Model Of Production Process Research Articles

Network enterprises: Production and business process models based on multi-agent systems

Network enterprises: Production and business process models based on multi-agent systems

Network enterprises: Production and business process models based on multi-agent systems

Network enterprises: Production and business process models based on multi-agent systems

Impact of bioenergy feedstock carbon farming on sustainable aviation fuel viability in the United States.

Biomass-derived sustainable aviation fuel holds significant potential for decarbonizing the aviation sector. Its long-term viability depends on crop choice, longevity of soil organic carbon (SOC) sequestration, and the biomass-to-biojet fuel conversion efficiency. We explored the impact of fuel price and SOC value on viable biojet fuel production scale by integrating an agroecosystem model with a field-to-biojet fuel production process model for 1,4-dimethylcyclooctane (DMCO), a representative high-performance biojet fuel molecule, from Miscanthus, sorghum, and switchgrass. Assigning monetary value to SOC sequestration results in substantially different outcomes than an increased fuel selling price. If SOC accumulation is valued at $185/ton CO2, planting Miscanthus for conversion to DMCO would be economically cost-competitive across 66% of croplands across the continental United States (US) by 2050 if conventional jet fuel remains at $0.74/L (in 2020 US dollars). Cutting the SOC sequestration value in half reduces the viable area to 54% of cropland, and eliminating any payment for SOC shrinks the viable area to 16%. If future biojet fuel prices increase to $1.24/L-Jet A-equivalent, 48 to 58% of the total cultivated land in the United States could support a more diverse set of feedstocks including Miscanthus, sorghum, or switchgrass. Among these options, only 8-14% of the area would be suitable exclusively for Miscanthus cultivation. These findings highlight the intersection of natural solutions for carbon removal and the use of deep-rooted feedstocks for biofuels and biomanufacturing. The results underscore the need to establish clear and consistent values for SOC sequestration to enable the future bioeconomy.

Особенности проектирования и использования цифрового двойника проектной организации

The author of the article considers the issues related to the development and effective application of digital twin in the activities of design organizations. A brief comparative analysis of the concepts of "digital twin" (DT) and "BIM-model" is given. The specifics of creating a digital model of a project organization, which forms the basis of the DT, are analyzed. The processes that need to be modeled online are given. 
 It is emphasized that the main project processes are extremely creative and are directly related to the effective formation of project development teams. Team building models that can be implemented in DT are presented and analyzed. Two problem statements are formulated for realization in the DT of a project company: direct and reverse. An enlarged approach is proposed to determine the parameters of the digital twin of the project organization when solving the direct problem.
 The final conclusion is that DT methods and tools are necessary for complex analysis, diagnostics and modeling of production, technical and social processes of design companies in the construction industry.

Dynamic modelling of bacteriophage production process

Dynamic modelling of bacteriophage production process

Digitization of learning environment of higher education institutions: conceptual foundations and practical cases

Digital transformation involves the use of digital technologies for rebuilding processes and increasing their efficiency. It is confirmed by the results of the research on transformational processes in various spheres. This research paper deals with the development (modernization) of digital learning environments of higher education institutions, which creates conditions for creating models of real production and social processes by means of modern digital technologies. It will strengthen the competence potential of all the stakeholders of higher education institutions, which train specialists in digital technologies. The need to upgrade the existing educational environments of higher education institutions in the context of crisis situations related to global challenges (for example, COVID-19) or the specifics of a specific country (the war in Ukraine) or an educational institution is substantiated. The research paper specifies a conceptual model of the next generation digital learning environment of a higher education institution, which involves the distribution of resource distribution and provision of integration of resources, data and users according to three levels (micro, meso and macro levels), and provides the cases of its implementation in National University of Life and Environmental Sciences of Ukraine and Borys Grinchenko Kyiv University. The monitoring data are presented both at the level of external (development of the component composition of the environment) and internal (change of organizational processes according to the students’ demand) design of the environment. The need for designing a change management system at the level of a higher education institution or its structural subdivisions is identified.

Geometric Poisson distribution of photons produced in the ultrarelativistic hadronic collisions

We show that the multiplicity distribution of photons produced with enhanced void probability in inelastic proton-proton collisions at sqrt{s} = 900 GeV, 2.76 TeV, and 7 TeV, measured at forward rapidities by the ALICE experiment at LHC, can be described by the geometric Poisson distribution. The traditionally used negative binomial distribution fails to reproduce the enhanced void probability and the shape of the modified combinants simultaneously. Our findings are relevant for the theoretical modeling of photon production processes in high-energy hadronic collisions.

A sequential cross-product knowledge accumulation, extraction and transfer framework for machine learning-based production process modelling

ABSTRACT Machine learning is a promising method to model production processes and predict product quality. It is challenging to accurately model complex systems due to data scarcity, as mass customisation leads to various high-variety low-volume products. This study conceptualised knowledge accumulation, extraction, and transfer (KAET) to exploit the knowledge embedded in similar entities to address data scarcity. A sequential cross-product KAET (SeqTrans) is proposed to conduct KAET, integrating data preparation and preprocessing, feature selection (FS), feature learning (FL), and transfer learning (TL). The FS and FL modules conduct knowledge extraction and help address various practical challenges such as changing operating conditions and unbalanced datasets. In this paper, sequential TL is introduced to production modelling to conduct knowledge transfer among multiple entities. The first case study of auxetic material performance prediction demonstrates the effectiveness of sequential TL. Compared with conventional TL, sequential TL can achieve the same test mean square errors with 300 fewer training examples when facing data scarcity. In the second case study, balancing anomaly detection models were constructed for two gas turbines in the same series using real-world production data. With SeqTrans, the F1-score of the anomaly detection model of the data-poor engine was improved from 0.769 to 0.909.

A new Malmquist productivity index with an application to commercial banks

Abstract Accepted by: Aris Syntetos Management-led productivity improvements are crucial for achieving sustainable development, and the Malmquist productivity index is known to be useful in relevant contexts. This study aims to extend such index by using non-parametric mathematical modelling of production processes. Specifically, and in the spirit of the existing index, we introduce the directional distance function to develop a new one applicable to the joint production of desirable and undesirable outputs. Furthermore, we decompose the new index into two constituent components to provide more intuitive explanations when revealing the root sources of productivity changes over time. Under the cost minimization assumption, the new index is applicable when producers implement resource allocation management, and the input–output quantities and the micro-level input prices are known. The index emphasizes that the allocative efficiency should be regarded as an important aspect of productivity assessment like the technical efficiency. As a practical benchmarking tool, it can offer valuable information and provide appropriate strategies for managerial decision-making. The index’s application and usefulness is demonstrated in the commercial bank sector in China.

Identification and fixing bottlenecks of a food manufacturing system using a simulation approach

In manufacturing systems, simulation modeling plays an important role in creating some changes instead of working on real systems. Manipulation in a real system is more costly than manipulation in a simulated model. In this research, we tried to use a simulation approach to recognize and minimize bottlenecks of a production line, which will decrease costs and improve productivity. To achieve our objectives, we chose a case and analyzed its production line. By using our case study strategy, we tried to collect our data and adapt a conceptual model of production processes drawing on an operation process chart (OPC). After that, we created a simulation model of the production processes by using the popular Arena simulation software 13.5. By running the Arena model, some bottlenecks were found. Ultimately, we proposed some solutions to obviate bottlenecks and reduce the total costs of production.

Techno-economic analysis and life cycle assessment of manufacturing a cellulose nanocrystal-based hybrid membrane

Moisture-selective polymer-based membranes can be a promising method for energy saving in drying systems of different industries that vent moisture vapor-rich air to the atmosphere, such as wood drying, biorefinery, food processing, and pharmaceutical industry. Developing a sustainable product with bio-based materials reduces the environmental impacts. This study assessed the techno-economic feasibility and life-cycle environmental impacts of producing a novel cellulose nanocrystal/polydimethylsiloxane hybrid moisture-selective membrane. The cradle-to-gate assessment was facilitated by developing an industrial-scale membrane production process model guided by optimized experimental results. The estimated plant capital, operating cost, and annual revenue of a 10 MT/day capacity cellulose nanocrystal/polydimethylsiloxane membrane production plants were $136 million, $139 million, and $198 million respectively. The estimated minimum selling price of the final product, 1 m2 80 μm thick cellulose nanocrystal/polydimethylsiloxane membrane was $3.68/m2, which is lower or comparable to the current alternative market retail price. The environmental impacts of the cellulose nanocrystal/polydimethylsiloxane production process were lower for all evaluated environmental impact categories, with an estimated global warming impact of 8.7 kg CO2 eq/m2 of 80 μm thick cellulose nanocrystal/polydimethylsiloxane membrane, representing a 12 % reduction compared to polydimethylsiloxane membrane production without cellulose nanocrystal. The small addition of cellulose nanocrystal to the polydimethylsiloxane membrane provided relatively lower environmental impacts with a similar cost and thus ought to be the preferred choice.

Probing into the interactions among operating variables in blue hydrogen production: A new approach via design of experiments (DoE)

Anthropogenic CO2 emission is a key driver in global warming and climate change. Worldwide, H2 production accounts for 2.5% of this CO2 emission. A shift to clean methods of hydrogen production is required to reduce CO2 emissions, and to mitigate the effects of climate change. Developing optimised process models of H2 production processes is required in order to investigate the effects of operational variables of the process and their impacts on key performance indicators (KPIs). Within this study, a detailed rate-based model was implemented to simulate the reformer in Sorption Enhanced Steam Methane Reforming (SE-SMR), as well as Sorption-Enhanced Auto-Thermal Reforming (SE-ATR) processes. The results indicate that the SE-ATR/ATR corresponds to a significantly improved performance over the SMR with the optimal operating conditions for achieving the desired KPIs, including hydrogen purity (86%), hydrogen yield (36%), methane conversion (99%), and carbon capture rate (50%) at a temperature of 720 °C, a pressure of 20 bara, and an S/C ratio of 6. Whereas with SMR, the temperature, pressure, and S/C ratio should be adjusted to 975 °C, 20 bara, and 6, respectively, to achieve a hydrogen purity of 84%, a hydrogen yield of 42%, a methane conversion of 96%, and a carbon capture rate of 48%. The study provides insights into the optimal operating conditions to achieve maximum efficiency in the reformer, and demonstrates the effectiveness of incorporating DoE within process modelling as a tool for optimisation.

Discernment: Blurring and visual evidence

Researchers thinking about visual evidence in the legal system address quite a variety of empirical questions but share an absorption in the ways in which the evidentiary problem is rooted in the blurring of genres. The blurring is plural: between illustration and proof, between interpretation and requiring an interpretation, between knowledge and perception, and between argument and evidence. Because genres are an intimate and essential part of the functioning of legal processes, such blurrings in turn problematize long-standing practices and the design of governance processes. Their findings are important theoretically, as well, in three ways. They show that the model of fact production processes must begin a step earlier than does the Lockean model of the fact upon which “western” and “modern” society and “science” have relied. The model must continue on beyond where Locke and those who think about the social construction of reality, such as Berger and Luckmann, stop. And “contextual” matters such as warranting, provenance, and authority must be incorporated into our model of the information production chain itself. In combination, what we are learning from research on visual evidence is thus not only invaluable for addressing the profound real-world problems identified by the authors assembled by Sandra Ristovska in this special issue of First Monday and others, but for our understanding of challenges being presented to the nature of governance itself both within and beyond the formal legal system.

Data-driven battery electrode production process modeling enabled by machine learning

Data-driven battery electrode production process modeling enabled by machine learning

Technoeconomic analysis of a fungal pretreatment-based cellulosic ethanol production

Cellulosic biomass shows great potential as feedstock for bioethanol production. Despite clear benefits in terms of greenhouse gas mitigation and bioproduct potential, the commercial production of cellulosic ethanol remains economically challenging at the current state of technology. This paper presents a technoeconomic analysis of a fungal pretreatment-based cellulosic ethanol plant with a processing capacity of 2000 tonnes of switchgrass per day. The production process model was designed and simulated using SuperPro Designer. The plant's ethanol yield, capital investment per unit capacity, and unit ethanol production cost were estimated to be 211.90 L/t of switchgrass, $ 3.60/L, and $ 1.44/L of ethanol, respectively. Fungal pretreatment was the major contributor (72%) to the total capital investment, mainly due to the large quantity of equipment required in the process. A positive net present value (NPV) was generated for the baseline model at ethanol selling price of $ 1.50/L, which increased by 5-fold for 80% glucose yield. Glucose yield was the most sensitive to NPV for all the process parameters evaluated.

A Prototype of a Domain-Specific Modeling Language for Formal Specification of a Human Worker

Abstract The application of innovative technologies that foster smart production resources’ interconnectivity alongside the virtual space that facilities to support process simulation makes the technology factor become the center of Industry 4.0. The production process modeling and simulation can be used to facilitate flexibility and automation of a shop floor. In our previous research, we have created a Domain-Specific Modeling Language (DSML) named MultiProLan, aiming to create production process models suitable for the automatic generation of executable code that enables the automatic execution of production processes. As the next step, we have proposed research on a DSML language aimed at Industry 4.0 human worker modeling. Industry 4.0 still considers workers as a cost, while favoring technological aspects over the workers’ wellbeing. Industry 5.0 complements Industry 4.0, focusing on a human-centric approach that puts core human needs and interests at the top of production processes. Based on our research proposal, here we present a blueprint of the HResModLan DSML prototype aimed at the formal specification of a human worker within Industry 5.0. Presented abstract and concrete syntaxes of the language are tested on a case study of a furniture factory to demonstrate whether they are a good base for the further development of the HResModLan language.

МОДЕЛЮВАННЯ БІЗНЕС-ПРОЦЕСІВ ДЛЯ СТВОРЕННЯ ІНФОРМАЦІЙНОЇ СИСТЕМИ УПРАВЛІННЯ ЯКІСТЮ ПІДПРИЄМСТВА БІОЕКОНОМІКИ

The article contains the results of research on modeling business processes for a bioeconomy enterprise. Modeling procedures are related to the distribution of management processes by scale and taking into account the peculiarities of production and management of the enterprise. The modeling procedure itself is necessary to determine each business process, its owners, results, the need to control and save information about its execution. Business processes of the bioeconomy can be divided into mandatory in accordance with the legal framework and reporting of all enterprises, production and management, taking into account the profile of the development of the enterprise. Modeling allows you to determine all production and information flows, control indicators. The results of modeling are a clear visualization, a description of the process. The documentation contains the sequence of all procedures, their provision and control. The proposed concept combines mandatory procedures for accounting for emissions, the implementation of environmental legislation and the introduction of a full production cycle at a bioeconomy enterprise. The adapted concept of mirrors for modeling the actual business processes of creating a balanced system of indicators for the enterprise involves the introduction of new sections, in the general projection Production. When introducing new management technologies, in particular, lean production, it is envisaged to make changes to the company's development strategy, implement procedures for restructuring production processes and retrain staff. An analysis of the life cycle of a bioeconomy enterprise shows that each of its phases requires a reassessment of strategic indicators and business processes. This approach allows you to combine the development strategy of the bioeconomy enterprise and its business processes into one whole. Known modeling techniques and tools based on information technologies can be used for modeling, analysis and optimization, provided that adapted model templates are formed for each specific enterprise. Among the known concepts of the use of business processes, the most relevant are the use of a quality management system and the formation of three mirror models of production and management processes, taking into account the features of environmental legislation and bioeconomy production processes. The proposed concept of modeling business processes can be the basis for making changes to the quality system and management of a bioeconomy enterprise.

Intelligent initial model and case design analysis of smart factory for shipyard in China

At present, due to the lack of core technology and technological innovation ability, the design technology of traditional shipyards in China is backward. The operation mode of front-line workers in shipyards is highly dangerous. There are problems that endanger the physical and mental health of workers, such as noise and paint mist pollution, which lead to low production efficiency of workers and difficulties in personnel allocation. Under this background, “shipyard labor shortage” and other similar situations followed. If the concept of smart factory is introduced into traditional shipyards, the above problems can be effectively alleviated and solved. However, due to the complexity of ship product structure processing and manufacturing, the definition of smart shipyard in China is still vague, and the research process of smart shipyard is relatively slow. Aiming at the vague functional concept of smart shipyard, the lack of research on information design and management, smart production process and smart implementation process, this paper provides a conceptual architecture design model of civil smart shipbuilding factory. The functional definition of smart shipyard is discussed, and the initial conceptual model of smart shipyard is established, including information network platform model, smart production process model and smart implementation process model. The application case verifies the above model. Firstly, the information network platform model of α group is constructed, and the group brain control system is established. Secondly, the smart production process of shipyard A under α group is established. Finally, the smart implementation process of shipyard A is designed. The case study shows that: All ships completed 100% modeling, and the pre-outfitting rate increased to about 95%. By using the wire cutting robot, the production efficiency is increased by 70%. In the smart factory mode, the 60,000 tons bulk carrier can save 35thousand dollars labor costs and 11 million dollars in shipping fuel costs each year. The shell steel plate of the 300,000 tons ore carrier is reduced by 212 tons, and the weight is reduced by 10.5%. Case shipyard A under α group using the above smart factory model can save about 0.7 million dollars labor costs per year; reduce fuel costs by about 2.2 million dollars per year; saving 2.5 million steel usage per year. In total, shipyard A reduced expenditure by about 5.4 million dollars in one year.

Spatiotemporal simulation of gas-liquid transport in the production process of continuous undulating pipelines

Large sections of gas accumulation easily form in continuously undulating liquid pipelines to impede the commissioning process affecting the safe operation of the pipeline. To solve the gas resistance and overpressure during the commissioning of continuously undulating pipeline in complex terrain, a whole process commissioning simulation model is proposed to quantitatively calculate the location and volume of gas accumulation and to monitor the pressure drop across the line in the real time. Based on a single V-shaped pipe compression process model, the proposed model considers the influence of back pressure, gas-liquid migration and integrates different process such as high point exhausting, pigging process and pump-pipe coordination. Multiple operating conditions of two real pipelines are simulated, and the results show that the proposed model has an accuracy of within ±15% for predicting the pressure along the pipeline and tracking the pigging device, indicating that the gas transport model of the continuous undulating pipeline production process has acceptable accuracy. In addition, the applicability of the proposed model under different operating condition is also verified. Specifically, the gas accumulation ratio and safety pressure of the entire pipeline are calculated by considering multiple sets of different exhaust Schemes for different flow rates, high points, and the use of pigging devices on two different real pipelines, demonstrating that the model has good generality and feasibility. Secondly, the model can calculate the pressure drop at different positions along the entire pipeline, monitor the position of the pigging device in real time, and simulate comprehensive production exhaust Schemes, demonstrating that the model has comprehensive functionality and some generality. In summary, the proposed model can provide validation and guidance for the subsequent production of related continuous undulating liquid pipelines.

Imitation Modeling of Production Processes in FlexSim Environment

Modeling systems in present day life give opportunity to find optimum ways of enterprise functioning and changes in set parameters without interference in production processes or before starting the planned production. The article studies imitation modeling use in agricultural machine-building. Brief description of FlexSim software is provided. Functional features of the system of imitation modeling allow users to identify bottlenecks, analyze statistic data, plot diagrams, etc. Imitation models of production processes on assembly line for seed-loaders are described, obtained results are analyzed and bottlenecks of the production line are identified. The authors study possibilities of optimization, which can raise productivity, for example, cutting the number of operators and introducing coordinators. The present research shows the importance of modeling and analyzing production processes in virtual environment in order to plan changes in production. Apart from modeling production processes, FlexSim program can be used for analyzing material, finance, information, staff resources, which affects managerial decision-making and strategy of industrial enterprise development.