Production Flow Research Articles

ANALYSIS OF THE CURRENT STATE OF FUNCTIONING OF COMMERCIAL PORTS OF UKRAINE

Thearticle presents the results of the study of the functioning of the ports of Ukraine through the prism of the impact of the war. A generalized analysis of the operation of Ukraine's ports from the first wave of blockade by the Russian Federation in 2022 to the current state is presented, including the actual throughput capacity of functioning ports and the nomenclature of cargo handling by Danube ports in 2023. In addition, the dynamics and structure of the supply of agricultural products by the main modes of transport are provided, where the importance of the ports of Ukraine as the main way of exporting agricultural products to ensure their arrival on international markets is highlighted; shows changes in grain and wheat prices between January 2021 and August 2023 based on International Grains Council indices. The role of the ports of the Danube region and the grain agreement for the export of cargo flows of agricultural andother products to African and Asian markets is singled out. The question of the potential for further development, development, modernization and renewal of the infrastructure of the ports of Izmail, Reni, and Ust-Dunaysk was revealed. The restoration of ship calls to the ports of Greater Odessa thanks to the formation of Ukraine's own humanitarian corridor was emphasized. The consequences of Russia's large-scale war against Ukraine in the field of port activity are grouped due to the consequences of direct and indirect influence. The risks of shipping among the countries of the Azov-Black Sea basin from the standpoint of security are summarized. It is concluded that the consequences of the protracted war scenario in Ukraine will have a negative impact not only on the port industry, but will also become a catalyst for an economic crisis in the developed economies of the world.

Multiphase flow and geomechanical behavior induced by gas production from silty-clay hydrate reservoirs through different horizontal well scenarios

Accurately predicting the coupled response behaviors during production is essential for the exploitation of gas hydrate. However, the multiphase flow and geomechanical analysis for gas production through horizontal wells in fine-grained sediments are few reported. In this study, a coupled thermal–hydraulic-mechanical (THM) model is carried out to assess the production response behaviors under different schemes. The simulation results indicate that the cumulative gas production for dual horizontal wells by depressurization assisted with hot water injection (Winj) is about 4.0 times and 2.46 times as much as that of single horizontal one and dual horizontal wells without Winj during the short-term production, respectively. However, the corresponding multiples in gas production become 2.63 and 1.40 times for the long-term production. The seafloor uplift for these three production scenarios is similar and approximately 0.06 m within 30 days. However, the ultimate seabed subsidence are 1.15 m, 1.56 m and 2.59 m, respectively. The Z-displacement undergoes approximately linear reduction with depth, while the X-displacement exhibits a gradient distribution except in the near-wellbore area. By contrast, dual horizontal wells under the hybrid production condition have the highest gas productivity and the minimal instability risk. Furthermore, the modified Fetkovich formula can effectively perform the inflow dynamic analysis of horizontal well systems by depressurization. These findings provide a reference for determining production strategies involving horizontal wells in silty clay reservoirs.

Methodology for location of leakages and unauthorized tie-ins on oil pipelines

Relevance. Pipeline transportation of oil and oil products is one of the most efficient and cost-effective modes of transport in the modern world. Despite this, this type of transport can also be environmentally hazardous in case of leakages caused, for example, by corrosion, violation of operating rules, unauthorized tie-ins. Non-operational localization and liquidation of leakages and unauthorized tie-ins is often not only the cause of significant financial losses, but also accidents and pollution of the area of varying severity and scale. Nowadays, the issue of determining the leakage that has occurred and its location in the shortest possible time remains open. In this regard, the development of new and improvement of existing methods for detecting leakages and tie-ins in pipelines is an urgent task today. Aim. To study the effect of the total head shift, which occurs when taking into account the change in the power of pumping units due to product leakage, on the accuracy of determining the localization of leakage or unauthorized tie-in; to improve the existing methods for determining the leakage coordinate taking into account the change in the total head developed by the oil pumping station. Methods. Modeling the occurrence of a leakage or unauthorized tie-in with a different percentage of product losses, constructing hydraulic slope lines with leakages of varying intensity in different coordinates, a comparative analysis of the results obtained from the considered existing methods and those proposed by the authors. Results. The authors have modeled the leakages in various coordinates and determined the possibility of the proposed method operation for finding the coordinates of leakages. They calculated as well the errors in determining the location of the tie-in or leakage, depending on the pump power drops when the product flows out of the oil pipeline. The paper introduces the formula for the localization of leakages or tie-ins, considering the change in the power of pumping units and, as a result, the total head.

Digital twin-based anomaly detection for real-time tool condition monitoring in machining

Real-time tool condition monitoring (TCM) has been emerging as a key technology for smart manufacturing. TCM can improve the dimensional accuracy of products, minimize machine tool downtime, and eliminate scraps and re-work costs. Digital twins offer new opportunities for real-time monitoring of machining processes, which can, in principle, take into account changes in machining processes and operating environments, help understand mechanisms of cutting tool wear, and improve the anomaly detection accuracy and fault diagnosis results. The present study exploits these potential advantages of digital twins and proposes a new digital twin-based anomaly detection framework for real-time TCM in machining. The framework of the digital twin consists of three parts: the physical product, the virtual product and data flow connections. Within this framework of the digital twin, the “physical product” represents the machining processes. The “virtual product” includes a real-time data-driven model representing the dynamic relationship between vibration data measured from machining processes as well as the model frequency features (MFFs)-based diagnostics for cutting tool anomaly detection. The “data flow connections” involve real-time measured vibration data and machine tool numerical controller (NC) signals providing real-time information on machine tool dynamics and various machining processes. The novelty is associated with an innovative integration of real-time data-driven modeling, MFFs extraction, and MFFs and machine tool NC signal-based tool wear diagnostics. This, for the first time, enables the concept of digital twins to be potentially applied to the TCM for complicated dynamic machining processes which, as far as we are aware of, has never been achieved before. Comprehensive field studies have demonstrated the effectiveness of the proposed digital twin-based TCM framework and its potential industrial applications.

Optimizing medical oxygen concentrators: Efficiency, flexibility, and patient-centric solutions

Medical oxygen concentrators (MOCs) play a vital role in providing oxygen therapy to patients with respiratory diseases. This paper offers a comprehensive evaluation of different adsorbents, including 13X, LiLSX, 5A, CaX, Ag-ETS-10, and AgLiLSX, utilized in MOCs. Process modeling and multi-objective optimization are conducted to assess the effectiveness of these adsorbents using the Skarstrøm cycle, employing pressure swing adsorption (PSA), vacuum swing adsorption (VSA), and pressure vacuum swing adsorption (PVSA) processes. The optimization result indicates that LiLSX is the top choice, providing medical-grade oxygen at a total product flow rate exceeding 15 SLPM. Additionally, 13X and CaX are identified as economical alternatives, particularly suitable for employment in the PSA and VSA processes, respectively. This study highlights the significance of establishing a connection between the Medical and Chemical Engineering communities through the direct incorporation of medical performance indicators, such as the fraction of inspired oxygen (FIO2), into the optimization process. The findings serve as a guide for selecting an appropriate design based on the patient’s requirements and demonstrate LiLSX’s capability to meet a diverse range of treatments, achieving FIO2 values up to 0.75. Furthermore, we explore the flexibility of MOC designs in meeting the demands of multiple patients simultaneously and propose energy-efficient design options based on patient needs. Overall, this study provides valuable insights into optimizing MOCs, ensuring effective and reliable oxygen therapy for patients, while also addressing challenges like the COVID-19 pandemic and potential global lithium scarcity.

Risk analysis of critical control points of <i>Staphylococcus aureus</i> in layer farms and egg chicken distributors

Microbiological criteria play a role in verifying the critical control points (CCP), which become part of the hazard analysis, and the CCP system that guarantees quality, considering possible danger points or stages in the food production chain. Studies about Staphylococcus aureus in chicken eggs more extensively discuss the path, source, and level of prevalence of contamination at the final distributor or consumer. Therefore, this study investigates CCP contamination of S. aureus in chicken eggs and their potential consumption, which could endanger human health from the layer farm until the final distributor. This study is critical in health, public health, and veterinary medicine for preventing and controlling consumers' security. This study done for CCP on the chain distribution of chicken eggs starts with preparing production and distribution process flow diagrams for livestock, agents/wholesalers, and retailers. Confirmation of operational production in the field/location study is based on the flow chart that has been arranged, identifying all potential dangers associated with each stage and analyzing potential risks considering every action for controlling identified hazards. The next step involves pinpointing the CCP to counteract the identified threat. An application tree decision defines the CCP, and the logical and final approach is the determination limit critical to the CCP. Analysis results in the determination of CCP contamination of S. aureus, indicating that chicken eggs, personal hands (farm workers, wholesalers, and retailers), shelf eggs, and feces are CCP on farms.

Robust modeling of material flows to end‐uses under uncertainty: UK wood flows and material efficiency opportunities

AbstractIn this study we quantify wood flows from raw materials to end‐uses for the United Kingdom in a robust way using a new material flow analysis (MFA) model with uncertainty. This is important to identify opportunities for efficiency given constraints on wood supply. We have developed a new “ProbPACTOT” MFA model which introduces a systematic method to handle mixed units during reconciliation and uncertainty in data observations, conversion factors, and process recipes. This makes it possible to track material flows all the way to end‐uses, which is otherwise difficult because the diverse materials, data types, and units used to quantify end‐products are hard to integrate into standard allocation‐based MFA models. We apply the model for the case of wood in the United Kingdom by defining 56 process recipes and reconciling 117 data observations from various sources. The results quantify upstream production and trade flows, through to 19 specific end‐uses of wood fibers. We use this to show the potential scale of savings by enhancing material efficiency; for example, if pallets were used 25% more intensively, 0.49 0.2 of wood fibers could be saved, corresponding to 4%–7% of the total soft sawnwood consumption of the United Kingdom. Judging the scale of opportunities for wood material efficiency in the United Kingdom is important domestically, and has global significance as the United Kingdom is the second largest net importer of wood products in the world. Moreover, this study proposes an important advancement in MFA giving a structure for modeling uncertain material flows up to end‐uses, applicable to any material. This article met the requirements for a gold‐gold JIE data openness badge described at http://jie.click/badges.

Assessment of robustness attributes in electronic products supply chains

To facilitate the shift to circular models, supply chains urgently need to be strengthened and made more resilient and robust. The COVID-19 pandemic generated problems in logistics activities, disrupting supply chains, including electronic products flows. In this context, based on the need to keep supply chains reliable in the face of the risks inherent in their processes, this work aims to identify the attributes for a robust supply chain and analyze the interrelationship among them using DEMATEL technique. As a result, it was observed that the agility factor, risk-oriented management, and flexibility are the most important factors, and that Information Technology and Human Resources are the most influential (causal factors) for the design of a robust supply chain in the context of electronic products.

Functional analysis of multi-scale fractures within a single fracture cluster in multi-horizontal wells

Defining the fracture function at each scale in the reservoir helps to analyze and optimize the thermal recovery properties of the reservoir. This study aims to reveal the functionalities of fractures at different scales by simulating one single fracture cluster coupled in multi-scale fractures. The geometric layout and parameter characteristics of the main fractures, branch fractures, and micro-fracture domain are investigated to speculate on their functions and influence on heat extraction performance. The results display that the main fractures and micro-fracture domain serve as the predominant channel for fluid flow. The branch fractures exert control over the flow transition from the main fractures to the micro-fracture domain, thereby influencing the generation of preferential flow. Micro-fracture domain is the primary way of fluid filtration loss. When the thickness of micro-fracture domain increased from 0 m to 20 m, the production flow rate increased from 2 kg/s to 4.2 kg/s, and the water loss ratio increased from 1 % to 4.9 %. However, expanding the micro-fracture domain can significantly enhance production flow rate and heat recovery rate at the expense of increased water loss ratio. Notably, preferential-flow-induced thermal breakthrough will not occur prematurely in this process. The permeability of branch fractures exerts the most substantial influence on the overall heat extraction, owing to its greatest impact on reservoir lifespan. These findings would provide valuable insights for optimizing fracturing morphology in multi-horizontal wells.

Optimal Strategy of Unreliable Flexible Production System Using Information System

Background: Optimization approaches and a models can be applied for critical production systems that experience equipment failure, repair delays and product quality control in order to maximize the total profit. We can cite, as an example, flexible manufacturing systems. Methods: Our methodology involves developing a decision model integrated with an information system to coordinate various system operations, ensuring timely response to customer requests. The module of the information system is provided to optimally manage the production flow and parts ordering according to machine availability. The objective is to determine the optimal order thresholds of part batches that maximize the total profit. Results: Numerical results are provided to analyze the influence of system reliability and uncertainty on decision variables, offering insights into the system’s performance and robustness. By using our method, the advancement of the flexible production systems is carried out by addressing key operational challenges and optimizing production processes for enhanced efficiency and profitability. Conclusions: To achieve this, an optimization algorithm is employed to identify optimal solutions that enhance profitability.

Effects Of Lean Manufacturing Practices On Operational Performance

Lean manufacturing is a concept of process improvement in production management which focuses on waste elimination. This paper explores relationships between lean manufacturing practices and operational performance. Using data collected from 55 manufacturing companies in Tasikmalaya city. Lean manufacturing were measured by five dimensions: production flow management, customer focus, process management, workforce management, and supplier management. Operational performance comprises four dimensions: cost, quality, lead-time, and flexibility. The findings are that all dimensions of lean manufacturing are significantly related to on operational performance. Production flow management has a higher level of significance in large enterprises compared with SMEs, whereas for customer focus there is a higher level of significance in SMEs compared with large enterprises. Process management, supplier management and workforce management have much lower level of significance for both SMEs and large enterprises.

Prediction maintenance based on vibration analysis and deep learning — A case study of a drying press supported on a Hidden Markov Model

The main objective of this paper is to describe a methodology that was developed to support maintenance decision-making methods based on equipment condition. Condition-Based Maintenance allows to increase equipment availability and maximize investments. This is mainly due to the prevention of unexpected equipment downtime. By avoiding turning on/off industrial equipment, production flows are more efficient, allowing manufacturers to improve the quality of the end-product. The industry aims more and more to correspond satisfying customer expectations. We argue that the methodology developed in this paper adds value to the existing literature, namely because the fact that it is possible to anticipate the state of an equipment without a large amount of support data. In other words, although one could find information gaps regarding the occurrence of failures, it was possible to accurately assess the state of the equipment. This approach is robust, as it can be used in distinct equipment with different sensors, making this methodology generalizable for Condition-Based Maintenance. The paper presents the validation of the preceding through a case study on drying presses in the paper industry. To do so, three states were adopted, namely: “Proper function”; “Alert state”; and “Equipment failure”. The methodology follows a series of steps, going through the collection of values from vibration sensors, imputation of values using Deep Artificial Neural Networks through on-line sensors, until reaching the last stage of classification carried out by the Hidden Markov Model. Through optimized observations from the previous steps, it was possible to define the hidden states through the Viterbi algorithm, which corresponds to the health states of the equipment. Additionally, it was possible to demonstrate that the proposed methodology can accurately characterize the condition states of the equipment based on the data obtained and can be generalized to other types of equipment.

Building resilience in the infant formula milk supply chain

In recent years, Infant Formula Milk (IFM), a vital source of nutrition for infants lacking breast milk in their first two years, has been plagued by diverse and severe global supply chain disruptions. These challenges have triggered shortages, compromised product quality, and threatened food security, leading to dire health consequences and even fatalities among infants. However, despite the criticality of IFM, current research is lacking in terms of how to build or improve the resilience of IFM supply chains. This paper presents a detailed framework for building a resilient IFM supply chain. A key pillar of this framework is a comprehensive analysis of potential hazards. Using the Hazard and Operability Analysis (HAZOP) method, 91 potential hazards were identified across the entire IFM supply chain. Subsequently, a clustering method identified 17 critical risks with irreversible consequences for infant health and supply chain flow. Finally, mitigation strategies that combine traditional approaches with 4.0 technology-enabled solutions are proposed. Adapting this framework can provide valuable insights for IFM supply chain stakeholders, enabling them to secure the vital flow of this life-sustaining product and safeguard the health and well-being of infants.

Determination of output composition in reaction-advection-diffusion systems on network reactors

We consider reaction-transport processes in open reactors in which systems of first order reactions involving a number of gas species and solid catalysts can occur at localized active regions. Reaction products flow out of the reactor into vacuum conditions and are collected at an exit boundary. The output composition problem (OCP) is to determine the composition (molar fractions) of the collected gas after the reactor is fully emptied. We provide a solution to this problem in the form of a boundary-value problem for a system of time-independent partial differential equations. We then consider network-like reactors, which can be approximated by a network consisting of a collection of nodes and 1-dimensional branches, with reactions taking place at nodes. For these, the OCP can be solved in a simple and effective way, giving explicit formulas for the output composition as a function of the reaction coefficients and parameters associated with the geometric configuration of the system. The possibility of determining reaction coefficients from experimentally obtained output composition is shown in the case of one chemically active node.

The global production pattern of the semiconductor industry: an empirical research based on trade network

Semiconductors are an important electronic component and play a central role in many industrial fields, whose production system is spread all over the world, involving trade in many raw materials, mechanical equipment, and finished products. Comprehending a broad global production picture of the semiconductor industry can be an arduous task. To tackle this complexity, the social network analysis method was used to capture the flows of products between economies in the semiconductor industrial chain. This study analyzed the evolution of the trade pattern of four key commodities in the semiconductor industrial chain, with a focus on identifying the status of major economies in the global semiconductor trade system. Additionally, the influencing factors of the formation of the trade networks were explored by using the Exponential Random Graph Model. The results showed that: (1) From 2001 to 2019, the import and export trade pattern of four key commodities in the semiconductor industrial chain has shown the characteristics of “rising in the east and decreasing in the west”, but the change range shows strong commodity heterogeneity, the change of the spatial pattern of integrated circuits trade is the most significant, and the integrated circuits trade proportion of Asian economies has increased hugely with more than 80%. (2) The trade connectivity of various commodities in the semiconductor industrial chain has increased, upstream support products with high technical requirements such as wafers and equipment have the lowest average degree and weak trade liquidity, and the average degree of trade network of packaging materials and integrated circuits is relatively high, with strong trade liquidity and closer and more prosperous trade connections. (3) From 2001 to 2019, the “core-periphery” system of global semiconductor industry trade has changed significantly, with the core circle undergoing obvious iterative reorganization. for example, China and Singapore have achieved status improvement to the core circle in the base materials trade network, while Malaysia has been squeezed into the semi-peripheral circle. (4) The formation of trade networks of various commodities in the semiconductor industrial chain was driven by three aspects: network self-organization, exogenous endowment attribute, and exogenous network embeddedness. Among them, the influence of the technological innovation level of economies on different commodity trade networks showed heterogeneous.

Modeling and simulation of a novel chemical process for clean hydrogen and power generation

The present work aims to develop a novel chemical process for clean hydrogen and power production and simulate it accordingly through a unique thermodynamic equilibrium model. This particular process is based on a partial oxidation of hydrogen sulfide (H2S) at superadiabatic conditions to study its respective chemical products. The simulation of superadiabatic partial oxidation of H2S is developed through the present model for the first time in the Aspen Plus. The process is further studied by varying different operating variables with an overall goal of optimizing the H2S conversion into hydrogen. The developed model predicts a satisfactory H2 production flow rate coupled with a low-sulfur dioxide (SO2) output within the superadiabatic partial oxidation regime at an operating pressure below 0.5 bar. The H2S conversion into H2 is then found to be 23.48 % at 0.25 bar. The overall energy and exergy efficiencies of the system are found to be 87.51 % and 70.08 % respectively. The dissociation of H2S in the presence of stoichiometric air results in elemental sulfur and hydrogen production rates of 0.0019 kg/s and 0.0012 kg/s, respectively.

Innovative Techniques for Optimizing Supply Chain Operations

Supply chain management is an approach used by firms to ensure that their business can be highly effective, and profitable and that operations run smoothly. This involves managing the movement of raw materials inwards and finished goods outwards. Logistics is a key component of this. It also involves managing the flow of products between companies, which can involve the movement of products between a manufacturer, a wholesaler, and a retailer. Supply chain management is therefore the integration of these flows between companies. Several innovative techniques can be used to optimize supply chain operations, particularly given recent advances in information technology. The function of logistics is known as activities that are related to the flow of products between companies, such as the transportation and warehousing of goods. Activities that take place within companies, such as inventory management and materials handling, are not considered to be logistical activities but part of the supply chain. The level of interest in supply chain management has risen quite dramatically over the last few years. This is partly due to advances in information technology, which have enabled closer integration of the supply chain. As well as increasing competition between companies, on both a national and an international level, has led to an increasing emphasis on the need for companies to concentrate on their core competencies, and to look to outside suppliers to provide other goods and services. This has led to the increased use of external suppliers.

Operations Management: Roles and Duties of Suppliers and Shippers in Supply Chain Management

In order to enhance competitiveness, companies must prioritize product customization, high quality, cost reduction, and distribution speed. To achieve these goals, it is essential to focus on supply chain management. Supply chain management is defined as the integrated process of obtaining materials and services, transforming them into intermediate and final products, and delivering them to customers. This involves activities such as purchasing and outsourcing, in addition to other functions that are crucial for the relationship between suppliers and distributors. The primary objectives of supply chain management (SCM) are the timely delivery of products to consumers, cost reduction, and the improvement of outcomes across the entire supply chain (as opposed to a single company). Additionally, SCM facilitates the reduction of time, the centralization of planning and distribution activities, and the optimization of resources. Given the current circumstances, the application of SCM is particularly advantageous, as it enables the management of the flow of goods or products in a supply chain.

Rapid synthesis of Mn-doped NiFe2O4 nanosheet arrays for high-performance hybrid supercapacitors

This research presents an innovative approach to the in-situ fabrication of Mn-doped NiFe2O4 (Mn-NiFe2O4) nanosheet arrays directly on nickel foam substrates. The formation of precursors on the nickel foam substrates is achieved through spontaneous corrosion, followed by a thermal treatment to form the Mn-NiFe2O4 nanosheet arrays. The material's structure and morphology were thoroughly examined, revealing that the addition of Mn transforms the nanoporous structure on the nickel foam into a nanosheet structure. The average thickness of the nanosheets is 30 nm, and their primary composition is Mn-doped NiFe2O4. The resulting highly porous structure of these nanosheets provides numerous active sites and effective electron and ion diffusion channels, thereby increasing charge density and mechanical stability. Electrochemical assays show that the areal-specific capacity of the synthesized electrode material reaches 4.34 C cm−2 (areal-specific capacitance is 8.68 F cm−2) at 1 mA cm−2. Notably, the constructed hybrid supercapacitor achieves a power density of 544 µW cm−2 at an energy density of 390 µWh cm−2. Furthermore, capacitance retention is 95.2% after 5000 charging cycles. Additionally, the assembled device delivers robust and sustained energy output for LED displays and electric toy cars. This method streamlines the production flow of electrode materials, reducing energy consumption while significantly enhancing the areal capacitance of supercapacitors. The assembled hybrid supercapacitor structure diagram and the assembled devices provide power sources for electric toy cars and LED displays.

Optimization of the Factory Layout and Production Flow Using Production-Simulation-Based Reinforcement Learning

Poor layout designs in manufacturing facilities severely reduce production efficiency and increase short- and long-term costs. Analyzing and deriving efficient layouts for novel line designs or improvements to existing lines considering both the layout design and logistics flow is crucial. In this study, we performed production simulation in the design phase for factory layout optimization and used reinforcement learning to derive the optimal factory layout. To facilitate factory-wide layout design, we considered the facility layout, logistics movement paths, and the use of automated guided vehicles (AGVs). The reinforcement-learning process for optimizing each component of the layout was implemented in a multilayer manner, and the optimization results were applied to the design production simulation for verification. Moreover, a flexible simulation system was developed. Users can efficiently review and execute alternative scenarios by considering both facility and logistics layouts in the workspace. By emphasizing the redesign and reuse of the simulation model, we achieved layout optimization through an automated process and propose a flexible simulation system that can adapt to various environments through a multilayered modular approach. By adjusting weights and considering various conditions, throughput increased by 0.3%, logistics movement distance was reduced by 3.8%, and the number of AGVs required was reduced by 11%.