cooperation with companies engaged in processing weaving waste or textile waste appropriately and effectively, checking the concentration of starch solution not only when changing construction but every beam change, and forming a checklist form that is filled in for monitoring after machine settings and preparation of the production process.

A Strongly Coupled Metal/Hydroxide Heterostructure Cascades Carbon Dioxide and Nitrate Reduction Reactions toward Efficient Urea Electrosynthesis.

The direct coupling of nitrate ions and carbon dioxide for urea synthesis presents an appealing alternative to the Bosch-Meiser process in industry. The simultaneous activation of carbon dioxide and nitrate, however, as well as efficient C-N coupling on single active site, poses significant challenges. Here, we propose a novel metal/hydroxide heterostructure strategy based on synthesizing an Ag-CuNi(OH)2 composite to cascade carbon dioxide and nitrate reduction reactions for urea electrosynthesis. The strongly coupled metal/hydroxide heterostructure interface integrates two distinct sites for carbon dioxide and nitrate activation, and facilitates the coupling of *CO (on silver, where * denotes an active site) and *NH2 (on hydroxide) for urea formation. Moreover, the strongly coupled interface optimizes the water splitting process and facilitates the supply of active hydrogen atoms, thereby expediting the deoxyreduction processes essential for urea formation. Consequently, our Ag-CuNi(OH)2 composite delivers a high urea yield rate of 25.6 mmol gcat. -1 h-1 and high urea Faradaic efficiency of 46.1 %, as well as excellent cycling stability. This work provides new insights into the design of dual-site catalysts for C-N coupling, considering their role on the interface.

Enhancing Antioxidant Activity from Aquatic Plant Cymodocea nodosa for Cosmetic Formulation Through Optimized Ultrasound-Assisted Extraction Using Response Surface Methodology

This study aimed to enhance antioxidant extraction from the aquatic plant Cymodocea nodosa for cosmetic formulation through optimized ultrasound-assisted extraction using response surface methodology. The optimized conditions—30 min of extraction time, 30% ultrasonic power, and 25% hydro-ethanolic solvent—resulted in a high total phenolic content of 113.07 mg EAG/g DM and antioxidant activity of 67.02%. Chromatographic analysis revealed a rich profile of phenolic compounds, including sinapic acid (0.741 mg/g), myricetin (0.62 mg/g), and quercetin-3-O-rutinoside (0.3 mg/g), demonstrating the extract’s potent therapeutic properties. While the extract exhibited limited anti-inflammatory activity, it showed no cytotoxic effects on RAW 267.4 cells, ensuring its safety for cosmetic applications. The formulated cream maintained stable pH (6.58 to 6.6), consistent viscosity (5966.38 to 5980.6 cp), and minimal color changes over a 30-day period, indicating robust stability across various temperatures (4 °C, 25 °C, and 40 °C). These results confirm the potential of C. nodosa extracts to develop effective, stable, and eco-friendly cosmetic products, offering substantial benefits for skin health and emphasizing the importance of sustainable extraction processes in the cosmetics industry.

Robot intelligent perception and control

Abstract. In recent years, with the rapid development of robotics, intelligent perception and control has become the core research direction in the field of robotics. This technology plays a key role in many fields such as industrial automation, medical assistance, and autonomous driving, significantly improving production efficiency and service quality, and also promoting the intelligent processes of various industries. On the basis of an in-depth analysis of robot intelligent perception and control technology, this paper systematically reviews the development of visual and non-visual perception technology and discusses the application of multi-modal perception in complex environments. The latest development of motion control and force control technology is analyzed, and its importance in fine operation is expounded. The future development direction of robot intelligent perception and control technology is proposed, and the necessity of enhancing real-time robustness and system integration is emphasized, which provides theoretical support and technical reference for promoting the continuous innovation of robot intelligent perception and control technology.

Pre-connected and trainable adjacency matrix-based GCN and neighbor feature approximation for industrial fault diagnosis

Industrial fault diagnosis methods based on graph convolution network (GCN) becomes a hot topic for its great feature extraction ability to multivariate time-series data. However, GCNs ignore inter-sample temporality when constructing the adjacency matrix (AM), leading to low prediction accuracy. A novel fault diagnosis method based on pre-connected and trainable AM-based GCN and neighbor feature approximation (PTGCN-FA) is proposed at the node-level task. Firstly, PTGCN-FA introduces the temporal nearest neighbors into spatial nearest neighbors to pre-connect and construct the AM. Then, the AM is trained only where the samples are connected, which makes the best weights obtained and reduces the time complexity of the model. Finally, after the GCN layers, the trained AM is introduced into the approximation of features, which are neighbors in the original sample space. Two process industry cases are carried out, and the simulation results including diagnosis accuracy, confusion matrix, study to the ratio of labeled data and an ablation experiment verify PTGCN-FA has more efficient and accurate diagnostic performance than related methods. Additionally, the analysis of the temporal neighborhood weight parameter shows that the performance of fault diagnosis can be improved by considering both temporal and spatial information between samples.

Exploring solution composition and vacuum pulse effects in the osmotic processing of sole (Paralichthys sp.) fillets

The study investigates the osmotic dehydration (OD) of sole fillets and its mass transfer kinetics. Brine (S10), brine+sucrose (S10Az), and brine+sucrose+acetic acid (S10AA) solutions were used, with treatments conducted under atmospheric pressure (control) and with vacuum impregnation pulses (VI) for 7 hours. A positive mass change was observed over time in S10 and S10Az, leading to increased processing yields, while a decreasing trend was noted in S10AA. VI had a significant effect on NaCl content in S10AA, resulting in a 45 % processing time reduction. The Peleg model accurately fitted the solutes content dynamics, suggesting that VI shortens the time it takes to reach equilibrium for NaCl and sucrose. Product texture characteristics were affected by the solution composition, with increased hardness in S10AA, but not by VI treatment. These findings enhance the understanding of fish pre-treatment operational variables and suggest the VI potential for streamlining processes in the fish industry.

Diffusiophoretically Mediated Nanopatterning by Solvent Nanodroplets on Polystyrene Surfaces.

Dissolution is a ubiquitous process in nature and industry. However, due to technical difficulties, the detailed dissolution process at the nanoscale has seldom been captured experimentally. In this study, we investigated the dissolution dynamics in the confinement of toluene surface nanodroplets on polystyrene (PS) thin films in oversaturated toluene/water mixture solutions. This was achieved by adjusting the immersion durations from several minutes to 9 h. Dissolution takes place upon the deposition of nanodroplets on the PS surfaces, leading to the formation of surface nanostructures. Interestingly, we found that the induced nanostructures underwent complex morphological changes, from complex nanocraters with central bulges and/or multiple rims to simple nanocraters. We speculate that diffusiophoresis plays a key role in the formation of the complex nanocraters, as it facilitates the transportation of dissolved PS molecules inside the nanodroplets. We believe this finding not only enhances our understanding of dissolution dynamics at the nanoscale but also holds promise for applications in dissolution-based nanopatterning.

Hydrodynamics and operation of a multistage fluidized bed with particles of super-high density

High-density particles are commonly used in fluidized bed reactors in uranium recycling processes of nuclear industry, where high fluidization quality (i.e. low gas-solids contacting efficiency) is difficult to achieve, resulting in various problems such as reduced conversion, low product selectivity, stronger equipment vibration and bad operating stability, etc. The objective of this study was to validate the feasibility and advantages of a multistage fluidized bed in processing a super-high-density powder. Wolfram carbide powder of true density of 15630 kg/m3 was used in a cold-model counter-current three-stage fluidized bed with downcomers. Stability of operation, operating range and hydrodynamics were systematically studied. The fluidization quality and operating stability were also compared with a single-stage conical fluidized bed of similar diameter and same solids inventories. The experimental results demonstrated that this high-density wolfram carbide powder could be fluidized and circulated continuously at this multistage fluidized bed, but lower fluidization quality was observed and the stable operating range is narrow. Narrower stable operating range was observed at higher solids circulation rates. At corresponding operating conditions, the fluidization quality of multistage fluidized bed is significantly better than that of the conical fluidized bed with a similar solids inventory.

Advanced Study: Improving the Quality of Cooling Water Towers’ Conductivity Using a Fuzzy PID Control Model

Cooling water towers are commonly used in industrial and commercial applications. Industrial sites frequently have harsh environments, with certain characteristics such as poor air quality, close proximity to the ocean, large quantities of dust, or water supplies with a high mineral content. In such environments, the quality of electrical conductivity in the cooling water towers can be significantly negatively affected. Once minerals (e.g., calcium and magnesium) form in the water, conductivity becomes too high, and cooling water towers can become easily clogged in a short time; this leads to a situation in which the cooling water host cannot be cooled, causing it to crash. This is a serious situation because manufacturing processes are then completely shut down, and production yield is thus severely reduced. To solve these problems, in this study, we develop a practical designation for a photovoltaic industry company called Company-L. Three control methods are proposed: the motor control method, the PID control method, and the fuzzy PID control method. These approaches are proposed as solutions for successfully controlling the forced replenishment and drainage of cooling water towers and controlling the opening of proportional control valves for water release; this will further dilute the electrical conductivity and control it, bringing it to 300 µS/cm. In the experimental processes, we first used practical data from Company-L for our case study. Second, from the experimental results of the proposed model for the motor control method, we can see that if electrical conductivity is out of control and the conductivity value exceeds 1000 µS/cm, the communication software LINE v8.5.0 (accessible via smartphone) displays a notification that the water quality of the cooling water towers requires attention. Third, although the PID control method is shown to have errors within an acceptable range, the proportional (P) controller must be precisely controlled; this control method has not yet reached this precise control in the present study. Finally, the fuzzy PID control method was found to have the greatest effect, with the lowest level of errors and the most accurate control. In conclusion, the present study proposes solutions to reduce the risk of ice-water host machines crashing; the solutions use fuzzy logic and can be used to ensure the smooth operation of manufacturing processes in industries. Practically, this study contributes an applicable technical innovation: the use of the fuzzy PID control model to control cooling water towers in industrial applications. Concurrently, we present a three-tier monitoring checkpoint that contributes to the PID control method.

Umsetzungsbeispiele der Software-definierten Produktion

Abstract Traditional automation technologies cannot fully exploit the possibilities of digitalization. Software-defined production represents a way out. Here, the rigid automation pyramid is dissolved and replaced by networked services. This not only makes production in the manufacturing and process industries more flexible and efficient, but also enables, for example, the meaningful use of AI and the exploitation of sustainability potentials. This article uses examples to describe possibilities and potentials of implementing software-defined production.

Steam cracking in a semi-industrial dual fluidized bed reactor: Tackling the challenges in thermochemical recycling of plastic waste

Steam cracking is an integral process in the plastic manufacturing industry. Conventional steam crackers are tubular reactors and use fossil-based feedstocks like naphtha and LPG. This work presents steam cracking in a dual fluidized bed (DFB) reactor as an alternative for the direct steam cracking of plastic waste. Experiments were performed on a semi-industrial DFB system using naphtha, clean polyolefins, real-life plastic wastes, and a polyolefin-derived pyrolysis oil. The results show that steam cracking in a DFB is fundamentally equivalent to steam cracking in tubular reactors. Selective production of light olefins and monoaromatics was achieved within a temperature range of 700–825 °C. Naphtha yielded up to 56 % light olefins and 7 % BTXS, with ethylene and BTXS production positively correlating with cracking severity, while C3 and C4 olefins show a negative correlation. These results confirm that the established steam cracking mechanisms also apply to large-scale DFB steam crackers. The yield of light olefins is consistently obtained at approximately 52 % relative to the polyolefin content of the feedstock, regardless of the non-polyolefin content. This highlights the DFB steam cracker’s ability to produce light olefins directly from plastic waste without presorting. However, steam cracking in DFB results in significantly higher CO and CO2 yields than conventional steam cracking, especially with feedstocks containing non-polyolefins like PET and cellulose. Additionally, steam cracking of an olefin-rich pyrolysis oil yields up to 50 % light olefins with minimal coke formation, highlighting the potential in processing plastic waste pyrolysis oils without pretreatment steps such as distillation and hydrotreatment.

The Feasibility of Egypt's Photovoltaic Industry Drawing on China's Successful Experience

This study aims to evaluate the feasibility of Egypt's photovoltaic industry drawing on China's successful experience. Firstly, based on Egypt's national conditions and actual situation, the current situation, development potential, and challenges faced by the Egyptian photovoltaic market were analyzed.Egypts economic foundation remains less competitive, with outdated electricity infrastructure and long-term dependence on natural gas, posing challenges to its transformation. Egypt is one of the regions with the most concentrated solar energy resources in the world, which gives it the possibility and new opportunities to overtake in the photovoltaic field. Secondly, by analyzing the development process of China's photovoltaic industry, this paper explores China's successful experiences in policy support, market demand, technological level, financial support, and talent cultivation.Compared with China, Egypt's photovoltaic industry is still in an underdeveloped and developing stage, and requires sustained efforts in multiple aspects. This article compares the significant differences in the development of photovoltaic industries between China and Egypt, and analyzes the opportunities and challenges faced by Egypt's photovoltaic industry, as well as the corresponding strategies from three aspects: policy stability, demand activation, and desert photovoltaics. Finally, based on the research results, policy recommendations and development paths are proposed to promote the development of Egypt's photovoltaic industry, to provide reference and inspiration for the sustainable development of Egypt's photovoltaic industry.

Enhanced methylene blue degradation and miniralization through activated persulfate coupled with magnetic field

In this work, for the first time, the effectiveness of the degradation and mineralization process of methylene blue) MB) was investigated using activated persulfate (PS) with a magnetic field. The effect of various operating parameters, including pH, PS (5–20 mg/L), intensity of the magnetic field (1–4 A), initial concentration of methylene blue dye (25–100 mg/L), and contact time (30–120 min), was evaluated. Process optimization was conducted via the Taguchi model, and the optimal values of these factors were found to be pH = 5, PS = 10 mg/L, MFs = 4 A, reaction time = 30 min, and the initial concentration of methylene blue dye = 50 mg/L. Under optimal conditions, the methylene blue removal efficiency and TOC destruction efficiency reached 91.8% and 88%, respectively. The kinetics of the process followed pseudo-second order (R2 = 0.9723). According to the promising results of the research, the efficiency of dye purification using a magnetic field has increased by about three times compared to the state without this factor. It can be suggested that this system be used as a wastewater treatment process for the textile industry to reduce the toxicity of wastewater and total organic carbon (TOC).

Green strategies for the valorization of industrial medicinal residues of Serenoa repens small (saw palmetto) as source of bioactive compounds

Serenoa repens is a medicinal plant well-known for its therapeutic potential in treating various urological disorders and prevention of prostatic cancer. However, the extraction process in the pharmaceutical industry leads to the generation of plant residues, typically discarded, wasting valuable resources. In this study, we aimed to explore a series of green extraction strategies to effectively valorize the residues of Serenoa repens fruits. Initially, we employed supercritical CO2 (1.2% yield on dry biomass) on the discarded biomass to identify and quantify residual fatty acids and polyprenols (1.6% of the extract dry weight), a class of unsaturated isoprenoid alcohols with promising biomedical applications. Subsequently, subcritical water extraction was utilized on the exhausted biomass to extract polar compounds. An increase in the extraction yield was observed with the rise in processing temperature up to 180 °C (yields were found higher than 26%). Phenolic compounds and carbohydrate macromolecules profiles were affected by the increased hydrolytic conditions. Polar extracts exhibited robust bioactivities, demonstrating significant antioxidant activity and antimicrobial efficacy against Gram-positive and Gram-negative bacteria strains. Extracts obtained at 180 °C demonstrated the highest efficacy. Furthermore, in vitro assessment of mannans-rich fraction provided a new perspective of potential applications in the cosmeceuticals field. Results underscore the potential of the sustainable extraction biorefinery for the residue of this medicinal plant and demonstrate that, harnessing these bioactive compounds, new sustainable and eco-friendly approaches for its complete utilization can be offered, thereby promoting near-zero waste practices and contributing to a more sustainable future.

Wood trade regions of Russia: clustering approach development

Network analysis of the Russian timber industry was based on the information about timber transactions between Russian companies in 2020. The data were collected from the Unified State Automated Information System Accounting Timber and Transactions with It. The method of graph clustering was developed. The first step is clustering of the hole graph by Leiden algorithm. The second step is drawing of each Leiden created cluster in abstract space using Fruchterman–Reingold layout and extraction of clusters from layout using meanshift algorithm. Such approach helped us to divide many Leiden-created clusters into components. This algorithm has a problem of resolution limit. It tends to combine some medium and small clusters into large ones. Also, a special method was developed to limit the uncertainty of clustering – both Leiden algorithm and Fruchterman–Reingold layout are non-deterministic algorithms. Wood trade clusters vary in size and content. They are rather autonomous. The average share of intra-cluster trade is 89%. The modularity score of our partition is 0.863. Each cluster has been described using open sources from the Internet. The content of the clusters does not contradict the logic of the wood industry processes. The clusters create rather compact areas on the map – wood trade regions. Their borders often overlap with existing administrative boundaries. Five types of network structure of clusters were defined: vertical monocentric, vertical polycentric, horizontal, dendritic, simple. There are three factors of clustering in wood industry of Russia: production chains (4 types – pulp, plywood, lumber, chipboard chains), demand chains (redistribution of raw material between manufacturers within the cluster, accumulation of wood volumes for some enterprises outside the cluster, wood trade between traders within the cluster), common holder. We have shown that existing approaches to cluster detection based on location quotients often misrepresent economic networks.

Comparative analysis of volatile aroma components in different sweet potato wine

The methanol content and volatile aroma components were determined, and sensory evaluation and analysis were conducted. Results showed that the methanol contents of all the six sweet potato wine samples met the limits of the national standard, and a total of 258 volatile substances were detected. Among them, alcohols and phenols have the highest contents in the sample BBC-1 brewed in the family workshops, esters have the highest contents in the sample BBY-2 brewed in the distillery, acids and ketones have the highest contents in BBC-4 brewed in the family workshops, and aldehydes have the highest contents in BBY-1 brewed in the distillery. The sensory evaluation results showed that BBC-2 has the strongest and most elegant aroma, perfect typicality, and unique taste. The comprehensive evaluation results of BBY-2 are second only to BBC-2. The sweet potato wine samples BBC-2 and BBY-2 have better quality, and are suitable for promotion as the characteristic products of local sweet potato wine. These results can provide scientific basis for the improving the brewing process and quality of sweet potato wine industry in Xiapu County, Fujian Province. Bangladesh J. Bot. 53(3): 731-743, 2024 (September) Special

Asset management knowledge graph for production plants in process industry

Abstract The introduction and adoption of various semantic models for describing assets within a plant have paved the way for new opportunities. This contribution centers on the establishment and continuous maintenance of a plant asset management system based on knowledge graphs, utilizing the information contained in various semantic models. Additionally, it highlights how the graph can be leveraged in the creation and configuration of AI-based anomaly detection models, aimed at the monitoring of measurement values in a process plant. The concept paves the way for the wide deployment of AI models in monitoring applications in process industry.

Sustainable Entrepreneurial Process in the Deep-Tech Industry

To date, deep-tech entrepreneurship and sustainable entrepreneurship are both attracting the interest of researchers. Indeed, deep-tech is being employed to address future sustainable challenges in the present. Nevertheless, the process of deep-tech startups is filled with distinct obstacles. These types of startups may necessitate a more targeted sustainable entrepreneurial process and specialised knowledge compared to conventional technological startups or general sustainable entrepreneurial processes. Currently, most publications discuss either a sustainable entrepreneurial process or conventional technical startups. Therefore, this article aims to investigate the process of sustainable entrepreneurs as they transition from startup ventures to scaleup enterprises within the context of the deep-tech industry. Based on previous sustainable entrepreneurial processes, a multiple case study was conducted within six deep-tech startups, using a narrative progress research strategy, to find the sustainable process pattern. A conceptual model of a sustainable entrepreneurial process in deep-tech industry is established, including five phases with six activities: (i) Sustainable idea definition; (ii) Sustainable opportunity recognition and evaluation; (iii) Venture launch; (iv.i) Sustainable products/services development; (iv.ii) New sustainable enterprise financing; and (v) Sustainable enterprise scaleup. This process enables sustainable deep-tech entrepreneurs, policymakers, and financial investors to necessarily have an overview of the key entrepreneurial stages to navigate from the startup to the scaleup process.

Mono- and di-rhamnolipids mixtures from Pseudomonas aeruginosa for use in extreme conditions of pre- and post-salt oil reservoirs compared with synthetic surfactants

Rhamnolipids are multipurpose molecules known as natural glycolipid biosurfactants that are often biosynthesized by Pseudomonas aeruginosa strains. They are readily biodegradable, have less impact on the environment and are less toxic than conventional surfactants. They can be applied in ex situ microbial enhanced oil recovery. However, there is still a lack of knowledge concerning the drastic environmental conditions of post and pre-salt reservoirs. In this study, different mixtures with different proportions of homologs of rhamnolipids from two genetically modified strains (GMOs) of P. aeruginosa and a non-GMO strain compared to commercial surfactants (Arquad C-50 and/or Ultrasperse II®) regarding their efficiency under high pressure, temperature and salinity conditions. Wettability reversal and interfacial tension tests were performed together with central composite rotational designs. Both genetically modified P. aeruginosa strains produced mainly di-rhamnolipids, whereas the non-GMO strain produced approximately 50 % mono- and 50 % di-rhamnolipids. Rhamnolipids and Arquad C-50 reversed 100 % of the wettability under pre-salt and post-salt conditions, whereas Ultrasperse II® achieved 73.3 % and 34.2 % (100 ppm) wettability, respectively. Interfacial tension presented the lowest values for rhamnolipids, with values of 0.4 mN/m and 0.5 mN/m, whereas Ultrasperse II® presented values of 2.6 and 2.5 mN/m, respectively under post-salt and pre-salt conditions at the +1 level of the tested variables. All rhamnolipid congeners tested here were more effective under post and pre-salt reservoirs conditions than commercial surfactants, thus expanding their potential for use not only in environmental bioremediation but also in oil industry processes.

Solving industrial fault diagnosis problems with quantum computers

In this article, we investigate in how far quantum computers can be leveraged to solve NP-complete fault diagnosis problems within the area of industrial cyber-physical systems. Therefore, two approaches are proposed which exploit quantum computing to solve diagnosis problems: The first method employs Grover’s algorithm, and the second is based on the Quantum Approximate Optimization Algorithm. To show the industrial application, we present an integrated approach to learn the diagnosis model from process data, check whether the model is suitable, and use it for diagnosis. The result is a method for quantum industrial fault diagnosis. For this approach, the diagnostic capabilities and the runtime have been evaluated on an IBM Falcon processor using three publicly available benchmarks from the process industry. Further, the scaling between quantum computers and classical PCs has been analyzed.