Industrial Production Processes Research Articles

Transfer of synthesis, logistic and recycling processes in nature to industrial processes

In biological structures, where logistic, synthesis and recycling processes take place, one finds compartments for these different processes. These are arranged in a specific order so that there is optimal synthesis, transformation, logistics, freedom from interference and flexibility of action. Between the compartments run fast transport systems, microtubules or roads, along which information, molecules etc. are transported. Because production, transport and recycling processes run in every living cell, or numerous macroscopic logistical pathways between cells have been evolved and optimized, various biological functional and design structures can serve as models for industrial production processes. In the context of biointelligent production concepts, input and output of material, energy and information, resource-optimized biological production processes and recycling of materials are interesting aspects with transfer potential. In this paper, numerous examples from nature and approaches to transfer the principles to industrial production processes are presented. Some of them have already proven their effectiveness and efficiency, others have yet to do so. The hypothesis is that further optimization potential can be tapped if principles that have been successfully applied for millions of years are transferred to human processes that have only been developed over decades or centuries.

Advances in volatile organic pollutant capture and adsorption degradation treatment technologies

With the continuous development of industry, the emission of volatile organic compounds (VOCs) continues to increase, and the pollution problem becomes increasingly serious. For example, in industrial production processes such as papermaking and traditional Chinese medicine extraction, low-content and complex volatile organic compounds will be produced, which will affect the factory environment. This article introduces the development and research status of VOCs sampling and treatment technology in recent years, explains the advantages and disadvantages of adsorption method, absorption method, membrane separation method, catalytic combustion method, biodegradation method, and low-temperature plasma technology application, and looks forward to the future development trends in this field.

Hybrid Unsupervised Learning Strategy for Monitoring Industrial Batch Processes

Industrial production processes, especially in the pharmaceutical industry, are complex systems that require continuous monitoring to ensure efficiency, product quality, and safety. This paper presents a hybrid unsupervised learning strategy (HULS) for monitoring complex industrial processes. Addressing the limitations of traditional Self-Organizing Maps (SOMs), especially in scenarios with unbalanced data sets and highly correlated process variables, HULS combines existing unsupervised learning techniques to address these challenges. To evaluate the performance of the HULS concept, comparative experiments are performed based on a laboratory batch process.

USE OF MICROWAVE RADIATION FOR EFFECTIVE PURIFICATION OF WASTEWATER FROM ORGANIC COMPOUNDS

This article is devoted to the problem of using microwave radiation as a potentially effective method of cleaning wastewater from organic compounds. The problem of cleaning wastewater from organic contaminants in the food industry requires highly effective methods since protein compounds in wastewater can cause environmental hazards and complicate the cleaning process. The purpose of the work was to investigate the effectiveness of using microwave radiation to purify wastewater from organic compounds, particularly protein impurities, and to establish the possibilities of this method for improving the process of water purification in the food industry. The article mainly examines the use of microwave radiation for this purpose and analyses its effect on proteins usually present in wastewater from the food industry. Experimental studies have shown the possibility of adequate wastewater treatment using microwave radiation. The advantages of using microwave heating, as well as its speed and regulation accuracy, are analysed, making this method attractive for use in wastewater treatment and other industrial production processes. The study includes an analysis of microwave radiation's effect on proteins commonly present in wastewater from the food industry. The research methodology involves modelling the composition of wastewater and using a microwave oven to process protein solutions. The results of the experiments demonstrate the possibility of adequate wastewater treatment using microwave radiation, which opens up prospects for further use of this method in industry and environmental protection. The results indicate the success of using microwave radiation to purify wastewater from organic compounds, notably protein pollution.

МОНИТОРИНГ ИННОВАЦИОННОГО РАЗВИТИЯ ВЫСОКОТЕХНОЛОГИЧНЫХ ПРОИЗВОДСТВ

The United States ranks first in terms of the number of space launches. This breakthrough was caused by the launch of numerous remote sensing satellites. Comparing the global space economy of states, it is noted that the United States spends more money on this than other countries. Russia spends significantly less money. The United States continues to be the world’s largest investor in space programs, followed by China, Russia, the EU and Japan. Monitoring 2020–2022 It shows that the results of economic activity in the space industry, taking into account macroeconomic conditions, are their practical implementation in the production processes of high-tech industries of the space industry. They specifically reflect the real economic state of the space industry, which is based on the reasonable attraction of a significant amount of private investment invested in space scientific and technical PPP projects, which makes it possible to dynamically develop the space industry

Determination of the influence of the electrohydraulic effect on succulent plant raw materials

The study is aimed at assessing the influence of the electrohydraulic effect on succulent plant raw materials. Experimental data show that the use of electrohydraulic effect helps to increase the juice yield of raw materials due to the active effect on the protoplasm of cells and increasing their permeability. It has been established that the optimal processing mode using the electrohydraulic method at 7 kV and 1 μF provides maximum juice yield, especially for pulp with a liquid consistency, such as grape pulp. Microscopy results revealed changes in cell structure, confirming the effectiveness of this treatment method. The developed experimental electrohydraulic effect installation takes into account the scientific findings obtained and represents a promising means for processing grape pulp in a stream. Thus, the study confirms the significance and potential of using the electro-hydraulic method to improve the production process in the food industry.

Analysis of the use of hydraulic drives in the automotive industry

The article is devoted to the study of the use of hydraulic drives in the automotive industry, which is a promising direction in engineering practice. The paper examines the global implementation of hydraulic drives in various vehicle systems, such as steering, braking, suspension and clutch mechanisms. The main attention is paid to the analysis of the advantages and disadvantages of hydraulic drives in the automotive industry. The study includes a conclusion about the operating efficiency of hydraulic drives, their reliability, durability and economic feasibility. The results obtained during the study can be useful in choosing optimal solutions for the use of hydraulic drives. This can help improve the safety and performance of vehicles, as well as improve production processes in the automotive industry. The article represents a special contribution to the development of new technical solutions in the automotive industry and can serve as a basis for further research in this area.

Using Information Technologies to Manage Printing Production: Integration and Optimisation Based on the System-Process Approach

Taking into account the characteristics of the system-process approach, the study considers the importance of the use of information technologies in the management of the production of printed products. The information structure is considered to be an organised system for collecting, processing, storing and distributing the necessary information required for management decision making. This structure aims to ensure that the information is available, accurate and relevant, which is required to manage the production process. By considering the interrelationships of all elements of the production process and establishing optimal information exchange procedures to achieve management objectives, the system-process management approach is used. This helps to improve coordination between the company’s departments. It also reduces production time and increases the level of quality and productivity. A wide range of tasks, from order processing and preparation of production documentation to control and analysis of production results, are involved in the creation of a company’s management information structure. Production planning, customer invoicing and scheduling of production processes are also important aspects of management. They help to ensure an efficient production process and customer satisfaction. A comprehensive system of information and management components is used to create and use an information structure for managing the production of printed products based on a system-process approach. These components include information technology, production process management systems, and logistics process management systems. The aim is to automate and optimise production processes in the printing industry. In particular, it is possible to optimise the processes of interaction between customers and producers through the development of print production using information technologies and automated management systems. This helps to improve the quality of the service and to make management decisions on a more informed basis. The study notes that effective operational management of receiving orders in the printing industry is critical to running a successful business. Key elements of this process include the proper collection and management of information. Initial data plays an important role in order acceptance and fulfilment, such as customer requirements, requirement structure, financial conditions and order volume. This information enables you to communicate effectively with customers, understand their needs, and estimate profitability and cost to produce. Key aspects of production management include responding quickly to changes in demand, optimising processes and fulfilling orders on time. In order to maintain the efficient functioning of the company, it is important that the data is current, updated and accessible to all parties involved in the process. It is concluded that a properly organised information structure based on the system-process approach is an important component of successful print production management. It contributes to the optimisation of work processes and increases the productivity of the company.

Integrating production and maintenance planning in process industries using Digital Twin: A literature review

Among the Industry 4.0 technologies transforming manufacturing environments, the Digital Twin (DT) technology is gaining attention as a driver for improving manufacturing performance and a platform to enhance collaboration. While the advantages of leveraging DT for supporting decision-making in production planning and maintenance planning are recognized, research taking an integrated perspective is scarce. In addition, besides the growing trend, recent studies highlight the limited adoption of DTs in process industries, emphasizing the necessity to address the unique features of their production processes. Through a literature review, this paper points out the main obstacles encountered during the implementation of DT in process manufacturing industries, as well as shows the research gap in exploiting DT to support the integration of decisions concerning production and maintenance and underscores the need for further investigation in this direction to discover its full potential.

Improved quality control and sustainability in food production by machine learning

In recent years, the food industry has faced a number of complex challenges related to both quality control and sustainability. Ensuring consumer safety and satisfaction remains a cornerstone of the food industry, supported by stringent standards that address the risks of contamination and spoilage. However, variability in raw materials, processing techniques and storage conditions are just some of the factors that affect quality in the food industry. To manage this high variability, it is essential to analyse the production process and factors that most influence food quality, aiming to predict and minimise food waste, thereby ensuring a sustainable process. This convergence of quality control and sustainability goals provides fertile ground for machine learning applications. By improving defect detection, process optimisation, resource allocation and predictive maintenance, these models help to improve product quality and reduce environmental impact. This article aims to explore the various applications of machine learning models in the food industry, where the variability of raw materials and the difficulty of controlling production and environmental factors challenge the use of traditional methods. The quality control and sustainability of an industrial corn cakes production process is used as a case study.

Integrating extended reality in industrial maintenance: a game-based framework for compressed air system training

In industrial environments, maintenance technologies developed under Industry 5.0 are important to ensure trouble-free production and reduce downtime. Compressed Air Systems (CASs) are an integral part of industrial production processes and require competent and correct maintenance. Maintenance personnel should be equipped with continuous and up-to-date training and their knowledge should be tested. There is a significant gap in the field of interactive educational games to improve the technical skills of the care staff, especially in the field of CAS. This research proposes a theoretical framework for a game based on Extended Reality (XR) technologies adapted for CAS maintenance training. The game leverages the trio of Augmented Reality (AR), Virtual Reality (VR), and Mixed Reality (MR) to provide immersive and interactive learning encounters aimed at improving technical proficiency, problem-solving skills, and safety awareness among maintenance workers. The aim is to take advantage of the rewards of game-oriented learning, such as enhanced user engagement and knowledge absorption, to increase the effectiveness of training. In this context, the CAS game framework was created with three frameworks: education, game, and CAS. The study concludes by highlighting the potential benefits, research areas, and technologies that underpin the proposed structure.

Optimization and Efficiency Improvement of Robot-based Industrial Production Process

Optimization and Efficiency Improvement of Robot-based Industrial Production Process

Use of multi-agent system for industrial production control

This paper describes specific implementation of Asset Administration Shell technology used for an industrial distributed control system. The base of this control system is a multiagent system of digital twins which was created by AAS. This multiagent system was developed for a specific platform CP Factory (mainly based on Simatic PLC) but the implementation is y portable to each common platform. Digital twin of several types of components of typical industrial production process are described in this paper with the implementation of active and passive administration shell. The main focus is on describing the way of integrating digital twins into the production system and the necessary SW tools. Industry 4.0 language was used as a common communication protocol as well as OPC UA and MQTT.

Study of particulate emissions when using special wires for underwater welding

The article describes the study to evaluate the emissions to atmospheric air of airborne nano- and microparticles generated during underwater welding in seawater from Ajax Bay (Sea of Japan) using special wires and coated electrodes. The most commonly used underwater industrial production processes were selected: semi-automatic (mechanized) underwater welding with a welding wire, manual welding with electrodes, and semi-automatic (mechanized) underwater cutting with a welding wire for cutting. An aerosol particle counter was used to determine the mass concentration of fine aerosol particles in the air of the working area above the aquarium. The highest number of suspended particles in the atmospheric air was observed in the process of underwater welding with a welding electrode. Comparing the welding wire and the welding electrode for underwater welding, it can be concluded that the welding wire is less dangerous for people, which is confirmed by the lower amount of suspended particles emitted into the atmospheric air during its use.

The role of primary recrystallization microstructure in secondary recrystallization of Goss grain in industrial low-temperature grain-oriented silicon steel

Low-temperature grain-oriented silicon steel has very excellent magnetic properties along the rolling direction. During industrial mass production, slight process fluctuations can directly lead to variations in the primary recrystallization microstructure, which in turn can have a dramatic effect on the magnetic properties of the final product. However, it is unclear how different primary recrystallization microstructures influence the magnetic properties of the industrial final products, making it difficult to further optimize the production process of industrial low-temperature grain-oriented silicon steel. Therefore, it is very important to clarify the transformation behavior of different primary recrystallization microstructures and their influences on the transformation behavior of inhibitors during the high-temperature annealing process. Here, we analyzed the differences between two primary recrystallization microstructures in terms of microstructure homogeneity, Goss grain characteristics and texture characteristics and investigated the secondary recrystallization behavior of Goss grains and the dissolution behavior of inhibitors in these two primary recrystallization microstructures during high-temperature annealing. Based on the results of this work, it was found that a finer primary recrystallization microstructure could be more favorable to the formation of a sharp Goss texture, which in turn could significantly improve the magnetic properties, and in addition, new insights into the transformation behavior and the grain boundary pinning behavior of inhibitors during high-temperature annealing process were established. The results of this work could help to further improve the understanding of the actual role of inhibitors during high-temperature annealing and could also provide new ideas for further improving the industrial production process.

Methodological proposal for the transfer of industrial manufacturing processes in a transnational firm: A China-Mexico particular case

This paper addresses the problem of the transfer of international production processes in the manufacturing industry and proposes a methodology to identify the essential activities required for it. The bibliographical research reveals the problems associated with the lack of an objective methodology in the management of projects for the transfer of processes between countries. In order to solve this problem and in the absence of a specific methodology, a case study was developed, based on the transfer of the Zoned Amplified production line of the Carrier company, from China to Mexico. In order to obtain a solid and complete methodology, different authors and proposed approaches for manufacturing transfers were compared, collecting the relevant information. As a result, a methodology composed of seven steps is proposed, either: factors for implementation, initiation of transfer documentation, design of the transfer plan, design for manufacturing, technology transfer and installation requirements, validation process and, finally, launch. This contributes to the industry in general, a practical and effective guide to address international process transfer projects, associated with specific standards in some cases, thereby overcoming the associated challenges and guaranteeing success in their execution.

Determination of Thermotolerant Yeast Population in Dairy Products

Thermotolerant yeasts constitute a critical indicator for the effective management of product quality, food safety, and production processes in the dairy industry. This study aims to investigate the presence of thermotolerant yeasts in diverse dairy products within the context of Turkiye. In this study, pH and thermotolerant yeast properties of Turkish white cheese, butter, cream (Kaymak), and Tulum cheese were investigated. Thermotolerant yeast counts in butter samples ranged between 4.30 and 4.82 log CFU/g, with pH values ranging from 4.91 to 6.68. Thermotolerant yeast counts of Tulum cheese, white cheese and cream samples were <2 log CFU/g. The pH values of cream and Tulum cheese were ranged from pH 5.07-6.79 and pH 4.91-6.68, respectively. The mean pH value for white cheeses was 4.98. As a results, thermotolerant yeast counts of Tulum cheese, white cheese and cream samples were below the detectable value; however, a high number of thermotolerant yeasts were determined in butter samples. In conclusions, these findings offer valuable insights for evaluating the microbiological quality of different dairy products, aiding producers in enhancing safety and quality for consumers.

Implementation of generative pretrained transformer (GPT) models in industrial practice and production process

This paper provides an insight into the application of generative pretrained transformer (GPT) models, such as GPT-4 developed by OpenAI, in the field of industrial practice and manufacturing process. The article describes the capabilities of these models, such as natural language understanding and generation, and their role in automating and personalizing services directly in manufacturing industry practice. The work presents concrete examples of how GPT models help automate production processes, support the development of new types of software and services, and facilitate work with artificial intelligence in the fields of robotics and machine control. The article also discusses possible challenges and ethical issues related to the use of these models. It also includes a discussion of the future development and potential of these technologies.

Design of Internet Of Things (IoT) trainer kit with Multi Communication

Industry 4.0, or the Fourth Industrial Revolution, is a recent technological development that has significantly changed the industrial production process. One of the keys to this change is the Internet of Things (IoT), where the role of humans is likely to diminish and be replaced by machines. Aligning the workforce with IoT is important, but creating a qualified workforce is a challenge. IoT learning modules are needed to help students understand IoT concepts. The purpose of this research is to design an Internet of Things kit module with Radio communication with LoRa SX1278 Ra-02. The research stages start from literature study, hardware design, software design and overall testing. Module testing is done by sending DHT11 sensor data using LoRa SX1278 Ra-02 and monitored in Thingspeak. From the test results that have been carried out, it can be concluded that sending using LoRa (Long Range) technology is influenced by distance and obstacles. At a distance of 40 to 230 metres, communication between the Lora Transmitter and Lora Receiver is successful, which shows that LoRa technology is able to overcome communication distances in that range. However, at a distance of more than 230 metres to 300 metres, data transmission can still be done by the Lora Transmitter, but the data cannot be received by the Lora Receiver, indicating a bottleneck in communication.

Holistic Assessment of Decarbonization Pathways of Energy-Intensive Industries Based on Exergy Analysis

The decarbonization of the industrial sector plays a crucial role in a successful energy transition. This transformation is very costly and complex, as many of the existing production processes and plants will have to be partially or completely replaced to reduce carbon dioxide (CO2) emissions. This raises questions about how significant reductions in CO2 emissions resulting from decarbonization will affect the use of resources to produce a certain product and the overall value of sustainability. This article considers the relationship between CO2 reduction and the impact on the resource efficiency of an industrial production process. For this purpose, a methodology was developed that holistically assesses the decarbonization pathway of an industrial sector. This holistic assessment takes into account the energy carriers, raw materials, and auxiliary and construction materials used for the operation and building of the significant plant components and summarizes them as a total use of resources. For this purpose, the use of resources is represented by the thermodynamic quantity exergy, which takes into account both the energy and material components of a production process. The energy and material streams in a production process are balanced by applying exergetic analysis. This methodology is used for current state-of-the-art and future decarbonized production processes in order to quantify the effects of the decarbonization process. By comparing the calculated resource efficiencies, the thermodynamic impact on the sustainability of decarbonization paths can be set in relation to the amount of CO2 saved. For validation, the developed methodology is applied to a conventional and a decarbonized ammonia production process. The conventional production route represents the production of ammonia by methane steam reforming, and the decarbonized production route is represented by synthesis gas production via water electrolysis and an air separation unit. The resource efficiency of the conventional ammonia production route, taking into account the energy sources, raw materials, construction materials, and auxiliary materials used, is 59%, producing a total of 1539 kg of CO2 emissions per ton of ammonia. The decarbonized process has a resource efficiency of 45%, while no CO2 emissions are produced in this manufacturing process. This means that the decarbonization of the production process reduces resource efficiency by 14%. In relation to the reduced amount of CO2, specific resource efficiency decreases by 9.09%/tCO2. The decline in resource efficiency is mainly due to the high level of heat and energy recovery in the conventional process and the very electricity-intensive hydrogen production in the decarbonized production process.