Process Optimization Research Articles

Infrared drying effects on the quality of jujube and process optimization using response surface methodology

This study developed a specialized laboratory-scale apparatus utilizing infrared technology to optimize the infrared drying process and investigate water transfer dynamics and structural transformations during infrared radiation drying (IRD) of jujube. Key parameters, including rehydration ratio, color deviation, and Vitamin C (VC) retention rate, were assessed for Xinjiang gray jujube were assessed. Additionally. Comparative analyses were conducted to evaluate microstructural, physicochemical, and volatile component differences between IRD and hot air drying (HAD) methodologies. Response surface analysis was employed to optimize IRD parameters. The results identified optimal conditions as an infrared temperature of 55 °C, a loading capacity of 490 g, and an infrared radiation distance of 11 cm, resulting in a rehydration ratio of 1.75, a color deviation of 3.01, and a VC retention rate of 59.10g/100g. IRD demonstrated superior performance compared to HAD, with a 34.88g/100g improvement in VC retention rate and a 42.90g/100g reduction in drying time. Additionally, jujube dried using IRD exhibited a denser microstructure than those dried by HAD. These findings highlight the effectiveness of IRD in accelerating drying processes while maintaining high jujube quality, thereby providing a robust theoretical foundation for future jujube drying research.

Optimizing Factory Workers Work Shifts Scheduling Using Local Antimagic Vertex Coloring

Optimization of industrial processes, reduction of worker costs, and protection of workers well-being are significantly dependent on effective work shifts scheduling. This article introduces a new approach to work shifts scheduling by combining Local Antimagic Vertex Coloring. In the provided model, workers are diagrammed as edges, while work shifts are shown as vertices. In order to ensure that adjacent vertices are allocated distinct weights that correspond to non-overlapping work shifts, the Local Antimagic Vertex Coloring approach is used to assign uniform weights to vertices. To optimize the effectiveness of scheduling, regular graphs are used, offering a methodical and fair framework for administrating shift allocations. Adopting this comprehensive approach ensures fair allocation of responsibilities among all workers, minimizes conflicts over shift schedules, and meets operational requirements such as skill levels, shift lengths, and staff availability. By virtue of its versatility, this model may be tailored to various industrial environments, therefore enhancing both scheduling efficiency and staff satisfaction. The actual applications of this method clearly demonstrate its durability, identifying significant improvements in shift planning, reduction of scheduling errors, and a more effective work shifts management process. This paper proposes a comprehensive solution to the complex problem of scheduling work shifts for industrial workers, including both theoretical and practical benefits.

Liquid CO2-Capture Technologies: A Review.

Escalating global carbon dioxide (CO2) emissions have significantly exacerbated the climate impact, necessitating imperative advancements in CO2-capture technology. Liquid absorbents have received considerable attention in carbon capture for engineering applications, due to their high flexibility, reliability, and recyclability. Nonetheless, the existing technologies of liquid CO2 capture suffer from various issues that cannot be ignored, such as corrosion, elevated costs, and pronounced secondary pollution. More efforts are required to realize process optimization and novel absorbent innovation. This review presents nanofluids and other novel liquid absorbents such as ionic liquids, amino acids, and phase-change absorbents. The preparation, mechanisms of action, and influencing factors of nanofluid absorbents are discussed in detail to provide researchers with a comprehensive understanding of their potential applications. Further, the challenges (including energy loss, environmental and human health, barriers to application and capture performance, etc.) encountered by these innovative absorbents and techniques are also commented on. This facilitates side-by-side comparisons by researchers.

Etching Chemistry Process Optimization of Ethylene Diluted with Helium (C2H4/He) in Interconnect Integration

Etching Chemistry Process Optimization of Ethylene Diluted with Helium (C2H4/He) in Interconnect Integration

Synthesis and characterization of eco-friendly cathodic electrodes incorporating nano Zero-Valent iron (NZVI) for the electro-fenton treatment of pharmaceutical wastewater

The electro-Fenton process has the potential to be an efficient effluent treatment method, contingent on effective process optimization. It relies on two critical components: efficient in-situ H2O2 generation and the integration of highly reactive heterogeneous catalysts into electrode synthesis. In this study, several cathodic electrodes were synthesized, including those using zero-valent iron nanoparticles (P-NZVI), zero-valent iron nanoparticles supported on activated carbon (AC-NZVI), and El Hamma Bentonite clay loaded with zero-valent iron nanoparticles (HB-NZVI). These electrodes were fabricated using sustainable, straightforward methods and subjected to thorough physicochemical and electrochemical characterization. The goal of this research was to develop environmentally friendly cathodes, employing either pressed catalyst techniques or supporting the catalyst on carbon felt (CF) or titanium foil. These electrodes were evaluated within a heterogeneous electro-Fenton-like process, with a boron-doped diamond (BDD) anode, targeting the efficient degradation of the pharmaceutical pollutant Antipyrine (ATP). Among the tested configurations, the AC-NZVI/CF electrode demonstrated the highest degradation efficiency. Key experimental parameters, such as pH, current density, and water matrices, were systematically studied to optimize the process. Under optimal conditions (pH 7, current density of 55 mA A/cm2), 80 % mineralization of a 40 mg/L ATP solution was achieved within 150 min, with an energy consumption of just 0.3502 kWh/g. The performance of the AC-NZVI/CF electrode remained stable when applied to real wastewater and after five consecutive cycles. Comprehensive analyses using FTIR, SEM-EDS, and XPS confirmed the stability and recyclability of the electrode, showcasing its potential for sustainable wastewater treatment applications.

Development of a Mathematical Model for Palm Fruit Digester Design: Integrating Dimensional Analysis and Process Optimization

This investigation delineates a thorough methodology for the formulation of a parametric model about a palm fruit digester apparatus, employing the tenets of dimensional analysis. The palm fruit digester, an essential component within the palm oil manufacturing processes, encompasses intricate interactions among various parameters that influence its operational efficiency and throughput. A palm fruit digester was conceptualised and fabricated locally to attain a more profound comprehension of these interrelationships. The performance parameter was scrutinized as data were amassed during the apparatus's testing, and the Buckingham Pi theorem was utilized to derive dimensionless Pi terms from pertinent parameters. The results of our analysis indicated that R2 values of 0.9956 for both throughput and machine efficiency were achieved. Consequently, the model can forecast the efficiency and throughput of the palm fruit digester. This helps researchers understand that the palm fruit digester's operational efficiency and throughput are essential to the industry's sustainability, financial stability, and quality standards. In addition to helping to optimise these procedures, the dimensional analysis modelling approach advances strategic ideas that have the potential to reshape operational capabilities in the processing of palm oil.

Теоретичні підходи до розвитку логістичних систем в умовах нестабільності економічного середовища

It has been established that modern conditions of economic instability are characterized by rapid changes in demand, supply, and other business parameters, forcing enterprises to seek new solutions to ensure their competitiveness. The necessity of flexible logistics systems management has been proven, allowing for adaptation to new challenges, enhancing the effectiveness of management practices, and ensuring sustainable business development. Theoretical approaches to developing logistics systems play a crucial role in addressing these tasks, particularly by implementing innovative technologies such as artificial intelligence, the Internet of Things (IoT), blockchain, and automation. The development of logistics systems is characterized as a complex and multidimensional task that requires flexibility, innovation, and sustainability to overcome economic risks. A logistics system structure is presented, including the main objective, core idea, goals, functions, principles, and the primary aim within the context of international logistics systems. The main directions for decision-making in conditions of economic instability are discussed, including risk and uncertainty analysis, resource and asset diversification, cost reduction, process optimization, flexible planning, innovation, digitalization, and a focus on resilience. The proposed theoretical approaches to developing logistics systems as adaptive, innovative, risk-oriented, customer-focused, and cooperative− contribute to effective functioning and adaptation in a rapidly changing economic environment. It has been demonstrated that important directions for ensuring the sustainability and competitiveness of businesses include: firstly, the adaptability of logistics systems to unstable conditions, which entails their ability to respond quickly to changes in market situations, economic crises, fluctuations in demand, and other external factors; and secondly, the integration of innovative technologies into local processes (digital platforms for monitoring; the use of big data; automation and robotics). Keywords: adaptability, economic instability, efficiency, logistics system, development, management, enterprise.

Developing Framework for Implementing Total Quality Management (TQM) in Sustainable Industrialized Building System (IBS) in Construction Projects

The construction sector is increasingly shifting towards sustainable and efficient methodologies, with the industrialized building system (IBS) playing a pivotal role in this transformation. Despite this, the adoption of total quality management (TQM) in IBS projects faces significant challenges, including a lack of comprehensive understanding of TQM standards and resistance to change within the industry. This study addresses these gaps by developing a comprehensive framework for implementing TQM in sustainable IBS construction projects. The objective is to enhance project quality and sustainability by addressing critical issues such as limited stakeholder awareness and opposition to TQM adoption. Using qualitative methodology rooted in phenomenology, this study explores the lived experiences of key stakeholders involved in IBS projects, including project managers, construction professionals, and government officials. Data were collected through in-depth interviews to capture their perspectives on TQM integration in the IBS context. The findings highlight the crucial role of TQM in fostering continuous improvement, enhancing stakeholder collaboration, and ensuring adherence to quality standards throughout the project lifecycle. The proposed framework incorporates essential TQM principles such as process optimization, employee engagement, and customer focus, providing a structured approach to overcoming the barriers to effective implementation. Furthermore, the framework promotes sustainability by reducing waste and improving energy efficiency in IBS projects. This study offers valuable insights for construction professionals, policymakers, and industry stakeholders, presenting practical solutions to improve the quality and sustainability of IBS construction. Leadership, cultural transformation, and continuous improvement are identified as key factors for successful TQM integration, ultimately leading to more efficient and sustainable building processes in the construction industry.

Impact of the Fitness Function on the Development of Mathematical Models by Symbolic Regression

Objective: This study aims to investigate the impact of the fitness function on the development of mathematical models using Symbolic Regression based on experimental data from the decolorization process of a synthetic effluent, employing a Taguchi matrix to evaluate the efficiency of this modeling process and its application to other processes. Theoretical Framework: The study is grounded in references on advanced oxidation processes, experimental design with an emphasis on the Taguchi method, and Symbolic Regression. Method: The research methodology involved modeling and simulation, with data collection conducted through photodegradation experiments on a synthetic effluent. Results and Discussion: The results demonstrated that the fitness function affects the predictive quality of the model obtained through Symbolic Regression. This impact is highlighted in the discussion section through validation experiments. Possible discrepancies and limitations of the study are also considered in this section. Research Implications: The practical and theoretical implications of this research are discussed, providing insights into how the findings can be applied or influence practices in the field of industrial process modeling and optimization. These implications are broadly applicable across various industrial sectors that involve transformation processes. Originality/Value: This study contributes to the literature with the application of new mathematical modeling techniques employed in conjunction with Experiment Design. The relevance and value of this research are evidenced by demonstrating that the use of Symbolic Regression is viable and may be superior to the Ordinary Least Squares Method.

Enhancing biosensor capabilities through laccase immobilization in nanostructured Langmuir-Blodgett films for phenol detection

Fabricating nanoscale structures combining various elements with specific functionalities is a pertinent strategy for enhancing sensor capabilities. In this study, we immobilized Laccase (Lac) in a biomimetic environment provided by a nanostructured Langmuir-Blodgett (LB) film of an amphiphilic material (octadecylamine, ODA), where poly(3-hexylthiophene-2,5-diyl) (P3HT) has been coimmobilized as the electron mediator. Tensiometry demonstrates that the enzyme is incorporated in the floating monolayers efficiently. The monolayers were transferred to solid substrates as LB films and characterized using UV–vis and infrared spectroscopies and Atomic Force Microscopy, exhibiting a quasi-ordered structure with low roughness. The films' ability to detect phenols was evaluated through enzymatic activity estimation using colorimetric and voltammetry measurements against vanillin, catechol, and pyrogallol. Our results demonstrate that the electrochemical response depends on the phenol's nature, with limits of detection for vanillin, catechol, and pyrogallol at 1.10.10−6, 2.13.10−7, and 2.07.10−7 mol.L−1, respectively. Additionally, the intensity of the response does not correlate with film thickness, confirming that the electrochemical reaction is a surface phenomenon for catechol and pyrogallol. We believe this study provides valuable insights into phenol detection in the food industry, which is crucial for ensuring food safety, quality, and authenticity by aiding in regulatory compliance, process optimization, and product preservation.

Pulsed Light and Retort Processing of Coconut Inflorescence Sap (neera): Process Optimization and Storage Stability

Pulsed Light and Retort Processing of Coconut Inflorescence Sap (neera): Process Optimization and Storage Stability

Preparation, process optimization, and performance study of tea polyphenol-sodium alginate/ethyl cellulose composite microcapsules for green slow-release formaldehyde capture agent

Aiming at the problem of prolonged formaldehyde release from artificial boards, a green slow-release formaldehyde scavenger was proposed in this study. Tea polyphenol microcapsules (TPM) were prepared by ionic gel-solvent evaporation method using sodium alginate/ethyl cellulose as the wall material and tea polyphenol as the core material. Fourier transform infrared spectroscopy (FTIR) analysis showed that the TPM exhibited the same characteristic absorption peaks as those of tea polyphenol, ethyl cellulose and sodium alginate. This indicates that the TPM was successfully prepared and the thermal stability of TPM meets the requirements of the hot pressing process of man-made boards. The optimal process of TPM was as follows: the mass ratio of tea polyphenol to ethyl cellulose was 2.58, the dosage of emulsifier was 1.01 g, and the mass fraction of sodium alginate was 17.23%, the encapsulation rate of TPM was 78.31%, and the average particle size was 18.69 ± 4.66 μm. After 180 min. After 180 min, the aldehyde reduction efficiency was 61.08%. In conclusion, TPM meets the requirements of the production process of wood-based panels and the need for continuous control of formaldehyde emission from wood-based panels.

Optimization of the extraction process of goji berry pectin using response surface methodology and its suitability as thickener for yogurt

Although goji berry with many main biological activity components is a nutritional medicinal and edible plan and widespread in the northeast of China, its current development also faces a new challenge of overcapacity. So this study was largely focused to investigate the optimal extraction process conditions (extraction water proportion, acidic pH regulating reagent, adjusted pH, extraction temperature, extraction time) for goji berry with increased yield. Box Behnken experimental design (BBD) was used to model the mathematical model of the relationship between the three main influence of pivotal extraction parameters (extraction pH, extraction time and extraction temperature) selected by the single factor experiments on the responses of goji berry pectin yield (%). Morover the predicted models were adequately fitted to the real experimental data (18.507 % ± 0.275 %, P < 0.001) for all the response variables within a short time. The maximum yield of pectin was sufficiently obtained with optimal conditions of the best water-goji ratio of 20:1, extraction pH of 2.2 adjusted by hydrochloric acid, extraction time of 80 min at 76 °C. Interesting, as thickener, goji berry pectin does not only improve the health benefits of yogurt in some studies have reported, but it also improves its sensory properties and viscosity of the yogurt in this paper. It will effectively improve the efficiency of obtaining goji berry pectin, which will provide strong experimental evidence for the widespread application of goji berry pectin. Although goji berry pectin does not have significant advantages in sensory evaluation and yogurt viscosity, it has been proven in some studies to have good functionality in terms of nutrition. This provides a good idea for the development of functional foods urgently needed in the current aging society. Goji berry will be an effective alternative source of pectin on health food industry on large scale. In addition, this paper also provides a feasible approach to effectively solve the problem of goji berry overcapacity.

Bacteriophage-Activated DNAzyme Hydrogels Combined with Machine Learning Enable Point-of-Use Colorimetric Detection of Escherichia coli.

Developing cost-effective, consumer-accessible platforms for point-of-use environmental and clinical pathogen testing is a priority, to reduce reliance on laborious, time-consuming culturing approaches. Unfortunately, a system offering ultrasensitive detection capabilities in a form that requires little auxiliary equipment or training has remained elusive. Here, a colorimetric DNAzyme-crosslinked hydrogel sensor is presented. In the presence of a target pathogen, DNAzyme cleavage results in hydrogel dissolution, yielding the release of entrapped gold nanoparticles in a manner visible to the naked eye. Recognizing that Escherichia coli holds high relevance within both environmental and clinical environments, an E. coli-responsive DNAzyme is incorporated into this platform. Through the optimization of the hydrogel polymerization process and the discovery of bacteriophage-induced DNAzyme signal amplification, 101 CFU mL-1 E. coli is detected within real-world lake water samples. Subsequent pairing with an artificial intelligence model removed ambiguity in sensor readout, offering 96% true positive and 100% true negative accuracy. Finally, high sensor specificity and stability results supported clinical use, where 100% of urine samples collected from patients with E. coli urinary tract infections are accurately identified. No false positives are observed when testing healthy samples. Ultimately, this platform stands to significantly improve population health by substantially increasing pathogen testing accessibility.

Machine‐Learning‐Assisted Process Optimization for High‐Performance Organic Thermoelectrics

AbstractOptimizing the processing conditions of conjugated polymers is a key step in improving the performance of various organic electronic devices, including organic thermoelectric (TE) devices that are capable of harvesting energy from waste heat. However, the inherent structural and energetic disorders in these materials and their unpredictable property changes after processing complicate the optimization principles, requiring numerous trial‐and‐error experiments to maximize the TE performance. Here, a machine‐learning (ML)‐based design of experiments approach is introduced to address these challenges, and its effectiveness is demonstrated using a representative thiophene‐based doped polymer system for organic TE. This approach not only helps to quantitatively understand how each processing parameter affects the TE properties of the polymer but also facilitates the prediction of optimal processing conditions, leading to achieve maximum TE performance with minimal experiments within a large parameter space. Furthermore, the ML‐based approach is validated by revealing the origins of the power factor maximization at the ML‐predicted processing conditions through analysis of the morphology and electronic states of the doped polymer films. The proposed methodology is applicable to the majority of polymer systems for organic thermoelectric energy conversion and will provide guidelines for determining optimal process conditions and improving TE performance with minimal effort.

Beyond Composting Basics: A Sustainable Development Goals—Oriented Strategic Guidance to IoT Integration for Composting in Modern Urban Ecosystems

IoT-based composting provides clear advantages over conventional urban composting in areas such as enhanced monitoring, efficiency, resource utilization, and management. Bibliometric analysis of 121 publications on IoT-based urban composting identified critical research gaps and emphasizes the necessity for a strategic framework for full implementation and execution of sustainable development goals-oriented IoT-based composting in modern cities across. Under the key theme of IoT-based urbanized composting automation, 16.5% of publications focus on urbanized composting automation but overlook the system’s scalability. The lowest mean citations of 72.7 (22.3% of publications) in intelligent composting process optimization show the lack of broader applications. A total of 28.9% of total publications focus on urban composting sustainability assessment but lack IoT integration in their scope. The composting process, pollution, environmental impact, cost, and life cycle analysis of modern city composting share 19% and 13.3%, respectively. However, both key themes lack real-time monitoring, operation, and economic feasibility for scalable models. The article highlights a fragmented landscape providing sustainable development goals-oriented strategic guidance for the full implementation and execution of IoT-based composting facilities in modern city ecosystems. The article comprehensively explains the budgetary constraints, scalability, data management, technological compatibility, privacy, security, and regulatory compliance essential for sustainable operation.

How do businesses utilize change management for process optimization? A cross-analysis among industrial sectors

PurposeThis paper aims to present a systematic literature review of 176 studies relating to change management in the context of process optimization and to investigate how companies effectively use change management to optimize processes across different industrial sectors.Design/methodology/approachDescriptive statistics are used to represent patterns, trends and correlations between change management strategies, research methods applied for processes optimization and industry field. A comprehensive analysis of the papers’ keywords, crossed with research methods and industrial sectors, allowed us to substantiate the results in analytic terms. For some selected studies, chosen on the basis of their significance to the research field, the contents were mapped and discussed in detail.FindingsThis study provides numerous insights into the various applications of change management across different industry fields. In general, change management appears to be no longer a theoretical discipline, showing instead practical relevance, which is reflected in testing theories through case studies and real implementations. The review emphasizes the need for careful and systemic planning by companies, effective communication, employee involvement and supportive organizational culture. These factors are crucial for enhancing process efficiency and employee acceptance of change. Digital technologies also prove to be valuable support for change management during process optimization.Originality/valueThe innovative contribution of this paper consists of the joint perspective taken when looking at process optimization and the application of change management strategies. Such a perspective favors an in-depth examination of the interactions between the two aspects and provides more comprehensive results compared to the existing literature.

Impact of tool geometry and friction stir welding parameters on AZ31 magnesium alloy weldment wear behaviour and process optimization

This study investigates the impact of friction-stir welding (FSW) tool pin shape (TPS) and processing variables, viz., rotation speed (RS), axial load (AL), and traverse speed (TS), on weld beads’ wear characteristics as per ASTM G99 standard. Wear rate (WR), friction force (FF), and coefficient of friction (CoF) are analyzed based on Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). FSW performed with a hexagonal TPS provides a better material flow between the plates, influencing the joint’s strength and improving the wear resistance of weldments. Higher RS leads to high material flashing, providing lower strength and wear properties. Changes in TPS from triangle to pentagon and from pentagon to hexagon produced higher tensile strength, at 11.16% and 12.15%, respectively. The Chimp Optimization Algorithm (ChOA) shows an optimal condition of hexagon TPS, AL of 2 kN, RS of 1800 rpm, and TS of 25 mm/min, whereas TOPSIS optimal condition are hexagon TPS, AL of 4 kN, RS of 1400 rpm, and TS of 50 mm/min. Confirmation experiments with optimal conditions shows, ChOA producing lower WR, CoF, and FF by 12.5, 2.56, and 1.54% than TOPSIS. Compared with TOPSIS, ChOA produced lower WR, CoF, and FF by 12.5%, 2.56%, and 1.54%.

Revolutionizing the Ammonia Alkali Process for Enhanced CO2 Conversion and Productions: Insights from Aspen Plus Modeling and Process Optimization

Revolutionizing the Ammonia Alkali Process for Enhanced CO2 Conversion and Productions: Insights from Aspen Plus Modeling and Process Optimization

Определение способов повышения энергоэффективности путем анализа электропотребления предприятий судостроительной и судоремонтной отрасли

The possibilities of improving energy efficiency in the shipbuilding and ship repair industry are being considered. Energy efficiency plays a key role in modern industry, especially in industries with high energy consumption, such as shipbuilding and ship repair. In the Astrakhan region, with a significant amount of available water resources, there are many enterprises in this industry. An overview of the industry in the region is presented, an analysis of the structure and dynamics of electricity consumption at enterprises in this industry is carried out, the identification of the main consumers of electricity and the most energy-consuming processes are identified. Based on these data, measures are proposed to optimize energy consumption. The existing technologies and methods aimed at reducing energy consumption and increasing energy efficiency in the shipbuilding and ship repair industry are analyzed. Both technical and organizational measures are considered, such as the introduction of energy-saving equipment, optimization of production processes and the introduction of energy monitoring and management systems. Recommendations on improving the energy efficiency of enterprises in the shipbuilding and ship repair industry will reduce energy costs, improve the environmental sustainability of production and increase the competitiveness of companies in a market economy. The results obtained can be used by the management of enterprises, energy management specialists and government agencies to develop strategies to reduce energy consumption and improve energy efficiency in this industry. An integrated approach will be useful to enterprises in the shipbuilding and ship repair industry for the efficient use of available resources, reducing costs and minimizing negative effects on the environment, which in the long term will contribute to increasing competitiveness and sustainability.