Increase Production Efficiency Research Articles

Desain Rancang Bangun Inovasi Teknologi Rocket Stove Hemat Energi Dan Turbin Ventilator Sebagai Upaya Optimalisasi Peningkatan Kapasitas Produksi Keripik Ikan Kunir

UD. Farah is a well-known trading business in Situbondo that specializes in producing highly sought-after fresh seafood chips called "Ikan Kunir". However, the production capacity is still low due to the use of traditional equipment in the kitchen. To address this, the development of technology using a Rocket Stove is necessary. The Rocket Stove design allows for high-temperature wood combustion, resulting in complete combustion, increased heat energy, and smoke-free operation. It is also more fuel-efficient compared to open fire, saving up to 50% fuel. Furthermore, the current kitchen conditions lack attention to health and safety aspects, leading to smoke-filled, messy, dirty, and dark environments. To improve air circulation and increase production efficiency, a Turbine Ventilator will be installed in the combustion area. This applied research focuses on designing and innovating energy-efficient Rocket Stove technology and utilizing a Turbine Ventilator to enhance the production efficiency of Ikan Kunir chips in terms of time, cost, and energy. The breakthrough aims to improve user health by achieving complete combustion and reducing smoke emissions. The goal of this activity is to address the business partner's challenges, particularly in increasing product capacity and improving occupational health and safety management.

Electrocatalytic reduction of simulated industrial CO2 and CO mixtures: Revising chronoamperometry to enable selective gas mixture reduction via cyclic voltammetry

While substantial advancements have been achieved in the electrocatalytic reduction of pure CO2 or CO, the reduction of carbon oxide mixtures remains underexplored, a key limitation in scaling the technology for industrial applications. This underexplored domain gains practical importance by considering carbon oxide mixtures, given that CO and CO2 together constitute a large proportion of diverse industrial gas streams. However, the simultaneous reduction of mixed CO and CO2 poses a potential challenge due to their differing optimal reduction potentials, which complicates an efficient reduction process. While cyclic voltammetry (CV) is typically used for characterization, which involves sweeping between positive and negative potentials, we utilized it to conduct reduction reactions within a defined negative potential window. This approach, serving as an alternative to conventional chronoamperometry that maintains a constant potential, ensures a continuous reduction reaction throughout the entire cycling process. By employing cycling between the optimized reduction potentials of CO2 (−1.4 V) and CO (−1.6 V), CV achieved an increase in production efficiency, ranging from 25 % to 40 % for predominant products (HCOOH and C2H4), in comparison to chronoamperometry. Meanwhile, the results underscored the dependency of performance enhancement on the scan rate of cycling, revealing plausible correlations with mass transfer and electrode surface dynamics. Furthermore, the findings indicated that the selectivity towards HCOOH and C2H4 is closely related to the CO2/CO ratios of gas sources. This provides insight into the potential for modulating selectivity of industrial gas reduction for improved product quality and customization.

Integration of bionics, digital innovations, and democratic management principles for industrial transformation.

This article explores an innovative and interdisciplinary approach to the integration of bionic principles, digital technologies and democratic governance in the transformation of industrial production in Ukraine. Emphasis is placed on the adaptation of industrial production to modern requirements of sustainability, efficiency and environmental safety in the context of the Ukrainian economy. The bionic approach involves the integration of natural principles and mechanisms into technological processes, offering a unique perspective for increasing production efficiency and environmental sustainability. The main objectives of this study are to study how a bionic approach, combined with digital technologies and public participation in decision-making, can transform industrial production in Ukraine, making it more sustainable, efficient and environmentally friendly. This includes an analysis of the bionic approach and its potential to improve production efficiency, the role of digital technologies in optimizing production processes, and the impact of democratic governance on creating a fair and transparent economic system in an industrial context. The article provides strategic directions and recommendations that can help Ukraine adapt to global trends and use them for sustainable industrial development and improving the quality of life. The importance of the bionic approach in creating a sustainable and efficient industry is undeniable. The implementation of this approach not only reduces the environmental impact of production, but also stimulates innovative development, opening up new opportunities for the creation of technologies that are environmentally safe and cost-effective. The article also emphasizes the importance of public participation in economic decision-making in the industrial sector. This democratic governance in the economy, the key theme of the article, emphasizes the importance of involving civil society in decision-making processes in the economy, especially in the context of industrial reform.

Design method of laboratory equipment monitoring system based on industrial internet of things

AbstractThe IoT‐based monitoring system is used to collect, transmit, analyze, and monitor industrial data in real time, as well as to monitor and operate industrial field equipment. Reduced manufacturing costs, better managerial decision‐making, and increased production efficiency are all very important. The main research results are as follows: (1) The current development of the IoT technology at home and abroad is analyzed, the overall design of the laboratory equipment monitoring system with a three‐layer three‐dimensional architecture is proposed, and its working mode and functional composition are discussed. (2) A set of PLC control system with S7‐300 PLC as the core is designed by using the laboratory CS4000 process experiment device, which realizes the functional requirements of the laboratory equipment monitoring system on‐site monitoring. The intelligent IoT gateway suitable for the system is selected as the data collection and aggregation device of the system, which fully demonstrates the great role of the IoT technology in the monitoring field. (3) A laboratory remote monitoring platform that can remotely monitor experimental data is designed and its software and hardware functions are tested. The results show that all indicators have excellent performance.

RE-ENGINEERING OF BUSINESS PROCESSES IN THE DESIGN ACTIVITIES OF MODERN MACHINE-BUILDING ENTERPRISES

Scientific and technical progress, globalization and market competition have faced manufacturers with the fact of a significant reduction in the life cycle of finished products. The modern stage of the development of mechanical engineering is characterized by the wide implementation of the latest achievements of science and technology, which ensures an increase in production efficiency due to the reduction of the length of the design process and the introduction of new, modern types of machines, equipment, materials, etc. Flexible production systems, robots, processing centers appeared, which significantly shortened the production cycle, and in these conditions, new requirements for design activities were formed. In connection with the rapid development of computer technologies, today there is practically no engineering activity that is not equipped with computer modeling and design tools in one way or another. Reengineering is a more radical measure that involves a global restructuring of business processes, therefore, during reengineering, the company's activities can be fundamentally changed. Today, you can find several understandings of the process approach to management. Among them, it is possible to single out an understanding that is based on a systematic consideration of the company's activity as a set of processes and the development of a process management system. This understanding of the process approach is based on the definition of the process and systems approach to the enterprise, the definition of the business process of the enterprise and the system of interrelated processes, as well as the understanding of the steps necessary to implement the process approach. Such an approach is the fundamental and determining point of increasing the efficiency of management, which is the management of production in the direction of its improvement. The peculiarities of design activity and the main approaches to its reengineering are considered.

Research overview on the genetic mechanism underlying the biosynthesis of polysaccharide in tuber plants.

Tuber plants are of great significance in the world as human food crops. Polysaccharides, important metabolites in tuber plants, also serve as a source of innovative drugs with significant pharmacological effects. These drugs are particularly known for their immunomodulation and antitumor properties. To fully exploit the potential value of tuber plant polysaccharides and establish a synthetic system for their targeted synthesis, it is crucial to dissect their metabolic processes and genetic regulatory mechanisms. In this article, we provide a comprehensive summary of the basic pathways involved in the synthesis of various types of tuber plant polysaccharides. We also outline the key research progress that has been made in this area in recent years. We classify the main types and functions of tuber plant polysaccharides and analyze the biosynthetic processes and genetic regulation mechanisms of key enzymes involved in the metabolic pathways of starch, cellulose, pectin, and fructan in tuber plants. We have identified hexokinase and glycosyltransferase as the key enzymes involved in the polysaccharide synthesis process. By elucidating the synthesis pathway of polysaccharides in tuber plants and understanding the underlying mechanism of action of key enzymes in the metabolic pathway, we can provide a theoretical framework for enhancing the yield of polysaccharides and other metabolites in plant culture cells. This will ultimately lead to increased production efficiency.

DEVELOPMENT OF RECOMMENDATIONS FOR OPTIMIZATION OF TECHNOLOGICAL PROCESSES OF PROCESSING AND USE OF HEAT AND MASS EXCHANGE EQUIPMENT FOR DRYING LEGUMES

The article is devoted to the development of recommendations for the optimization of technological processes of processing and the use of heat and mass exchange equipment for drying legumes. Legumes are an important source of protein and other nutrients in the food and feed industry, and their drying plays a key role in preserving and increasing shelf life. The article includes analysis of technological processes, selection of optimal heat and mass exchange equipment, control of temperature and humidity, reduction of losses of useful substances and implementation of a quality monitoring and control system. Optimizing these processes will help increase production efficiency and improve the quality of dried leguminous herbs, contributing to the development of the industry and meeting the demand for valuable products. In this context, our article is devoted to the development of recommendations for the optimization of technological processes of processing and the use of heat and mass exchange equipment for drying legumes. By combining scientific analysis, practical experience and innovative approaches, we set ourselves the task of developing integrated recommendations that will contribute to increasing the efficiency of the drying process, reducing the loss of useful substances and improving the quality of dried legumes. An important aspect of our article is not only the theoretical base and scientific research, but also a practical approach to solving this problem. We hope that the developed recommendations will find practical application in the agro-industrial sector, contributing to the conservation of resources, increasing the quality and competitiveness of products and contributing to the sustainable development of this important industry.

A Fault-Tolerant Soft Sensor Algorithm Based on Long Short-Term Memory Network for Uneven Batch Process

Batch processing is a widely utilized technique in the manufacturing of high-value products. Traditional methods for quality assessment in batch processes often lead to productivity and yield losses because of offline measurement of quality variables. The use of soft sensors enhances product quality and increases production efficiency. However, due to the uneven batch data, the variation in processing times presents a significant challenge for building effective soft sensor models. Moreover, sensor failures, exacerbated by the manufacturing environment, complicate the accurate modeling of process variables. Existing soft sensor approaches inadequately address sensor malfunctions, resulting in significant prediction inaccuracies. This study proposes a fault-tolerant soft sensor algorithm that integrates two Long Short-Term Memory (LSTM) networks. The algorithm focuses on modeling process variables and compensating for sensor failures using historical batch quality data. It introduces a novel method for converting quality variables into process rates to align uneven batch data. A case study on simulated penicillin production validates the superiority of the proposed algorithm over conventional methods, showing its capacity for precise endpoint detection and effectiveness in addressing the challenges of batch process quality assurance. This study offers a robust solution to the issues of soft sensor reliability and data variability in industrial manufacturing.

Improvement of the Technology of Precision Forging of Connecting Rod-Type Forgings in a Multiple System, in the Aspect of the Possibilities of Process Robotization by Means of Numerical Modeling.

The study refers to the application of numerical modeling for the improvement of the currently realized precision forging technology performed on a hammer to produce connecting rod forgings in a triple system through the development of an additional rolling pass to be used before the roughing operation as well as preparation of the charge to be held by the robot's grippers in order to implement future process robotization. The studies included an analysis of the present forging technology together with the dimension-shape requirements for the forgings, which constituted the basis for the construction and development of a thermo-mechanical numerical model as well as the design of the tool construction with the consideration of the additional rolling pass with the use of the calculation package Forge 3.0 NxT. The following stage of research was the realization of multi-variant numerical simulations of the newly developed forging process with the consideration of robotization, as a result of which the following were obtained: proper filling of the tool impressions (including the roller's impression) by the deformed material, the temperature distributions for the forging and the tools as well as plastic deformations (considering the thermally activated phenomena), changes in the grain size as well as the forging force and energy courses. The obtained results were verified under industrial conditions and correlated with respect to the forgings obtained in the technology applied so far. The achieved results of technological tests confirmed that the changes introduced into the tool construction and the preform geometry reduced the diameter, and thus also the volume, of the charge as well as provided a possibility of implementing robotization and automatization of the forging process in the future. The obtained results showed that the introduction of an additional rolling blank resulted in a reduction in forging forces and energy by 30% while reducing the hammer blow by one. Attempts to implement robotization into the process were successful and did not adversely affect the geometry or quality of forgings, increasing production efficiency.

Reentrant hybrid flow shop scheduling with stockers in automated material handling systems using deep reinforcement learning

In smart factories, automated material handling system (AMHSs) replace manual material handling to increase production efficiency, in which stockers serve as the temporary storage for work-in-process inventories. Furthermore, costly machines and complex processes in advanced manufacturing lead to the need for multiple reentrant processes of the same workstation. However, previous works on scheduling problems rarely considered the function of stockers and reentrant processes, and their approaches were mostly based on metaheuristic algorithms. Recent advances in artificial intelligence enable the possibility of solving scheduling problems using deep reinforcement learning (DRL). Therefore, this work investigates the reentrant hybrid flow shop scheduling problem with stockers (RHFS2) inspired by AMHSs, and solves it by DRL. Firstly, the states, actions, and rewards of the Markov decision process for this problem are designed; and then, two deep Q network (DQN) approaches based on the actions for determining machines and jobs, respectively, are proposed. Simulation results demonstrate that our proposed DQN approaches outperform for finding better solutions of different-scale problems than classical metaheuristic algorithms.

Application of micro-substance tracer test in fractured horizontal wells

This paper delves into a novel micro-substance tracer test in fractured horizontal well C-15. The experimental results are highly encouraging as they demonstrate that the trace material tracer is capable of satisfying the testing demands, even when there are large numbers of fracturing stages involved. Data interpretation process involved dividing the test duration into two stages-fluid flowback period and stable production period. The tracer test data were employed to analyze the production profile of the well. The findings made it evident that the primary production stage underwent alterations in different production stages. Moreover, the degree of heterogeneity pertaining to each fracturing stage was characterized by employing the residence time distribution method. It was observed that the Lorentz coefficient lying between the primary production stage and the remaining fracturing stages ranged from 0.46 to 0.68. This study expands the application of the residence time distribution method for evaluating tracer testing. Through a comprehensive analysis of heterogeneity data within the fracturing stages and the production dynamics of the well, the effectiveness of the fracturing process can be assessed. This research enables reservoir operators to gain deeper insights into the dynamics of test wells, ultimately leading to increased production efficiency.

Classification and identification of agricultural products based on improved MobileNetV2.

With the advancement of technology, the demand for increased production efficiency has gradually risen, leading to the emergence of new trends in agricultural automation and intelligence. Precision classification models play a crucial role in helping farmers accurately identify, classify, and process various agricultural products, thereby enhancing production efficiency and maximizing the economic value of agricultural products. The current MobileNetV2 network model is capable of performing the aforementioned tasks. However, it tends to exhibit recognition biases when identifying different subcategories within agricultural product varieties. To address this challenge, this paper introduces an improved MobileNetV2 convolutional neural network model. Firstly, inspired by the Inception module in GoogLeNet, we combine the improved Inception module with the original residual module, innovatively proposing a new Res-Inception module. Additionally, to further enhance the model's accuracy in detection tasks, we introduce an efficient multi-scale cross-space learning module (EMA) and embed it into the backbone structure of the network. Experimental results on the Fruit-360 dataset demonstrate that the improved MobileNetV2 outperforms the original MobileNetV2 in agricultural product classification tasks, with an accuracy increase of 1.86%.

Development of production potential of agro-industrial complex of the Republic of Belarus in the context of trends in global food market

The paper presents the results of analysis of trends in global agricultural production in the context of impact on the development of agro-industrial complex of the Republic of Belarus, including: determining impact of the state of the world grain market on balance of markets and prices, increasing demand for agricultural products and, in particular, livestock products, stimulating consumption of feed, strengthening the negative impact of barriers in global trade in food and resources for its production. The directions and opportunities for the domestic agro-industrial complex are determined due to the internal potential of sustainability, increasing the efficiency of strategic forecasting, intensifying the processes of technical and technological re-equipment of production, and developing the market infrastructure. A set of measures has been proposed, grouped in key areas, which will increase production and export potential of the domestic agro-industrial complex and implement a strategy of sustainable economic growth, including: strengthening the feed base of animal husbandry as an export-oriented industry, increasing production efficiency, optimizing costs, improving product quality, ensuring impeccable compliance with technological, technical and labor discipline, technical regulations, creating sustainable models of product promotion in domestic and foreign markets.

Microalgae cultivation using ammonia and carbon dioxide concentrations typical of pig barns

ABSTRACT While global population growth drives increased production efficiency in animal agriculture, there is a growing demand for environmentally friendly practices, particularly in reducing air pollutant emissions from concentrated animal feeding operations. This study explores the potential of cultivating microalgae in photobioreactors (PBRs) as an eco-friendly and cost-effective approach to mitigate NH3 and CO2 emissions from pig barns. Unlike traditional physicochemical mitigation systems, microalgae offer a renewable solution by converting pollutants into valuable biomass. The research focused on Scenedesmus dimorphus growth under typical NH3 and CO2 concentrations found in the indoor air of pig barns. Four NH3 (0, 12, 25, and 50 ppm) and four CO2 concentrations (350, 1200, 2350, and 3500 ppm) were tested using photobioreactors. Results showed a maximum specific growth rate of 0.83 d−1 with 12 ppm NH3 and 3500 ppm CO2. The dry biomass concentration was significantly higher (1.16 ± 0.08 g L−1; p < 0.01) at 25 ppm NH3 and 2350 ppm CO2 than other test conditions. S. dimorphus demonstrated the peak NH3 and CO2 fixation rates (23.8 ± 2.26 mg NH3 L−1 d−1 and 432.24 ± 41.09 mg CO2 L−1 d−1) at 25 ppm NH3 and 2350 ppm CO2. These findings support the feasibility of using algae to effectively remove air pollutants in pig barns, thereby improving indoor air quality.

Impact of Mathematical Models in IT System Design and Optimization

This research investigates the crucial role of mathematical models in designing and optimizing modern IT systems. The paper explores how mathematical tools simplify complex systems, enabling efficient design and improved understanding. The impact of mathematical models extends beyond initial design. The research emphasizes the importance of maintaining these models throughout a system's life cycle to ensure ongoing optimization. Fuzzy Logic Controllers and Coverage Path Planning (CPP) algorithms are highlighted as key examples of how mathematical models are utilized in IT system design, particularly for robotic guided vehicles. The research focuses on real-world applications of CPP and the role mathematical models play in finding optimal solutions. This study aims to benefit professionals in robotics research, logistics, and process automation. It explores how mathematical models can contribute to overcoming challenges in modern industries, such as increased production efficiency and reduced costs.

THEORETICAL ASPECTS OF AGRICULTURAL SPECIALIZATION AND ITS IMPACT ON LAND USE EFFICIENCY

Agricultural specialization is a key strategyemployed by farmers to increase production efficiency and optimize resources. By focusing on a specific crop or livestock, farmers can benefit from economies of scale, specialized knowledge, and increased productivity. However, the impact of specialization on land use efficiency is a topic of interest and debate in the field of agriculture. This research aims to explore the relationship between agricultural specialization and land use efficiency, examining the advantages and challenges associated with thispractice. By analyzing data and studies on the subject, this study seeks to provide insights into how specialization can influence land use efficiency and offer recommendations for improving sustainable land management practices in agriculture.

Selected Issues, Methods, and Trends in the Energy Consumption of Industrial Robots

Industrial robots, like all machines, require energy to operate, which is why energy efficiency in industrial robotics has been a subject of consideration in recent years in many scientific and industrial centers. Interest in the topic is especially noticeable in Industry 4.0. Research on energy efficiency stems from the emergence of new possibilities in terms of making strategic decisions related to manufacturing processes. As energy-efficient production is an essential part of sustainable development, the energy efficiency of industrial robots must be considered. The need to reduce costs while maintaining quality and increasing production efficiency has necessitated the implementation of modern solutions aimed at reducing electricity consumption. The rational use of electrical energy, especially in the industrial sector, significantly reduces production costs and, consequently, contributes to a company’s profits and competitiveness. This article aims to provide an overview of energy efficiency issues based on recently published articles. This article discusses the appropriate selection of robots, their programming, energy-efficient trajectory planning, and the monitoring of the operation of the robotic system to minimize energy consumption. Typical industrial applications of robots are also mentioned and discussed.

Komunikasi yang Canggih di Era Society Industri 5.0

Industry 5.0 is a new industrial era characterized by the use of advanced technology such as the Internet of Things (IoT), artificial intelligence (AI), and robotics. In this day and age, communication has become increasingly important as technological advances allow humans to interact more effectively with machines and systems. Advanced communications in the Industry 5.0 era require the use of new technologies such as augmented reality (AR) and virtual reality (VR) to enhance the user experience. For example, in manufacturing, AR can be used to visually guide workers through the production process, and VR can be used for training and simulations. In addition, AI technology also enables more effective communication between humans and machines. For example, in the automotive industry, AI can be used to monitor vehicle performance and provide early warning if there is a problem. This reduces downtime and increases production efficiency. As communication technology advances, concerns arise regarding changes in communication ethics. Apart from the many positive benefits, virtual communication also has a negative impact on society. This includes the development of individualistic personalities which can give rise to social communication crises, especially among the younger generation. This article discusses the communication ethics of young women on social media. Basically, communication ethics is very important and easy to implement. Both as media and as media. Good communication ethics prevent misunderstandings and arguments that lead to mutual insults. If the communication is rude, impolite, and far from moral values, especially if it is spread via unknown social media, then it is useless and will not provoke or cause conflict Maybe so

A Review of Lithium-Ion Battery Recycling: Technologies, Sustainability, and Open Issues

Lithium-ion batteries (LIBs) are a widely used energy storage technology as they possess high energy density and are characterized by the reversible intercalation/deintercalation of Li ions between electrodes. The rapid development of LIBs has led to increased production efficiency and lower costs for manufacturers, resulting in a growing demand for batteries and their application across various industries, particularly in different types of vehicles. In order to meet the demand for LIBs while minimizing climate-impacting emissions, the reuse, recycling, and repurposing of LIBs is a critical step toward achieving a sustainable battery economy. This paper provides a comprehensive review of lithium-ion battery recycling, covering topics such as current recycling technologies, technological advancements, policy gaps, design strategies, funding for pilot projects, and a comprehensive strategy for battery recycling. Additionally, this paper emphasizes the challenges associated with developing LIB recycling and the opportunities arising from these challenges, such as the potential for innovation and the creation of a more sustainable and circular economy. The environmental implications of LIB recycling are also evaluated with methodologies able to provide a sustainability analysis of the selected technology. This paper aims to enhance the comprehension of these trade-offs and encourage discussion on determining the “best” recycling route when targets are in conflict.

Optimization Of Drilling Strategies To Increase Production Efficiency In The Field Of Production Geology

This research aims to investigate and optimize drilling strategies as an effort to increase production efficiency in the geological context of oil and gas production. Effective drilling is a key element in the exploitation of hydrocarbon resources, and this research combines geological analysis and drilling techniques to achieve optimal results. This study begins with an in-depth characterization of the physical and chemical properties of the reservoir rocks to understand the geological challenges faced. Next, existing drilling techniques are evaluated and analyzed in the context of a particular production field. The results of this analysis are the basis for developing an integrative model that combines aspects of geology and drilling techniques.Through this approach, this research aims to identify potential improvements in drilling strategies that could significantly increase production. Simulation and modeling results illustrate the positive impact of implementing optimized drilling strategies on production efficiency and hydrocarbon recovery. The conclusions of this research provide a new perspective on the importance of integration between geological science and drilling techniques in achieving efficient production goals. It is hoped that these findings will provide practical guidance for the production geology industry to increase the sustainability of oil and gas production.&#x0D;