Improve Production Processes Research Articles

A generative pre-trained transformer industrial bot to improve operators’ working experience in a small Industry 5.0 factory

The industrial sector is embracing a new revolution, Industry 5.0 (I5.0), focusing on human well-being and ecosystem preservation. Previous industrial revolutions have emphasized incorporating the latest state-of-the-art innovations and technologies to improve production processes, overseeing some of their long-term damaging impact on human beings. Our research contributes to the I5.0 practical implementation in factories by proposing the design of a generative pre-trained transformer (GPT) industrial bot as a tool to assist workers of a small experimental factory in improving their daily working experience. The industrial bot closely tracks factory production and allows operators to monitor a few fundamental elements of their well-being via text queries, such as the pollution level and the maximum overtime hours per worker. It also provides factories with three valuable functions: faulty equipment discovery, root cause analysis, and synthetic data generation. These features originate from factory-customized data loaded into the OpenAI GPT4 language model (LM) presented in two industrial bot versions. The first is an offline version, created using a Langchain agent connected to the GPT4 LM through OpenAI APIs and visualized with Streamlit, an open-source front-end tool. The second is an online version produced by the GPT4 internal function that creates customs GPTs. We highlight both versions’ advantages and disadvantages to guide factories in considering the suitable environmental model when adopting I5.0. Our system also allows operators to receive additional tips, thanks to the online GPT4 robust database, to enhance their knowledge on maintaining their well-being and their factory contextualized on the query sent to the industrial bot.

Integrative Literature Review of Methods and Tools for Identifying Environmental Impacts in Projects in Plastics Industries

Objective: This study seeks to identify the methods and tools described in international scientific documents for identifying environmental impacts in plastics industry projects. Method: To identify the methods and tools, an integrative literature review was developed, seeking to explore and identify the state of the art regarding the objective of the study. Results and Discussion: The results indicate that Life Cycle Assessment (LCA) is the most prominent method for identifying environmental impacts in the plastics industry, and is applied to improve production processes, product design and end-of-life disposal, regardless of the sector within this industry. However, different databases and approaches are used to identify and improve processes and design in this sector. Research Implications: It is a study with vast potential to show how environmental concerns are within plastic industry projects and how impacts related to design, production process and end of life are being identified in this sector.

Tracing the Origin of Oxide Inclusions in Vacuum Arc Remelted Steel Ingots Using Trace Element Profiles and Strontium Isotope Ratios

Non-metallic inclusions (NMIs) in steel have a detrimental effect on the processing, mechanical properties, and corrosion resistance of the finished product. This is particularly evident in the case of macroscopic inclusions (>100 µm), which are rarely observed in steel castings produced using state-of-the-art technologies, whereby casting parameters are optimized towards steel cleanliness, and post-treatment steps such as vacuum arc remelting (VAR) are used, but frequently result in the rejection of the affected product. To improve production processes and develop effective countermeasures, it is essential to gain a deeper understanding of the origin and formation of NMIs. In this study, the potential of elemental and isotopic fingerprinting to trace the sources of macroscopic oxide NMIs found in VAR-treated steel ingots using SEM-EDX, inductively coupled plasma mass spectrometry (ICP-MS), laser ablation ICP-MS (LA-ICP-MS), and laser ablation multicollector ICP-MS (LA-MC-ICP-MS) were exploited. Following this approach, main and trace element content and 87Sr/86Sr isotope ratios were determined in two specimens of macroscopic NMIs, as well as in samples of potential source materials. The combination of the data allowed the drawing of conclusions about the processes leading to the formation of these inclusions. For both specimens, very similar results were obtained, indicating a common mechanism of formation. The inclusions were likely exogenous in origin and were primarily composed of calcium–aluminum oxides. They appeared to have undergone chemical modification during the casting and remelting process. The results indicate that particles from the refractory lining of the casting system most likely formed the macroscopic inclusions, possibly in conjunction with a second, calcium-rich material.

Engineering Management and Modular Design: A Path to Robust Manufacturing Processes

Manufacturing environments, characterized by dynamic changes and uncertainties, demand effective strategies to minimize disruptions. This study introduces an innovative approach that integrates engineering management principles with modular design to prioritize risk mitigation and enhance robustness in manufacturing processes. From a systems engineering perspective, all manufacturing activities are perceived as interconnected components within a unified system. Leveraging the Axiomatic Design (AD) theory and the Design Structure Matrix (DSM) method, the study modularizes manufacturing process architecture to effectively curb risk propagation and manage system complexity. This study identifies the most optimal design as a pivotal architectural configuration, significantly improving the structural robustness and stability of the System of Interest (SOI). Empirical evidence supports this design’s capability to reduce complexities, thereby enhancing robustness within the broader system architecture. Notably, the proposed approach results in a substantial reduction in complexity, with the most optimal design exhibiting an approximately 82.79 percent reduction in work volume compared to the original design. Our research underscores the critical relationship between manufacturing and engineering management. Effective collaboration between these domains optimizes resource allocation, decision-making processes, and overall organizational strategy, leading to improved production processes and increased efficiency. Importantly, the study demonstrates a significant enhancement in modularization, resulting in elevated overall robustness in manufacturing processes. This highlights the proactive involvement of engineering management in the design phase to address production challenges, ultimately optimizing system performance. Thus, this research contributes to both practical applications and academic discourse by offering a novel approach to enhancing the robustness in manufacturing processes. By integrating engineering management principles and modular design strategies, organizations can fortify their processes against disruptions and effectively adapt to evolving circumstances.

2D Model of a Biomass Single Particle Pyrolysis—Analysis of the Influence of Fiber Orientation on the Thermal Decomposition Process

Understanding the influence of heat transfer on the pyrolysis process is crucial for optimizing industrial biofuel production processes. While numerous scientific studies focus on experimental investigations of pyrolysis using laboratory-scale devices, many neglect the essential role of thermal energy in initiating and controlling thermal decomposition processes. This study presents a transient two-dimensional numerical model of biomass single-particle pyrolysis, which includes the energy balance, mass conservation equations and pyrolysis gas pressure and velocity equations. The model employs explicit numerical methods to manage the high computational demands of 2D transient simulations, but is successfully validated with the use of experimental data found in the literature. The model reflects the heterogeneous structure of wood by using different thermal conductivity coefficients depending on the wooden fibers’ orientation. The results demonstrate the impact of fiber orientation on the heat transfer and thermal decomposition processes. The anisotropic properties of wood led to varied temperature fields and pyrolysis decomposition stages, aligning well with experimental data, thus validating the model’s accuracy. The proposed approach can provide a better understanding and lead to improvement in biofuel production processes, enabling more efficient and controlled conversion of biomass into fuel. By optimizing the pyrolysis process, it contributes to the development of sustainable energy preservation and regeneration methods, supporting a shift towards more sustainable fuel production patterns using renewable biomass resources like wood.

A Comprehensive Study on Adverse Reactions of Benzoyl Peroxide (BPO) in Dermatological Aesthetics Utilizing the FAERS Database.

Benzoyl peroxide (BPO) is widely used in dermatological aesthetics for treating acne and other skin conditions. However, its potential adverse reactions remain a concern. This study aimed to investigate the application of BPO in dermatological aesthetics, analyze its associated adverse reactions, and provide insights into patient safety. The study analyzed adverse reaction reports related to BPO in the Food and Drug Administration's Adverse Event Reporting System database from 2004 to 2024. Demographic characteristics, types of adverse reactions, and specific issues related to the novel drug EPSOLAY (5% microencapsulated BPO) were examined. The findings reveal that BPO users are predominantly female (74.18%), with a significant proportion falling within the 18-44 age group (37.45%). The most common adverse reactions involve skin and subcutaneous tissue disorders (36.34%), including skin swelling, pain, and burning sensations. Reports on EPSOLAY indicate adverse reactions such as erythema, pruritus, and skin exfoliation, but no tumor-related reports have been recorded. BPO usage in dermatological aesthetics is associated with various adverse reactions, primarily affecting the skin. The introduction of EPSOLAY has not altered the adverse reaction profile significantly. However, the risk of BPO decomposing into the carcinogen benzene under certain conditions necessitates enhanced patient education, improved production processes, and continuous post-marketing surveillance to ensure drug safety.

Application of science and technology to improve the competitiveness of traditional craft villages in the context of modernization and industrialization in Vietnam

Traditional craft villages are facing fierce competition in the context of globalization and industrialization. In order to survive and develop, the application of science and technology in the production and business process is an inevitable trend. This study aims to evaluate the effectiveness of the application of science and technology in improving production processes, enhancing product quality, expanding markets and sustainable development to increase competitiveness in the modern economic environment for traditional craft villages through a typical case study. The author used research methods such as analyzing available documents and in-depth interviews with artisans in the traditional lacquer craft village of Tuong Binh Hiep, a typical traditional craft village in Vietnam. The research results show that the application of science and technology, including automation, e-commerce and software production management, has helped traditional craft villages improve productivity, reduce costs and expand international markets. This has made an important contribution to enhancing the competitiveness of craft villages in the context of economic globalization and industrialization. However, to maintain the momentum of development and ensure sustainability in the future, long-term and comprehensive solutions are needed to optimize the effectiveness of science and technology while adapting to new global market challenges. From the opinions and analysis of the application of science and technology in Tuong Binh Hiep Lacquer Craft Village, a number of important conclusions can be drawn, showing the path of sustainable development of traditional craft villages in the context of integration. From the above issues, the objective of this study is to evaluate the effectiveness of applying science and technology to improve production processes, enhance product quality, and expand markets to help traditional craft villages in Vietnam increase their competitiveness in the modern economic environment.

An Optimized Method for Single Cell Cloning of Human CAR-T Cells based on FBS-coated Plates

T cell-based immunotherapy, especially chimeric antigen receptor (CAR)-T cells, has emerged as an appropriate approach for treating hematologic malignancies and is currently under investigation in clinical trials for solid tumors. Despite significant improvements in CAR-T cell production processes, the isolation and expansion of CAR-engineered T cells continue to pose significant challenges. The aim of this research is to provide a simple and cost-effective method for the isolation and expansion of human CAR-T cells. This novel concept applies coated FBS culture plates and focuses on enhancing viability and functionality to improve the adherence of suspended T cells. Methods: This study evaluated a two-dimensional (2D) culture technique for isolating the CAR-T cells that target prostate-specific membrane antigen (PSMA) utilizing matrices pre-coated with 0.2% glutaraldehyde and FBS. Jurkat cells were transduced with a lentiviral vector encoding the anti-PSMA CAR construct. FBS-coated and commercialized Matrigel-coated matrices were used for single-cell isolation and clonal expansion. Functional tests were conducted to assess the activation and proliferation of CAR-T cells and the IFN-γ release assay subsequent to cloning and expansion. Results: Transfection efficiency markedly improved, with 88.4% of Lenti-X 293T cells demonstrating GFP expression. Among the Jurkat cells, 57.1% showed GFP expression post-transduction, of which 34.1% showed surface expression of anti-PSMA CAR. Clonal expansion on the FBS-coated matrix proved effective, yielding 92.1% GFP-positive isolated cells. Functional assays demonstrated that CAR-T cells co-cultured with LNCaP cells exhibited significantly enhanced proliferation, activation (as indicated by CD69 and CD25 expression), and cytokine release assay (IFN-γ) compared with those co-cultured with DU 145 and mock cells. Conclusion: This new approach is efficient, economical, and scalable for isolating specific homogenous T cells and promoting their clonal proliferation and expansion. Future research should concentrate on optimizing culture conditions and testing this method in preclinical animal models to ensure its clinical applicability and efficacy.

The Role of Industry 4.0 in the Context of Economic Performance of Enterprises: A Literature Review

Abstract Research purpose. This literature review aims to comprehensively examine the role of Industry 4.0 in shaping the economic performance and sustainability of enterprises within Central European countries and provide a nuanced understanding of the impact of Industry 4.0 technologies on corporate performance in this regional context. Implementation of Industry 4.0 technologies, such as IoT devices, artificial intelligence, and robotics, enhances operational efficiency. This efficiency can lead to cost reductions, improved production processes, and streamlined supply chains, positively impacting the economic performance of enterprises. Increased innovation often translates to the development of new products and services, driving revenue growth and positively affecting economic metrics. Design / Methodology / Approach. Employing a literature review methodology, snowballing techniques, and bibliometric analysis, this study examines a wide range of scholarly articles, reports, and publications to discern patterns, current trends, and empirical evidence related to the nexus between Industry 4.0 adoption and corporate outcomes. Findings. The findings reveal the multifaceted influence of technologies such as automation, artificial intelligence, and the Internet of Things on key economic indicators, including revenue growth, cost efficiency, and profitability, across various industries. Additionally, the review highlights the current trends, identifies methodological approaches, and suggests potential avenues for future research. Originality / Value / Practical implications. This synthesis contributes valuable insights to the discourse on Industry 4.0’s implications for economic performance and sustainability, adds significant value to the understanding of the intersection between technological advancements and economic outcomes in the business landscape, offering a foundation for scholars, practitioners, and policymakers interested in navigating the transformative landscape of advanced technologies within the business context.

Cross-Laminated Timber Panels Produced by Low-Grade Yellow-Poplar Sorted by Nondestructive Evaluation

Abstract To manufacture and market a uniform and consistent product, the US lumber industry developed grading rules to classify their lumber. Visual grading is the most commonly applied grading system, although nondestructive evaluation (NDE) could be applied. Therefore, the objective of this research was to evaluate cross-laminated timber (CLT) panels produced from yellow-poplar (Liriodendron tulipifera) lumber sorted by NDE and compare their bending properties in the major direction to standard published panels by the American National Standards Institutes/The Engineered Wood Association (ANSI/APA) PRG 320-2019. Ten panels were produced with dimensions of 3.75 inches thick by 18 inches wide by 120 inches long. Flatwise bending, shear block, and cyclic delamination tests were performed following ANSI/APA PRG 320-2019. The results of the bending tests indicated that the calculated characteristic values using NDE-sorted lumber resulted in a 19 percent higher bending strength (Fb) than published values in ANSI/APA PRG 320-2019 for stress-rated lumber (E1 and E4) and 35 percent higher than visually graded yellow-poplar CLT panels reported by Azambuja et al. However, the modulus of elasticity (MOE) values (1.56 by 106 psi) were lower than those listed for E1 and E4 type panels. The adhesive evaluation showed delamination in some samples located in the outer areas of the panel, indicating that proper adhesion is possible with improvements in the panel production process used in the research. Overall, the results suggest potential opportunities to utilize yellow- poplar lumber that does not meet a visual structural grade category under Northeastern Lumber Association Manufacturers’ rules by classifying and sorting the lumber according to static MOE (MOEs) values assessed using NDE.

Value engineering як інструмент прийняття управлінських рішень в проєктах

The article examines the methodology of Value Engineering (VE) as a systematic approach to optimizing resources, improving efficiency, and making informed managerial decisions in project activities. The key aspects of VE are analyzed, with particular attention given to functional analysis, which allows identifying and evaluating the primary functions of objects while minimizing costs without compromising quality. The specific application of VE in large-scale industrial projects, requiring the integration of multidimensional approaches to achieve strategic goals, is considered. It is substantiated that VE ensures a balanced ratio between cost and functionality, which is critically important in the context of limited resources, dynamic market changes, and increased competition. The modern trends in VE development are highlighted, including the use of digital technologies and big data analysis that contribute to process automation, decision accuracy, and expanding the scope of VE applications. The integration of VE with other management approaches, notably Lean Six Sigma, is analyzed, demonstrating its synergistic effect through improving production processes, cost reduction, and quality enhancement. The importance of an interdisciplinary approach in forming teams capable of generating innovative solutions to create long-term value is proven. The historical context of VE development, starting from VE implementation in various sectors such as construction, industry, and technology, with a focus on cost optimization, functionality enhancement, and risk management, is reviewed. It is demonstrated that VE promotes efficient resource management, ensures the achievement of strategic and tactical goals, and enables organizations to create competitive products and services. Special attention is paid to the human factor, particularly leadership and teamwork, which contribute to solving complex problems through creative potential and multifaceted analysis. It is emphasized that the systematic implementation of VE is a powerful tool for the strategic development of organizations, not only ensuring effective management of costs and functions but supporting innovative growth, resilience, and long-term competitiveness in today’s market. Keywords: Value Engineering, managerial decisions, functional analysis, resource optimization, project management, decision-making, efficiency, strategic development, competitiveness.

Impact of artificial intelligence and knowledge management on proactive green innovation: the moderating role of trust and sustainability

PurposeIn this research, we seek to understand the effects of artificial intelligence (AI) and knowledge management (KM) processes in enhancing proactive green innovation (PGI) within oil and gas organizations. It also aims to investigate the moderator role of trust and sustainability in these relationships.Design/methodology/approachThis paper employs a quantitative analysis. Surveys have been gathered from the middle-line managers of twenty-four oil and gas government organizations to evaluate the perceptions of the managers towards AI, KM processes, trust, sustainability measures and proactive measures toward green innovation. Analytical and statistical tools that were employed in this study, including structural equation modeling with SmartPLSv3.9, have been used to analyze the data and to examine the measurement and structural models of this study.FindingsThe study results reveal a significant and positive impact of AI utilization, KM processes and PGI within oil and gas organizations. Furthermore, trust and sustainability turn out to be viable moderators affecting, and influencing the strength and direction of AI, KM and PGI relationships. In particular, higher levels of trust and more substantial sustainability commitments enhance the positive impact of AI and KM on green innovation outcomes.Practical implicationsUnderstanding the impact of AI, KM, trust and sustainability offers valuable insights for organizational leaders and policymakers seeking to promote proactive green innovation within the oil and gas industry. Thus, organizations can increase the efficiency of sustainable product development, process improvement and environmental management by using robust AI technologies and effective KM systems. Furthermore, fostering trust among stakeholders and embedding sustainability principles into organizational culture can amplify the effectiveness of AI and KM initiatives in driving green innovation outcomes.Originality/valueThis study extends the current knowledge by assessing the effect of AI and KM on proactive green innovation while accounting for trust and sustainability as moderators. Utilizing quantitative methods offers a nuanced understanding of the complex interactions between these variables, thereby advancing theoretical knowledge in the fields of innovation management, sustainability and organizational behavior. Additionally, the identification of specific mechanisms and contextual factors enriches practical insights for organizational practitioners striving for a practical understanding of the dynamics of the complexities of sustainable innovation in an AI-driven era.

Application of Resin Adsorption Process for Mitigating Protocatechuic Acid Cytotoxicity in Corynebacterium Glutamicum Fermentation

Recent advances in biotechnology have brought about revolutionary changes across diverse industries, with microbial fermentation technology playing a important role in the production of high-value compounds. Among these, Corynebacterium glutamicum has emerged as a key strain for efficiently producing biochemicals like amino acids. While fermentation processes using C. glutamicum are widely adopted in industries due to their high productivity and cost-effectiveness, the cytotoxicity of protocatechuic acid (PCA), a metabolic product generated during fermentation, has been a significant hindrance to productivity. PCA, known for its potent electrochemical antioxidant properties and wide application in industries such as food, pharmaceuticals, and cosmetics, poses challenges when accumulated at high concentrations during fermentation, inhibiting cell growth and reducing productivity. Therefore, this study aimed to explore the feasibility of applying adsorption processes to enhance PCA productivity in C. glutamicum. Building on previous research, we investigated an approach to effectively remove PCA from fermentation broth using specific ion exchange resins to reduce cytotoxicity and increase overall PCA production. In this study, we improved C. glutamicum strains and optimized production media to enhance PCA production capacity. Subsequently, we analyzed the impact of adsorption processes using ion exchange resins on alleviating cytotoxicity and improving productivity. Through experimentation, we optimized PCA adsorption efficiency and conditions using ion exchange resins, resulting in the production of 3.97 g/L of PCA in fermentation. This research is expected to contribute to the improvement of high-value biochemical production processes based on microbial fermentation.

Construction of epoxy composites with double alternating “rigid-flexible” structures: Curing kinetics and thermal/mechanical properties

The curing rate, post-curing modulus, and strength of epoxy resin are key performance indicators for epoxy resin-based composites. Optimizing these factors is essential for improving production processes and expanding practical applications. Functionalized rigid-flexible bilayer transition interfaces between nano-ZnO and epoxy resins were developed using chitosan (CS) and 1,2,3-Tris(glycidyloxy)propane (GTE). Their impact on the curing characteristics, rheology, and mechanical properties of the composites was investigated. The activation energies of pure EP and systems containing ZnO, ZnO-CS, and ZnO-CS-GTE were studied using non-isothermal calorimetry, obtaining 53.604 KJ/mol, 52.548 KJ/mol, 56.66 KJ/mol, and 51.482 KJ/mol, respectively. ZnO-CS-GTE showed a notably stronger promotional effect. Nano-ZnO inhibited gelation due to filler aggregation at 80 °C for 4 min, while ZnO-CS-GTE promoted gelation in just 2.6 min owing to its functional groups, achieving a modulus near 1 GPa after curing. Mechanical studies revealed that the tensile, flexural, and compressive strengths of the ZnO-CS-GTE system increased by 48.52 %, 32.67 %, and 45.01 %, respectively, with flexural and compressive moduli rising by 15.14 % and 15.76 %. The rigid-flexible interface enhanced the dispersion of epoxy resin and strengthened interfacial adhesion.

Cost and carbon-intensity reducing innovation in biofuels for road transportation

The transportation sector is the leading contributor to greenhouse gas emissions in the United States. Incentives for biofuel production in the form of direct subsidies and tradable performance standards have been substantial. Although research suggests such policies are less cost-effective at reducing emissions than an explicit carbon price, a dynamic assessment that accounts for innovation may differ substantially from static cost estimates. This study evaluates cost and carbon-intensity reducing innovation in the U.S. biofuel industry and estimates the value of social benefits for comparison with the observed level of policy support.Using multi-factor experience curves, this study finds that cost declines have been significant in ethanol production, with an estimated learning rate of 21.8%. However, learning in biodiesel and renewable diesel has been much less pronounced, at 3.23% and 1.33%, respectively. Reductions in carbon intensity are found to be largely related to feedstock choice rather than improvements in production processes. Based on the innovation rates identified in this study, current policy support for biofuels from stacked incentives is found to exceed the social benefits. This misalignment calls for a reassessment of biofuel policies to ensure they are economically and environmentally justified.

Intelligent Optimization and Impact Analysis of Energy Efficiency and Carbon Reduction in the High-Temperature Sintered Ore Production Process.

The coordinated optimization of energy conservation, efficiency improvement, and pollution reduction in the sintering production process is vital for the efficient and sustainable development of the sintering department. However, previous studies have shown shortcomings in the multi-objective collaborative optimization of sintering systems and the quantification of pollutant impacts. To address these, this paper proposes a multi-objective optimization method integrated with the NSGA-III algorithm and establishes an integrated system optimization model for sintered ore production and high-temperature waste heat recovery. The results demonstrate significant improvements: energy utilization efficiency increased by 0.67%, energy consumption decreased by 17.3 MJ/t, production costs were reduced by 11.45 CNY/t, and the emissions of CO2, SO2, and NOx were reduced by 0.464 kg/t, 0.034 kg/t, and 0.008 kg/t, respectively. Additionally, the study identified optimal configuration parameters and analyzed the quantitative impact of several key factors on multiple indicators. The results also show that reducing the water content of the mixture, decreasing the middling coal content in the fuel, and increasing the thickness of the material layer are effective strategies to reduce energy consumption and pollutant emissions in the sintering process. Overall, implementing these optimizations can bring significant economic and environmental benefits to the steel industry.

A IMPLANTAÇÃO DA METODOLOGIA 5S EM UMA CÉLULA DE MONTAGEM DE UMA INDÚSTRIA METALÚRGICA

The 5S methodology originates from Japan and is based on the application of five concepts: Seiri, Seiton, Seiso, Seiketsu, and Shitsuke. The 5S method focuses on organizing different sectors of a company based on organization, standardization, cleanliness, and discipline. It is a behavioral improvement program characterized by fostering teamwork, organizing the work environment, preserving employee well-being, maintaining productivity, and emphasizing cleanliness and organization. The objective of this work is to describe the implementation of the 5S methodology through the physical rearrangement in a medium-sized metallurgical industry. The research, characterized as a case study in a company in the interior of the state of São Paulo, is carry out applied and qualitative approach, presenting the implementation of a 5S improvement project through physical rearrangement. The choose of the 5S methodology is due to the fact that consolidating, enhancing, or creating an organizational routine facilitates the adoption of the studied concepts in a real case within a medium-sized industry that manufactures and sells fitness equipment. The implementation of the 5S program began with the approval of the management, achieved through awareness demonstrated by photographic evidence showing the current status of the company. This project’s implementation was necessary due to the evident problems arising from a lack of organization, cleanliness, and the conditions where the products were found in the sector. Its implementation led to a significant improvement in production processes in terms of quality, efficiency, and productivity, as well as enhancements in visual aspects and workplace conditions. It can be concluded that the 5S Program is a simple philosophy that is easy to implement, but its results entirely depend on the level of engagement of the people involved. Although challenges exist in the implementation process, particularly of a behavioral nature, technical improvements were also observed, resulting in a more positive work environment and a more efficient industrial routine. Despite still having many actions to be taken, it is considered that the 5S Program was successful in its implementation.

FORMATION OF STRATEGIC DIRECTIONS FOR THE USE OF ARTIFICIAL INTELLIGENCE IN THE ENTERPRISE TO ACHIEVE THE GOALS OF SUSTAINABLE DEVELOPMENT

Rapid artificial intelligence (AI) development opens new opportunities for enterprises to achieve sustainable development goals. This article summarizes the research results of applying AI to optimize production processes, reduce environmental impact, increase productivity, and strengthen social responsibility. The article aims to highlight the potential of AI for achieving enterprises' sustainable development goals and identify effective strategies for its application to increase economic efficiency, social responsibility, and environmental sustainability. A qualitative analysis of statistical data, official regulatory documents, books, and articles from accredited journals was used to achieve the goal. The obtained results showed that AI could be used to analyze production processes and forecast the demand for raw materials, optimize supply chains and reduce energy consumption, identify potential sustainability risks and develop strategies to prevent them, identify defects in production and control product quality in real-time, create personalized services and products for customers. The study highlights the importance of AI's ethical and safe use to ensure its positive impact on society and the environment. The practical value of the article lies in the systematic review of studies on the effects of AI on the sustainable development of enterprises. The obtained results can be used to improve production processes, increase enterprises' competitiveness, and promote sustainable development.

Harnessing the potential of deep eutectic solvents in biocatalysis: design strategies using CO2 to formate reduction as a case study.

Deep eutectic solvents (DESs) have emerged as green solvents with versatile applications, demonstrating significant potential in biocatalysis. They often increase the solubility of poorly water-soluble substrates, serve as smart co-substrates, modulate enzyme stereoselectivity, and potentially improve enzyme activity and stability. Despite these advantages, screening for an optimal DES and determining the appropriate water content for a given biocatalytic reaction remains a complex and time-consuming process, posing a significant challenge. This paper discusses the rational design of DES tailored to a given biocatalytic system through a combination of experimental screening and computational tools, guided by performance targets defined by solvent properties and process constraints. The efficacy of this approach is demonstrated by the reduction of CO2 to formate catalyzed by NADH-dependent formate dehydrogenase (FDH). By systematically analyzing FDH activity and stability, NADH stability (both long-term and short-term stability after solvent saturation with CO2), and CO2 solubility in initially selected glycerol-based DESs, we were able to skillfully guide the DES screening process. Considering trade-offs between experimentally determined performance metrics of DESs, 20% solution of choline chloride:glycerol in phosphate buffer (ChCl:Gly80%B) was identified as the most promising solvent system for a given reaction. Using ChCl:Gly as a co-solvent resulted in an almost 15-fold increase in FDH half-life compared to the reference buffer and stabilized the coenzyme after the addition of CO2. Moreover, the 20% addition of ChCl:Gly to the buffer improved the volumetric productivity of FDH-catalyzed CO2 reduction in a batch system compared to the reference buffer. The exceptional stability of the enzyme in this co-solvent system shows great potential for application in continuous operation, which can significantly improve process productivity. Additionally, based on easily measurable physicochemical solvent properties and molecular descriptors derived from COSMO-RS, QSAR models were developed, which successfully predicted enzyme activity and stability, as well as coenzyme stability in selected solvent systems with DESs.

Improved Production Process Map and Safety of Millet‐Based Fermented Beverage

ABSTRACTThe present study aimed to develop a standardized process map to produce a microbiologically safe and consumer‐acceptable Brukina beverage. Field interactions and observations were employed for the baseline data, while an improved production process was developed and utilized to produce a Brukina beverage. The microbial safety of the new approach was assessed by determining the total coliform, yeast and mold, as well as Staphylococcus aureus. A consumer preference test was conducted to validate the contribution of the improved and hygienic steps to the overall acceptability. The existing production processes for manufacturing Brukina beverage did not embrace Good Manufacturing Practices (GMPs) and as such, the resultant beverage was contaminated with coliforms and S. aureus. Moreover, the sensory characteristics including taste, mouthfeel, viscosity and overall acceptability, were negatively affected. The inclusion of food safety management practices and efficient production steps has a greater tendency of producing microbiologically safe and market‐acceptable fermented millet‐based beverages while safeguarding consumers’ health and satisfaction.