Existing Production Processes Research Articles

Mathematical model of in-line manufacturing of sections in a flexible shipyard production system

The assembly and welding production of the shipyard is a complex production system. Studying the functioning of its individual elements, the interrelationships between them, and responses to the disturbing effects of external and internal factors in real conditions is difficult, expensive, and time-consuming. For this purpose, it is appropriate to use all possible modeling methods, especially when it comes to modeling systems with streaming processes. The application of this practice will allow, without significant expenditure of various kinds of resources, in a short time to find the optimal planning solution for the composition and performance of equipment, the placement of personnel, etc. Most modeling methods are based on a pre-developed mathematical model. The purpose of its development in the context of this article is reduced to the search for rational solutions related to increasing the flexibility of existing production processes and their management.

ELECTRON BEAM LITHOGRAPHY PROCESS QUALITY IMPROVEMENT BY ROBUST ENGINEERING APPROACH

The model-based robust approach is successfully applied to different industrial processes for improving their quality performance characteristics. The Robust engineering approach is implemented in cases of heteroscedasticity of the performance characteristics in presence of errors in the process parameters or noise factors, which is typical for the production processes. Higher quality and reproducibility of the quality characteristics can be achieved both for existing production processes or for technological process design at the production planning and development stages. In this paper the model-based robust engineering approach is implemented for the quality improvement of polymethyl methacrylate (PMMA) resist profiles, obtained by electron beam lithography process. Specific technological requirements concerning the developed profile structures, their variances (reproducibility) in production conditions and robustness toward the errors in the process parameters, are considered. Different multicriteria optimization approaches were applying and compared, aiming to simultaneously fulfil the requirements for the geometric characteristics of the positive resist PMMA.

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.

Online Machine Learning and Surrogate-Model-Based Optimization for Improved Production Processes Using a Cognitive Architecture

Cyber-Physical Systems (CPS) play an essential role in today’s production processes, leveraging Artificial Intelligence (AI) to enhance operations such as optimization, anomaly detection, and predictive maintenance. This article reviews a cognitive architecture for Artificial Intelligence, which has been developed to establish a standard framework for integrating AI solutions into existing production processes. Given that machines in these processes continuously generate large streams of data, Online Machine Learning (OML) is identified as a crucial extension to the existing architecture. To substantiate this claim, real-world experiments using a slitting machine are conducted, to compare the performance of OML to traditional Batch Machine Learning. The assessment of contemporary OML algorithms using a real production system is a fundamental innovation in this research. The evaluations clearly indicate that OML adds significant value to CPS, and it is strongly recommended as an extension of related architectures, such as the cognitive architecture for AI discussed in this article. Additionally, surrogate-model-based optimization is employed, to determine the optimal hyperparameter settings for the corresponding OML algorithms, aiming to achieve peak performance in their respective tasks.

Digital transformation of the company: classification of approaches to definition and specifics of management

The paper analyses approaches to defining a company digital transformation. Its common and distinctive characteristics have been identified and classification of approaches to the definition proposed. The author’s view of digital transformation as a permanent process that requires a complete revision of company policy and aims at digital changes in existing production processes, business models, information and communication channels, and corporate culture have been formulated. It also involves the creation of new digital productions, relationships, products and services to meet the growing needs of consumers and expand the user base. The positive experience of the Crimean digital transformation leaders has been presented. The current features of company digital transformation management have been highlighted depending on the discrete elements and systems of the company, their digital transformation management, and management specific characteristics. As the main specific characteristics of digital transformation management, the following are noted: permanence and unpredictability of management, acceleration of management processes, and ensuring cybersecurity. Additionally, specificity of starting to manage digital transformation before the decision is made to implement it in the company has been noted.

ENHANCING ENTERPRISE PRODUCTION MANAGEMENT SYSTEM THROUGH LEAN PRODUCTION PRINCIPLES

Efficient production management is essential for enterprises to maintain competitiveness and optimize resource utilization. Lean production principles have proven to be effective in streamlining operations, eliminating waste, and improving overall productivity. This study aims to enhance the enterprise production management system by implementing lean production principles. Through a systematic analysis of existing production processes, waste identification, and the application of lean tools and techniques, the study proposes strategies for process optimization, inventory management, quality improvement, and workforce engagement. The findings highlight the benefits of incorporating lean production principles into the enterprise production management system, leading to increased efficiency, cost reduction, and enhanced customer satisfaction.

Нечеткологическая модель многостадийной химико-энерготехнологической системы переработки мелкодисперсного рудного сырья

The results of the study, the purpose of which was to build a software model of a multi-stage integrated system for processing finely dispersed ore raw materials, are presented. The role of such raw materials can be processed waste at mining and processing plants of apatite-nepheline and other types of ores, which accumulate in large volumes in tailing dumps. They create a significant environmental threat in the territories adjacent to the plants due to weathering, dust formation, penetration into the soil and aquifers of chemical compounds and substances hazardous to human health. Therefore, the improvement of existing production processes, the development of new technological systems for mining and processing plants, including the application of the principles of the circular economy, waste recycling, justifies the relevance of the chosen research area. The proposed program model is based on the use of trainable trees of systems (blocks) of fuzzy inference of the first and second types. This approach made it possible to avoid unnecessary complication of the bases of fuzzy inference rules when using only one fuzzy block when building a multi-parameter model of the entire multi-stage complex system. The use of several fuzzy inference blocks that describe the behavior of individual units of the system and their configuration in accordance with the physical structure of the system allows the use of relatively simple sets of rules for individual blocks. The joint selection of their parameters when training a tree of fuzzy blocks makes it possible to achieve high accuracy of the solutions obtained. The novelty of the research results is the proposed software fuzzy model of an integrated system for processing finely dispersed ore raw materials. The results of a simulation experiment conducted in the MatLab environment using a synthetic data set generated in Simulink are presented. The results showed that the trained fuzzy model provides good fidelity of the parameters and variables from the test part of the synthetic set.

AI in Process Industries – Current Status and Future Prospects

AbstractThe chemical industry is one of the key industrial sectors in Germany and at the same time one of the largest consumers of energy and raw materials. A successful energy transition and the development of a circular economy can only succeed if they are actively supported and shaped by the chemical industry – through the redesign of existing production processes and the exploration and implementation of new process routes. The challenge is to realize this transformation within a very short time and for many production processes, whereby a much larger number of process routes must be explored. Digital technologies are key to master this transformation towards more sustainability, climate, and environmental protection. The KEEN project aims to explore and leverage artificial intelligence (AI) opportunities in process industry. The newly developed AI methods are tested wherever possible in real working environments and production plants to prove the economic benefit, applicability, and reliability of the methods and technologies.

Multi-Ion-Based Modelling and Experimental Investigations on Consistent and High-Throughput Generation of a Micro Cavity Array by Mask Electrolyte Jet Machining.

The controllability and consistency in the fabrication of micro-textures on large-scale remains a challenge for existing production processes. Mask electrolyte jet machining (MEJM) is an alternative to Jet-ECM for controllable and high-throughput surface microfabrication with more consistency of dimensional tolerances. This hybrid configuration combines the high-throughput of masked-ECM and the adjustable flow-field of jet-ECM. In this work, a duckbill jet nozzle was introduced to make MEJM more capable of batch micro-structuring. A multiphysics model was built to simulate the distribution of electrochemical reaction ions, the current density distribution, and the evolution of the shape of the machined cavity. Experimental investigations are presented showing the influence of the machining voltage and nozzle moving speed on the micro cavity. Several 35×35 micro cavity arrays with a diameter of 11.73-24.92 μm and depth of 7.24-15.86 μm are generated on 304 stainless steel.

Environmentally friendly, non-glove box, closed-system and continuously massive production of lithium sulfide for battery applications

Lithium sulfide (Li2S) is an important material for lithium-sulfur batteries and solid-state batteries. However, its prohibitive price hinders the practical development of these technologies, reflecting multiple problems in existing production processes including high temperature/energy demands, greenhouse gas emissions, low yield, low purity and the use of air sensitive equipment. Herein we report the development of an environmentally friendly process for the scalable production of Li2S without need for a glove box. The net chemical process is the reaction between Li metal and hydrogen sulfide (H2S) with ethanol as the auxiliary solvent, which can in principle be recovered and recycled. The production capability reaches 1.0 kg_Li2S/day, 50–100 times greater than the largest scale reported in the literature. The material quality of the resulting Li2S is validated through its use as a cathode material in lithium-sulfur batteries, achieving essentially comparable performance with commercial Li2S. Moreover, additional value is provided by concomitant H2 production which is demonstrated through its use for the in-situ reduction of copper oxide. We believe that the process described by this work can be readily adapted to support the developments of advanced batteries.

Co-Production of Dimethyl Carbonate, Dimethoxymethane and Dimethyl Ether from Methanol: Process Design and Exergy Analysis

Dimethyl carbonate is an important green chemical that has been widely used in the chemical industry. In the production of dimethyl carbonate, methanol oxidative carbonylation has been studied, but the conversion ratio of dimethyl carbonate using this method is too low, and the subsequent separation requires a large amount of energy due to methanol and dimethyl carbonate being azeotrope. In this paper, the strategy of “reaction instead of separation” is proposed. Based on this strategy, a novel process is developed to combine the production of DMC with that of dimethoxymethane (DMM) and dimethyl ether (DME). The co-production process was simulated using Aspen Plus software, and the product purity was up to 99.9%. The exergy analysis of the co-production process and the existing process was carried out. The exergy destruction and exergy efficiency were compared with those of the existing production processes. The results show that the exergy destruction of the co-production process is about 276% less than that of the single-production processes, and the exergy efficiencies in the developed co-production process are significantly improved. The utility loads of the co-production process are significantly lower than that of the single-production process. The developed co-production process increases the methanol conversion ratio to 95%, with a reduced energy requirement. It is proved that the developed co-production process can provide an advantageous option over the existing processes with improved energy efficiency and material savings. The strategy of “reaction instead of separation” is feasible. A new strategy is proposed for azeotrope separation.

Recycling of resources as a new vector of business development in the region

The current situation associated with geopolitical changes and the destruction of traditional supply chains in the vast majority of sectors of the economy, not only in Russia, but also in a number of countries, has led to a new reading of issues related to the search for new sources of resources to support existing production processes. The solution of this complex task will be aimed at meeting the growing needs in the face of a growing shortage of resources and minimizing environmental consequences. In a systemic sense, the development vector aimed at more efficient use of initial resources has another, no less important effect — stimulating innovation, creating new jobs, developing a circular economy based on recycling and its more advanced form of upcycling. The purpose of this article is to develop the basic provisions of the model for the optimal choice of directions for the use of waste (the recycling model based on the principles of "3R" and zero pollution — "Zero Waste") in the sectors of material production of the regional economy. The analysis of the dynamics of waste accumulation, including the morphological composition of municipal solid waste, made it possible to identify the main areas of generation of secondary resources in the regional economy and propose an approach to building a matrix for the optimal use of various types of recycling in the sectors of material production. Based on the author's approach, which consists in using a matrix method for determining the most efficient ways of waste processing for consumer industries, the article proposes a toolkit that allows you to determine the priority vectors for the development of business activity in the regional economy for the use of secondary material resources.

Evaluation of daylight comfort in industrial building

Industrial halls have a very high energy consumption due to existing production processes, heating, cooling, lighting. To reduce energy consumption, it is necessary to make a number of technical modifications to the structure itself, or the interior. The industrial sector is one of the largest consumers of energy. One way to save energy is to take advantage of daylight. Natural daylight is an important part of our daily lives at home and at work. Providing natural daylight to the work environment is essential for the personal well-being, work efficiency and safety of the users of this environment. This paper deals with the evaluation of visual comfort in an industrial hall. Visual well-being is assessed on the basis of physical calculations. These were implemented by the RADIANCE simulation program. The lighting calculation was performed for both the cloudy sky and the clear sky. The program also qualified and quantified the brightness distribution. Potential sources of glare have also been identified.

Developing a model for the introduction of Industry 4.0 technologies into the production processes of aviation industry enterprises

Aim. The presented study aims to develop a model for the introduction of Industry 4.0 technologies into the production processes of domestic industrial companies in the aviation sector.Tasks. The authors reveal the content of the concept of Industry 4.0; propose an index for assessing the innovativeness of enterprises; present an empirical research base (company cases); propose a model for the introduction of Industry 4.0 technologies into the production processes of companies; assess the selected companies according to the developed model.Methods. This study uses the methods of in-depth interviews, analysis and synthesis of the obtained results. The results of the interviews are analyzed using the authors' model for the introduction of Industry 4.0 technologies. The theoretical basis of the study includes papers by foreign authors on the theory and practice of the introduction of Industry 4.0 technologies.Results. The concept and meaning of Industry 4.0, which creates a new industrial sector and can be considered as a new industrial era based on the use of advanced technologies in business, are revealed. The authors collect empirical data on four companies in the field of aviation engineering (cases) and use them to analyze the challenges of introducing Industry 4.0 technologies and adapting existing production processes in each case. A new model for the introduction of Industry 4.0 technologies into the production processes of domestic companies is proposed and described, making allowance for the identified shortcomings of similar existing models. The results of the assessment of the studied companies according to the developed model based on the analysis of cases are presented. The major directions for the implementation of Industry 4.0 are identified: lean management, the paperless factory concept, and workshop infrastructure.Conclusions. It is shown that each of these directions can be viewed as a basis for the successful implementation of innovations. The main conclusion of the study is that Industry 4.0 requires managers to change the way they think before any technologies can be adopted.

DIGITALIZATION IN AGRICULTURE: PROBLEMS OF IMPLEMENTATION

The relevance of the research topic is determined by the fact that at the present stage the targets of modern agricultural production are concluded in the need to increase the volume of output of livestock and crop production while maintaining quality. At the same time, this topic has a certain problem field, since the growth rate of output in the industry in question is impossible today without the use of advanced technologies. In this context, the leading role belongs to the digitalization of agriculture, since only through high-tech approaches at the present stage it is possible to ensure highly competitive work of agricultural enterprises.
 The purpose of the study is to analyze the problems of digitalization implementation in agriculture. In the process of writing the work, comparative, analytical methods were used, through which a number of publications and monographs of recent years were studied within the framework of the topic of this article.
 The results of the study should include the justification of the need to implement a number of measures including retraining and training of personnel, synchronization of existing production processes with innovative solutions, as well as to organize the necessary financing for the implementation of these measures. It was concluded that these measures will optimize the process of digitalization of the agricultural sector and increase the productivity of agricultural enterprises.

Constructing the optimal power algorithm for AS/RS systems using multi-mobile robots

For any mobile system there is especially advantageous from a business perspective to develop energy-saving techniques that also extend to existing production processes. Therefore, looking for ways to enhance the energy efficiency of robot operations to maximize energy consumption efficiency is of considerable significance, a route-planning issue that refers to finding the shortest path to meet the predetermined goal location in a certain complex environment. So, one of the energy saving methods for a multi-mobile robot environment is to find the optimal path for a mobile robot that can improve power consumption. In this paper, an optimal power algorithm for “automatic storage and retrieval system” using multi-mobile robots is introduced based on efficient motion planning among a group of multi-mobile robots that gives a significant improvement in the level of energy consumption. Energy mechanism can be achieved using electrical power quantities on real robots, models or analytical equations based on robots’ physical model. The simulation results indicate that the algorithm enhanced power consumption efficiency.

SP Gas Well Development Strategy at Offshore B Flowstation Using Analytical Hierarchy Process

This research is focused on analyzing strategies for developing SP well production in the B Flowstation offshore platform. The development in question is the construction of platforms and SP gas well production facilities based on the application of the SP gas well production operation mode to the existing Bravo Flowstation production system. The application of the SP well production operation mode will determine the design of the production facility and the amount of investment the company has to operate the SP well. The mode of production operation also affects the continuity and stability of SP gas well production in meeting the company's production targets. Based on seismic results and studies from the company that wells have capacity of 53.5 BCF with a gas production rate of 30 MMSCFD and is capable of producing for 6 years. Incorrect application of operating modes has the potential to cause premature production, which means that production from the well cannot last for 6 years. That is because the occurrence of water coning which has an impact on gas production is hindered by the rate of water production. In addition, the application of the operation mode also affects the continuity of gas well production. Gas production activities may be halted due to production shutdowns due to a mismatch of the SP well production line technology design that is applied to an existing production system. The cessation of SP well gas production activities can also be caused by operational activities such as maintenance activities. From the potential problems that arise, a qualitative analysis is needed by considering every aspect of the problem. With the complexity of things that must be considered in the production development strategy used the AHP (Analytic Hierarchy Process) method. 4 alternative choices of SP well operation modes are determined by the expert. The alternatives include: high pressure mode; low pressure mode; medium pressure mode; and combine high low pressure mode. Criteria identified by the expert include: technology; capital costs; the impact of existing production; operating costs; decline reservoir. From the data obtained in the field as a reference for experts to determine the weighting in the AHP method, the dominant alternative is the development of SP wells based on the combining high low pressure operation mode. The high low pressure operating mode provides continuous production without being affected by existing production processes and has the potential for a medium for water coning. With a sizeable investment the SP well development strategy can be on target in production and on return on investment.

Using carbon black to facilitate fast charging in lithium-ion batteries

High-energy-density lithium (Li)-ion batteries with excellent fast-charging ability are crucial for popularizing electric vehicles (EVs). Although graphite has a high energy density, the near 0 V redox potential vs. Li/Li+ and selective Li+ intercalation limit its application for fast charging. Carbon black (CB) is an amorphous carbon with graphite-like crystallites that have more orientations and a larger lattice spacing than graphite, thereby facilitating Li+ intercalation. CB is only recently investigated for fast-charging applications. Here, the battery performance is systematically improved by modifying the CB content of graphite, thereby endowing batteries with a high energy density and a fast-charging ability. Optimized anodes with a commercial-level areal capacity of approximately 3 mAh cm−2 are prepared and used to prepare pouch cells (>2 A h). These cells have a high energy density of 200 Wh kg−1 and 420 Wh L−1 and retain 87% of the initial capacity after 500 cycles at 3C. The improved fast-charging ability is attributed to the reduction in the Li+ intercalation resistance after the introduction of CB. The composite anode fabrication is compatible with the existing production processes. Thus, the composite anode can potentially be used with high-capacity cathodes to fabricate high-energy-density batteries with fast-charging ability for EVs.

Comments on Michael Hudson: Making Capitalism Great Again? A Critique of the “Rentier Takeover” Thesis

Michael Hudson argues that a new form of financial capitalism has displaced the industrial capitalism of Marx’s day. Unlike earlier capitalists, whose pursuit of lower costs led to improvements in the organization of production, the typical wealth owner today is a passive rentier who, like a feudal landlord, merely claims the surplus from existing production processes. Some form of this vision of financialization is widely held, but, I argue, misleading. It exaggerates the differences between historical and present-day capitalism, and misses the ways in which “finance” and “industry” form complementary parts of a single process. JEL classification: B51, E44, N20

Toward the Enhancement of Microalgal Metabolite Production through Microalgae-Bacteria Consortia.

Simple SummaryMicroalgae are photosynthetic microorganisms with high biotechnological potential. However, the sustainable production of high-value products such as lipids, proteins, carbohydrates, and pigments undergoes important economic challenges. In this review, we describe the mutualistic association between microalgae and bacteria and the positive effects of artificial consortia on microalgal metabolites’ production. We highlighted the potential role of growth-promoting bacteria in optimizing microalgal biorefineries for the integrated production of these valuable products. Besides making a significant enhancement to microalgal metabolite production, the bacterium partner might assist in the biorefinery process’s key stages, such as biomass harvesting and CO2 fixation.Engineered mutualistic consortia of microalgae and bacteria may be a means of assembling a novel combination of metabolic capabilities with potential biotechnological advantages. Microalgae are promising organisms for the sustainable production of metabolites of commercial interest, such as lipids, carbohydrates, pigments, and proteins. Several studies reveal that microalgae growth and cellular storage of these metabolites can be enhanced significantly by co-cultivation with growth-promoting bacteria. This review summarizes the state of the art of microalgae–bacteria consortia for the production of microalgal metabolites. We discuss the current knowledge on microalgae–bacteria mutualism and the mechanisms of bacteria to enhance microalgae metabolism. Furthermore, the potential routes for a microalgae–bacteria biorefinery are outlined in an attempt to overcome the economic failures and negative energy balances of the existing production processes.