Integrated Production Process Research Articles

Effect of Offshoring on Exports of Firms in South Korea

This study empirically investigates the export-magnification effect of offshoring using a firm-level panel dataset from the manufacturing sector in South Korea. It estimates the impact of offshoring activities on export performance by examining intra-firm and arm’s length offshoring. The empirical evidence demonstrates the export-magnification effect of offshoring on both export market participation and export intensity. Particularly, the export-magnification effect of offshoring still exists among export entrants switching from non-exporters to exporters. Moreover, a greater export-magnification effect from intra-firm offshoring than from arm’s length offshoring is found using instrumental variable (IV) Tobit and probit models. This indicates that the vertical integration of production processes through intra-firm offshoring has a greater effect on export performance than international outsourcing to third parties.

Yeast enhancement by mass mating and selective pressure for the integrated production process of first and second-generation ethanol

Second-generation ethanol production is a worldwide applicable technology with the potential to replace fossil fuels and contribute to sustainability. The incorporation of second-generation ethanol production in Brazilian biorefineries, besides the technological advantages, adds to the abundance of feedstock derived from the sugar and alcohol industry itself. However, developing yeast strains that resist the inhibitory conditions of the new substrate, potentiated by cellular recycling, is extremely necessary. The aim of the present work was to develop yeast strains by hybridization and selective pressure techniques, with multi-tolerant profile for the fed-batch fermentation process using a mixture of molasses and bagasse hydrolysate as substrate. Therefore, the mass crossing technique was carried out involving five strains of Saccharomyces cerevisiae, previously selected, for demonstrating high tolerance to fermentation from mixed-must composed of lignocellulosic hydrolysate and sugarcane molasses. The culture resulting from the mass mating was followed by a selective pressure during 51 generations, generating enrichment of more tolerant strains. Employing microplate growth evaluation (optical density [DO] 600 nm), ten evolved isolates were selected, which were submitted to lab scale fermentation, simulating industrial conditions to the maximum. In the end, it was possible to highlight a lineage (C8E1-13T) presenting trehalose reserve content significantly higher than the other lineages evaluated, thus demonstrating the generation of an improved phenotype.

Current issues of industrial and technological cooperation in the EAEU countries

The subject of the study is the integration of production processes and technology exchange between Russia and the EAEU countries. The purpose of the work is to analyse the organizational and economic mechanisms of industrial and technological cooperation in the EAEU countries and to determine the conditions for increasing their effectiveness in the context of sanctions policy aimed at restricting the access of the Russian economy to foreign markets. The methodological basis of the research is a systematic approach, methods of induction, deduction, analysis and synthesis. The article considers examples of successful activities of joint ventures – one of the leading forms of industrial and technological cooperation between Russia and the EAEU countries, common in the automotive industry, aircraft manufacturing, energy and petrochemistry. Their creation stimulates economic growth, promotes industrial diversification and strengthens the international positioning of the region. The analysis revealed the following positive results from the organization of joint ventures between Russia and the EAEU countries: expansion of markets and increased production volumes, technology exchange and high innovation potential, employment generation and competence development. The problems that reduce the positive effect were also identified, in particular, the lack of harmonized standards, financial risks, managerial and cultural differences. Solving these problems requires combining the efforts of business and government agencies. The results of the study demonstrate the importance of creating and improving the efficiency of joint ventures in the EAEU countries, they can be used to adapt Russia’s economic strategy to new geopolitical conditions.

An interpretable operating condition partitioning approach based on global spatial structure compensation-local temporal information aggregation self-organizing map for complex industrial processes

Effective and interpretable partitioning of operating conditions in complex industrial processes is crucial for ensuring the efficiency and reliability of emerging integrated production processes. However, contemporary operation–condition partitioning models fall short in this domain for two main reasons. First, the parameters related to purely data-driven methods fail to involve physically meaningful semantics, resulting in suboptimal accuracy and interpretability. Second, there exists a spatial–temporal coupling interaction among process variables that reflects physically meaningful spatial–temporal correlations, further impeding effective interpretation. To address these challenges, an interpretable operation–condition partitioning method based on a Global Spatial Structure Compensation-Local Temporal Information Aggregation Self-Organizing Map is proposed. This approach formulates the operation–condition partitioning problem as a spatio-temporal feature extraction based on the operation–condition partitioning problem. First, a local separable aggregation (LSA) model based on the informer backbone is introduced to partition industrial variables into interpretable time-local groups. This ensures that the model can learn the underlying factors of the condition’s occurrence, thereby providing a reliable basis for interpretable root cause analysis. Next, a Global Spatial Feature Compensator (GSFC) is introduced that leverages the process mechanism knowledge and graph network to establish explicit spatial interrelationships among time-local groups in the LSA algorithm, thereby enhancing the model's inferential capabilities and security assurance. Subsequently, a spatiotemporal self-organizing map is designed to integrate the aforementioned spatial and temporal features, facilitating precise operation–condition partitioning decisions. Finally, the effectiveness and understandability of the proposed method are validated through comprehensive experiments in a real industrial application case study.

Advances in the co-production of biosurfactant and other biomolecules: statistical approaches for process optimization.

An efficient microbial conversion for simultaneous synthesis of multiple high-value compounds, such as biosurfactants and enzymes, is one of the most promising aspects for an economical bioprocess leading to a marked reduction in production cost. Although biosurfactant and enzyme production separately have been much explored, there are limited reports on the predictions and optimization studies on simultaneous production of biosurfactants and other industrially important enzymes, including lipase, protease, and amylase. Enzymes are suited for an integrated production process with biosurfactants as multiple common industrial processes and applications are catalysed by these molecules. However, the complexity in microbial metabolism complicates the production process. This study details the work done on biosurfactant and enzyme co-production and explores the application and scope of various statistical tools and methodologies in this area of research. The use of advanced computational tools is yet to be explored for the optimization of downstream strategies in the co-production process. Given the complexity of the co-production process and with various new methodologies based on artificial intelligence (AI) being invented, the scope of AI in shaping the biosurfactant-enzyme co-production process is immense and would lead to not only efficient and rapid optimization, but economical extraction of multiple biomolecules as well.

СУТНІСТЬ І ВИДИ ІТ У ПРОМИСЛОВОСТІ

The relevance of conducting scientific research dedicated to the development of Information Technology (IT) management in industry is determined by the direct impacts that this field exerts on the global economy, enterprise productivity, competitiveness of national industries, and overall societal quality of life. The contemporary landscape is rich with compelling reasons for conducting scientific research in the field of IT management in industry. Taking into account the analysis of the role and classification of IT, there are grounds to assert that the development of IT management is a key factor in the modern industrial environment. IT not only allows enterprises to increase productivity and reduce costs but also makes them more competitive and ready for market challenges. It has been proven that IT in industry differs from other sectors in its focus on automation and control, the use of the Internet of Things for data collection, active utilization of analytics and artificial intelligence for decision-making, integration of production processes, and supply chain management. These substantiated characteristics help enterprises achieve greater efficiency and resilience. Additionally, IT in industry contributes to the realization of the concept of sustainable development, where enterprises can more effectively utilize resources and reduce environmental impact. This is an important aspect in the context of modern requirements for sustainability and environmental responsibility. It is argued that IT in industry can facilitate the transition to a circular economy, where enterprises minimize waste and maximize resource reuse. This can be achieved through the implementation of resource management systems and material recycling. Overall, IT in industry plays a significant role in achieving efficiency, sustainability, and competitiveness for enterprises in the modern world. The provided classification helps managers understand which specific IT solutions can be beneficial for particular tasks and contributes to better resource management and strategic decision-making in industrial enterprises.

INSTITUTIONAL ASPECT INNOVATIVE MODERNIZATION OF AGRICULTURAL PRODUCTION

The institutional determinants of innovative modernization of agricultural production are substantiated.
 It is established that the transformational features domestic agricultural production are monoculture agricultural production, its structural deformation, increased degradation of land and water resources, growing dependence of agricultural producers on imported inputs for the production process, and a reduction in the number of rural workers and the population of rural communities.
 It is argued that transformational changes in agro-industrial production should be focused on large-scale modernization changes in the production process in terms of restoring land fertility, improving the quality characteristics of food products, expanding the existing export potential of agricultural products and the share competitive products. 
 It is established that the threats to the recovery of agricultural production are the narrowing of the domestic consumer market; reduction of the purchasing power of the population with a decrease in its number; reduction and blocking of exports of agricultural products; rising costs of material resources and rising costs of agricultural products and food prices.
 It is substantiated that institutional support for the innovative modernization of agro-industrial production should be accompanied by the formation of effective basic and special institutions and institutions that meet the criteria of systematicity when they are included in the hierarchical structure of norms and institutions of innovation.
 It is emphasized that the institutional support for innovative modernization should implement the following key tasks: ensuring a favorable investment climate for attracting financial resources to processing enterprises and the formation of local regional structures with low capacity for processing agricultural raw materials; creating conditions for the inclusion of agricultural producers in global value chains.
 Institutional interventions should be aimed at stimulating the diffusion and development of product innovations; supporting and shaping organizational structures for vertical and horizontal integration; supporting and shaping organizational frameworks for vertical and horizontal integration; and restructuring forms of state support for agricultural production.
 The strategic guidelines for the innovative modernization of agro-industrial production are defined: introduction of motives and incentives for structural changes in agricultural production, intensification of the development of small forms of management, integration of production processes, and use of competitive advantages.

The Potential of Dynamic Electrochemistry for Post-Processing of 3D-Printed Metal Parts

Creativity has no limits with 3D-printing of metals allowing the realisation of new geometries that cannot be provided by any other production method. Nevertheless it is a long way from an innovative idea to a 3D-printing based production process. The 3D-printed metal parts leave the printer with a significant amount of support structures fixed to the part, adhering metal powder and a surface roughness that is much too high for the technical application. While mechanical post treatment methods are mostly work, time and cost intensive they also cannot provide a proper finishing on sterically hindered parts and inner surfaces.Here chemically-electrochemically based methods, such as the Hirtisation® process, enable an integrated production process using the freedom in design of 3D-printing and additionally give an valid option for complete process automatisation that is required for standardisation and qualification of industrial serial production.While classical electro-polishing is failing to adress most of the issues resulting from the printing process, the use of dynamic electrochemistry, in terms of using current or potential pulses to finish the surface of the metal parts, provides a powerful toolbox for this application.This presentation will show the possibilities of dydnamic electrochemistry in terms of applying short current or potential pulses on 3D printed parts and will discuss the use of current pulses on different industrial relevant studies. A key factor for the success of such methods is a knowledge-based electrochemical tailoring of the actual current conditions at the metal surface and a deep understanding and adjustment of the material surface chemistry. Only by such an understanding of the different steps in the production chain and adjustment of these steps to each other, a constant and reproducible quality of the final products can be realised.

Bayesian optimization of HDPE copolymerization process based on polymer product-process integration

A framework for finding an optimal operating point of HDPE with the target properties is proposed. A bimodal high-density polyethylene (HDPE) copolymerization process is established to calculate molecular weights, dispersity, and predict properties. The process incorporates a probability-based description method with reactivity ratio to describe the content of monomer A/B and sequence distribution. A properties prediction model is established to predict glass transition temperature, melt temperature, melt index, and density. Bayesian optimization algorithm is utilized to optimize the process. This algorithm combines Gaussian process regression and an expectation improvement model to determine the optimal mass flow of feed and temperature of reactors. The objective function is modified using a penalty function to incorporate property constraints. The optimization goal is to maximize profits by identifying the optimal composition of feed and reactor temperature. Optimized bimodal HDPE copolymerization process leads to a significant increase in profit, with a 21.8 % improvement compared to the original process. The effect of melt index, is considered in determining the optimal operation range and maximizing profit. This provides valuable guidance for producing new grades of HDPE.

Synergies between Carnot battery and power-to-methanol for hybrid energy storage and multi-energy generation

Power-to-methanol (PtMe) technologies and Carnot batteries are two promising approaches for large-scale energy storage. However, the current low efficiency and inadequate profitability of these two technologies, especially concerning green methanol production, pose challenges for their industrial implementation. One solution is to integrate these two technologies to augment the material and energy utilization efficiency through dynamic operational coordination and multi-energy production. This study systematically investigates the synergies of integrating CO2 energy storage (CES) and PtMe for combined heating, power, and methanol generation, aiming to enhance system's efficiency and economic viability. In this context, a novel hybrid energy-driven polygeneration system (CES-PtMe) is developed, featuring a highly integrated methanol production process and a newly proposed CES configuration with heating input and output capabilities. Detailed system simulations assess its performance under steady state, while nonlinear programming models are formulated for optimal storage sizing and energy scheduling considering fluctuating renewable energy. Various scenarios are set to examine the techno-economic potential of the CES-PtMe system, using renewable data from Gansu, China as a case study. The results indicate that the system can achieve a high efficiency of nearly 80% with a renewable penetration exceeding 77%. By incorporating optimal energy scheduling throughout the year, the system shows economic viability in the context of the current fossil energy market. While it has a limited ability to meet user energy demands, the proposed system retains economic benefits compared to standalone technologies.

Ontology-based knowledge representation of industrial production workflow

Industry 4.0 is helping to unleash a new age of digitalization across industries, leading to a data-driven, interoperable, and decentralized production process. To achieve this major transformation, one of the main requirements is to achieve interoperability across various systems and multiple devices. Ontologies have been used in numerous industrial projects to tackle the interoperability challenge in digital manufacturing. However, there is currently no semantic model in the literature that can be used to represent the industrial production workflow comprehensively while also integrating digitalized information from a variety of systems and contexts.To fill this gap, this paper proposed industrial production workflow ontologies (InPro) for formalizing and integrating production process information. We implemented the 5 M model (manpower, machine, material, method, and measurement) for InPro partitioning and module extraction. The InPro comprises seven main domain ontology modules including Entities, Agents, Machines, Materials, Methods, Measurements, and Production Processes. The Machines ontology module was developed leveraging the OPC Unified Architecture (OPC UA) information model. The presented InPro ontology was further evaluated by a hybrid combination of approaches. Additionally, the InPro ontology was implemented with practical use cases to support production planning and failure analysis by retrieving relevant information via SPARQL queries. The validation results also demonstrated that using the proposed InPro ontology allows for efficiently formalizing, integrating, and retrieving information within the industrial production process context.

СИСТЕМНО-СТРУКТУРНИЙ АСПЕКТ ВИБОРУ ЕЛЕМЕНТІВ РОБОТОТЕХНІЧНИХ СИСТЕМ

The article is devoted to solving the problems of technological preparation of robotic production. Currently, the creation of robotic systems has acquired the status of a completely independent technological task, which is solved on the basis of a significant reduction in the terms of technological preparation of production and the creation of fundamentally new software and technical tools. The growth of technical equipment and the technical integration of production processes under the conditions of robotization, which is related to this, have a significant impact on the selection criteria of individual structural elements of robotic systems. In contrast to the created traditional production systems, in which the main structural elementsimplemented in the relevant design and technological solutions were only machine tools, technological equipment and cutting tools, in robotic systems the range of structural elements is significantly expanded: the robotic systems, in addition to thespecified structural elements, contain technical means of control, industrial robots, transport equipment, technical means of storage, etc. It is quite obvious that now the methodology of creating robotic systems should go beyond solving only technical problems and should include a comprehensive and deep study of technology, management and organization, which are not only interdependent with related technical problems, but also directly affect their correct solution. The analysis of the latest researches and publications, which were devoted to the robotization of production, allows us to conclude that the problem of solving the taskof a justified choice of structural elements of robotic systems is currently not formalized and not solved. The article offers methodological bases for the formalization of the process of selecting structural elements of robotic systems, taking into account the specific limitations and production conditions. The proposed methodology makes it possible to systematically cover not only all technical solutions already existing in production, but also to find those, the creation of which is possible and, in some cases, even expedient; find existing technical solutions that are already implemented directly in production or that are provided with technical documentation, which will help minimize search time and prompt selection of ready-made solutions.

Production Scheduling Optimization of Garment Intelligent Manufacturing System Based on Big Data.

In order to improve the efficiency of cloth laying and cutting integrated production process, this article proposes a method of optimal scheduling of cloth laying and cutting garment production system process based on big data and genetic algorithm. The chromosomes in the algorithm are expressed by real strings. The method of bit string crossover and mutation is used to solve the premature problem of the algorithm. The experimental results show that the actual cutting time of the plan is 736 min, and the total idle time is 113 min. The idle time occurs in processes 25, 28, 34, 35, and 31, respectively. The cutting time of the plan arranged by the genetic algorithm is 627 min, and there is no idle time. Conclusion. This method can effectively solve the optimal scheduling problem of the cloth laying and cutting production process.

Integrated process for the production of indigo and indirubin in an anaerobic environment at laboratory and pilot level

The production of indigo commonly requires an oxidation step in which indoxyl is oxidized to indigo. There are no investigations into the effect of oxygen transfer on indigo production. Herein, increased yield and purity of indigo were found with increased reaction volume, indicating a negative effect of aeration on indigo production in alkali conditions. Therefore, the condensation of indoxyl in the presence and absence of oxygen was assessed. The results showed consumption of indoxyl in aerobic conditions to be faster than in anaerobic conditions, while the utilization rate of indoxyl into indigo and indirubin was lower. In order to improve indoxyl utilization, the production of indigo/indirubin in an anaerobic environment was evaluated in a nitrogen gas environment during the indoxyl condensation step. The yield and purity of indigo were 4.5 mg/g and 43.5%, respectively, which were 1.1 and 1.5 times higher than those of the traditional process. Moreover, the alkaline condition under the nitrogen atmosphere provided a high production of indirubin. The cost of raw materials was found to be the most important factor for determining the cost of indigo production and could be reduced by improved indican utilization. Based on these findings, an anaerobic indigo/indirubin integrated production process was proposed for a pilot scale adaptation.

Direct conversion of cellulose to l-lactic acid by a novel thermophilic Caldicellulosiruptor strain

BackgroundConsolidated bioprocessing (CBP) of lignocellulosic biomass to l-lactic acid using thermophilic cellulolytic/hemicellulolytic bacteria provides a promising solution for efficient lignocellulose conversion without the need for additional cellulolytic/hemicellulolytic enzymes. Most studies on the mesophilic and thermophilic CBP of lignocellulose to lactic acid concentrate on cultivation of non-cellulolytic mesophilic and thermophilic bacteria at temperatures of 30–55 °C with external addition of cellulases/hemicellulases for saccharification of substrates.Resultsl-Lactic acid was generated by fermenting microcrystalline cellulose or lignocellulosic substrates with a novel thermophilic anaerobic bacterium Caldicellulosiruptor sp. DIB 104C without adding externally produced cellulolytic/hemicellulolytic enzymes. Selection of this novel bacterium strain for lactic acid production is described as well as the adaptive evolution towards increasing the l-lactic acid concentration from 6 to 70 g/l on microcrystalline cellulose. The evolved strains grown on microcrystalline cellulose show a maximum lactic acid production rate of 1.0 g/l*h and a lactic acid ratio in the total organic fermentation products of 96 wt%. The enantiomeric purity of the l-lactic acid generated is 99.4%. In addition, the lactic acid production by these strains on several other types of cellulose and lignocellulosic feedstocks is also reported.ConclusionsThe evolved strains originating from Caldicellulosiruptor sp. DIB 104C were capable of producing unexpectedly large amounts of l-lactic acid from microcrystalline cellulose in fermenters. These strains produce l-lactic acid also from lignocellulosic feedstocks and thus represent an ideal starting point for development of a highly integrated commercial l-lactic acid production process from such feedstocks.

Chitosan Production by Fungi: Current State of Knowledge, Future Opportunities and Constraints

Conventionally, the commercial supply of chitin and chitosan relies on shellfish wastes as the extraction sources. However, the fungal sources constitute a valuable option, especially for biomedical and pharmaceutical applications, due to the batch-to-batch unsteady properties of chitin and chitosan from conventional ones. Fungal production of these glycans is not affected by seasonality enables accurate process control and, consequently, more uniform properties of the obtained product. Moreover, liquid and solid production media often are derived from wastes, thus enabling the application of circular economy criteria and improving the process economics. The present review deals with fungal chitosan production processes focusing on waste-oriented and integrated production processes. In doing so, contrary to other reviews that used a genus-specific approach for organizing the available information, the present one bases the discussion on the bioprocess typology. Finally, the main process parameters affecting chitosan production and their interactions are critically discussed.

A scalable, integrated downstream process for production of a recombinant measles virus-vectored vaccine

Purification of very large and complex, enveloped viruses, such as measles virus is very challenging, it must be performed in a closed system because the final product cannot be sterile filtered and often loss of virus titer and poor product purity has been observed. We developed a purification process where the clarified and endonuclease treated culture supernatant is loaded on a restricted access chromatography medium where small impurities are bound and the virus is collected in the flow-through, which is then concentrated, and buffer exchanged by ultra/diafiltration. Up to 98.5% of host cell proteins could be captured by direct loading of clarified and endonuclease treated cell culture supernatant. Reproducible process performance and scalability of the chromatography step were demonstrated from small to pilot scale, including loading volumes from 50 mL up to 9 L. A 10-fold virus concentration was achieved by the ultrafiltration using a 100 kDa flat-sheet membrane. The order of individual process steps had a large impact on the virus infectivity and total process yields. The developed process maintained virus infectivity and is twice as fast as the traditional process train, where concentration is performed before loading on the chromatography column. Capturing impurities by the restricted access medium makes it a platform purification process with a high flexibility, which can be easily and quickly adapted to other vectors based on the measles virus vector platform.

Modeling and simulation of a fixed bed gasification process for thermal treatment of municipal solid waste and agricultural residues

This work aims to develop a numerical simulation model of the combined and integrated production process of combustion and gasification, for a synthesis gas production system (SYNGAS), fed with municipal solid waste (MSW), agricultural and forestry waste. For this purpose, the EMSO software (Environment for Modeling, Simulation, and Optimization) was used in the formulation of a fixed-bed gasifier with the co-current flow. The model is developed based on mathematical calculations of partial differential equations, being one-dimensional (1-D), and considers chemical kinetics, diffusivity, and heat and mass transfer phenomena. Its validation is based on data available in the literature (variables, initial and operational conditions). As a result, a simulation of a gasifier was obtained, capable of predicting the production of Syngas, having a good correlation with the published experimental results. The general data obtained were in agreement, with high consistency for the analysis of the pilot plant in the laboratory and semi-industrial scale for solid waste processing. However, detailing the behavior of the gasifier is essential to maximize the efficiency of the process. For that, the numerical simulation tested several operational parameters, such as air–fuel ratio and gasifier temperature for instance.

Optimization, modelling and simulation to scale-up the production of rice bran extract and defatted rice bran

Rice bran is the source of rice bran oil, but much of it is used as livestock feed without being extracted for oil. Some food industries utilize the stabilized rice bran as a source of fiber, protein, and cooking oil. It contains lipase that catalyzes triglyceride hydrolyzation into glycerol and fatty acids, which leads to rancidity. A stabilization process must therefore be introduced to increase oxidation resistance in rice bran and oil hydrolysis. Defatted rice bran still contains protein, fiber, vitamins, and minerals. There has not been much research on integrated production process of crude rice bran oil and defatted rice bran. This research aimed to study the procedures to optimize, model, and simulate, generate Process Engineering Flow Diagram (PEFD). The phases in this study included laboratory-scale extraction with rice bran feed capacities of 10g, 25g, 100g, dan 500g; optimization using mathematical computations, simulations of mass-balance scale up and generation of PEFD from the pilot plant of 5kg rice bran capacity. The results of this research, including optimization, modelling, and simulation showed that to increase production scale from a number of raw materials of 57.690g to 5kg in a single batch required 5kg rice bran and 23.121kg n-hexane and produced 0.671kg oil and 4.121kg defatted rice bran, 13.212kg of reusable n-hexane and this study also provided a PEFD of the rice bran oil production process for a 5 kg rice bran capacity.

Using axiomatic design principles for the development of a device to measure the positioning error of an industrial robot

Robots are part of the integrated production process, being widely used in manufacturing processes, including the positioning of parts. One of the factors that influences the accuracy of the products to be machined is related to the errors of positioning the workpiece at each stage of manufacture. To determine the amplitude and the medium value of the positioning error, we used axiomatic design to develop a device capable of measuring positioning errors. The result was a constructive solution for a device capable of taking the positioning data of the end of the robot arm along three axes of a spatial coordinate system. In this way, data are recorded using dial comparators positioned on existing channels in the three walls corresponding to the corner of a cube-shaped box. Statistical processing of measurement results should provide information on the positioning accuracy of a workpiece by an industrial robot.