ISSN: 3005-8066 (Online)
3005-8058 (Print)
The Fourth Industrial Revolution, known as Industry 4.0 (I4.0), has introduced a completely disruptive pace compared to the rhythm of the three previous industrial revolutions. With a wide range of technologies, design principles, and a high potential to replace the human workforce, this industry presents aspects that urgently require greater attention. With a purpose close to meeting this need, Industry 5.0 (I5.0) emerges, a milestone not yet registered with historical facts but with great hopes for positive changes. While I4.0 maintains design principles for its complete activity, I5.0 has a supporting tripod for its operation. As I5.0 is still perceived as an evolutionary character of I4.0, it is expected that for the time being, it will use these same design principles for its activity and may later include new principles. Based on this context, this article seeks to contextualize, in a descriptive way, the functioning of design principles 4.0 for the imminent industrial context 5.0. The article uses a conceptual approach based on previously published literature on the subject of design principles in I4.0. Although the characteristics of I5.0 are not yet fully known, it is assumed that it has a more refined character than I4.0, so that points that presented a positive, significant, and already consolidated result are maintained for the new model. The distinctive feature of this article is its presentation of a textual analysis that breaks down the potential contributions of design principles in relation to the three core values of Industry 5.0: Sustainability, Human-Centricity, and Resilience.
Intelligent factories provide flexible and adaptive production processes, offering significant competitive advantages to manufacturers and are widely studied in industrial production. Information technology is recognized as a key factor influencing the production efficiency and intelligence of Intelligent factories. However, current research has primarily focused on the operational processes of intelligent factories, with limited analysis of information technology. To address this gap, this paper conducts a bibliometric analysis of information technology in intelligent factories, along with a review of its development and applications. Firstly, the data collection and visualization methods of bibliometrics are introduced. Secondly, bibliometric analyses are performed using platforms such as VOSviewer and Scimago to investigate co-authorship, co-citation, and contributions from countries and institutions in the field of information technology for intelligent factories. Finally, a framework for information technology in intelligent factories is established, summarizing its development in terms of information acquisition, transmission, processing, management, and control. This paper aims to assist scholars in understanding the development trends of intelligent factory technology and enhancing the informatization level of intelligent factories.
As a typical high-performance alloy, the excellent mechanical properties and stringent processing requirements of 30CrMnSiNi2A high-strength steel pose great challenges to high-quality and efficient processing. Currently, researchers have proposed methods such as improving cutting tool performance, minimal quantity lubrication (MQL), and applying external energy field to assist processing. However, due to the unregulated material properties, the further improvement of surface quality is limited, and there are problems of phase change and thermal damage in laser processing. Cold plasma jet (CPJ) is rich in active particles and has a low macroscopic temperature. It can effectively regulate material properties without causing serious surface damage. Therefore, a new 30CrMnSiNi2A machining approach adopting CPJ is proposed to improve the cutting process. The mechanism of its action on material properties and cutting process is revealed based on single-grain diamond scratching tests and micro-milling tests. The results show that CPJ can promote material fracture and improve material removal efficiency. The material removal efficiency R at 400 mN is increased from 0.433 before treatment to 0.895. Under the optimal processing parameters (feed speed Vf = 800 μm/s, spindle speed n = 40,000 rpm, and milling depth ap = 5 μm), compared with dry micro-milling, the cutting forces Fz, Fx and Fy in CPJ-assisted micro-milling are reduced by 26.5%, 24.8% and 31.3%, respectively. The surface roughness Sa is reduced by 19.3%, and the phenomena of plastic flow and burr are suppressed. The CPJ-assisted machining process proposed in this paper can regulate the material properties to improve the cutting process without causing serious damage to the material, providing a new approach for achieving high-quality and efficient processing of 30CrMnSiNi2A.
This paper reports, for the first time in the literature, a preliminary study to investigate the feasibility of utilizing waste algae powder (byproducts of biofuel manufacturing from algae) in binder jetting 3D printing to produce environmentally friendly products. In this study, the algae powder’s morphology and particle size distribution were characterized using scanning electron microscopy and particle size analyzer, respectively, and the flowability was assessed through apparent density and repose angle. The algae powder successfully printed the cylindrical, cubic, and gyroid parts on a binder jetting 3D printer. Results show that it is feasible to print parts with binder jetting 3D printing utilizing waste algae powder. The use of waste algae powder in additive manufacturing offers a novel approach to upcycling waste algae powder into valuable products for various applications such as packaging and construction.
Recently, onboard sensing and support devices have been used for the well-being of humans, animals, birds, plants and, more generally, biodiversity. The performance of these tools is closely linked to their electromagnetic environment, mainly artificially created by humans. Therefore, the presence of electromagnetic radiation linked to human activities near such tools constitutes a threat. The intelligent and sustainable manufacturing of these tools, which makes it possible to face such a threat, can be achieved through their design and optimization. This commentary aims to highlight the interaction of artificial electromagnetic radiation with onboard health tools involving living tissues in urban biodiversity (One Health concept) and the intelligent and sustainable construction and protection (Responsible Attitude concept) of these tools. The manuscript presents an overview of onboard devices, possible effects of electromagnetic radiation, durable construction and shielding, and analysis of electromagnetic compatibility integrity control. The main outcome of this contribution regarding sustainably designed onboard devices is that numerical analysis tools of electromagnetic fields could efficiently verify their integrity and the behavior of their necessary smart shields. These different themes are associated with examples of literature.
Lithium batteries pave way for rapidly reducing greenhouse gas emissions. Still there are concerns associated with battery sustainability, such as the supply of key battery materials like cobalt, nickel and carbon emissions related to their manufacture. While LiMn2O4 spinel is a common cathode material for Li-ion batteries that remove Co and Ni, studies on over-stoichiometric variants and their behavior across a broad potential range may be limited. Research in this area could provide valuable insights into the performance, stability and electrochemical characteristics of such cathodes, offering potential benefits for the development and optimization of Li-ion battery technologies. This study investigates the electrochemical behavior of Li-rich Li1+yMn2−yO4−δ (LMO, y ≈ 0.03, δ ≈ 0.01) spinel as a cathode in Li-ion batteries, focusing on the phenomenon of extra capacity under the extended operating voltage 1.5–4.8 V vs. Li+/Li. The nanostructured LMO sample synthesized by sol-gel method and calcined at 900 °C is characterized by X-ray diffraction, scanning and transmission electron microscopy and surface area measurements. The Li-rich spinel electrode delivers a specific discharge capacity of 172 mAh g−1 at 1st cycle. It retains 123 mAh g−1 at the 100th cycle (71.5% capacity retention) at current density of 100 mA g−1 current density (i.e., ~0.7 C rate). An excellent stability is obtained in the 1.5–4.8 V potential window, with a discharge capacity of 77 mAh g−1 after 500 cycles at the same current density, owing to the reduction of the Jahn-Teller effect by Li doping. These results contrast with the specific capacity of 85 mAh g−1 (1st cycle) and the capacity retention of 54.3% after 100 cycles, obtained when the cell operates in the narrow potential range of 3.0–4.5 V.
The scientific article analyzes the dynamics of textile industry production in the USSR and the Russian Federation from 1985 to 2022 years.The article provides a fairly complete overview of modern methods of forecasting the development of objects, mainly based on time series analysis, including issues of forecasting cyclic and discontinuous processes, forecasting multidimensional objects with a correlated system of indicators. Authors calculate the forecast until 2026 year based on a bank of mathematical forecasting models implementing various monotonic nonlinear transformations both along the ordinate axis and along the abscissa axis. The criterion of the minimum variance of the forecast error was used as a criterion for selecting a specific model from the bank. The scientific value of the article lies in the fact that, for the first time, it offers a criterion for choosing a mathematical model from a set of them, which uses the minimum estimate of the variance of forecast errors for this model. This work can be considered a step towards the creation of artificial intelligence since the selection of the optimal model for a specific time series allows to obtain a training sample for it, which is fundamentally impossible to obtain without it.
Laser Additive Manufacturing (LAM), an avant-garde technology in manufacturing, harnesses the precision of laser energy to fabricate intricate parts through the meticulous process of melting and subsequently depositing layers of metal powders. Among the esteemed materials employed, 316L stainless steel (316L SS) stands out for its unparalleled corrosion resistance, exceptional high-temperature tolerance, and remarkable creep strength, making it a ubiquitous choice in the aerospace, medical, and nuclear power sectors. LAM has distinguished itself in the fabrication of intricate 316L SS components, yet enhancing the metallurgical bonding strength within these structures remains a pivotal area of ongoing research. This research endeavor delves into the intricate microstructure and mechanical properties that characterize the interface between the LAM-produced 316L SS cladding layer and its substrate, further investigating how varying laser energy densities (E) subtly influence these properties within the additive manufactured components. Remarkably, the interface region exhibits a tensile strength of 615.1 MPa, surpassing that of both the deposited layer and the substrate by 5.4% and 7.4% respectively, underscoring a robust bond between the two layers. This investigation not only sheds light on the unique process capabilities and performance merits of LAM in crafting 316L SS cladding layers but also pioneers novel approaches and conceptual frameworks for bolstering the metallurgical bonding strength of this esteemed material. As such, it constitutes a treasure trove of insights for subsequent research endeavors and practical applications across related disciplines.
Technological innovations, education, business and society change quickly and often unpredictably. The fusion of artificial intelligence (AI), machine learning, augmented reality (AR), virtual reality (VR) and augmented reality (XR) opens a new era in which work, production, communication and thought processes are massively transformed. In this context, the challenge arises: How can small and medium-sized enterprises (SMEs) adapt to this accelerated change? This study highlights a path forward and introduces the concept of “SME 5.0” or “Hybrid SME” or “SME of Tomorrow” as a comprehensive solution to address the complexities of the digital age. In this integrated exploration of the X.0 Wave Theory and SME 5.0 Concept, the framework for human civilization’s evolution and technological shifts converges with a practical roadmap for small and medium-sized enterprises (SMEs) navigating the dynamic digital landscape. Acknowledging transformative waves in technology, economics, and societal structures within the X.0 Wave Theory, the study accentuates the ongoing nature of these shifts. It advocates for a long-term perspective, urging policymakers and industry leaders to consider potential future scenarios to devise strategies fostering innovation, competitiveness, and privacy safeguards. Simultaneously, the study introduces SME 5.0 as a holistic solution for SMEs, aligning with the transformative success envisioned by the X.0 Wave Theory. Proposing the Seven Pillars of Sustainability (7PS) framework tailored to SMEs, the concept emphasizes digitalization and sustainable technology. The title, “Harmonizing the X.0 Wave Theory and SME 5.0 Concept”, encapsulates the synergy between theoretical underpinnings and practical solutions. The subtitle, “Fostering Sustainable Collaboration, 7PS Engineering, and Overcoming Legal Challenges in the Digital Age”, provides a glimpse into the study’s focus on practical implications, sustainability, engineering, and legal considerations for SMEs in the rapidly evolving digital era.
This manuscript describes the research path when extending a maturity model. The initial model—ManuMaturity—was for manufacturing companies aiming beyond Industry 4.0. The extended OSME model covers data sharing within a supply chain, an open innovation ecosystem and sustainable manufacturing. The OSME maturity model has five maturity levels: traditional factory, modern factory, agile factory, agile cognitive factory and agile cognitive industry and seven dimensions (such as infrastructure, data, customer, business model, employee, sustainability and processes). The tool was experimented with in manufacturing companies on two occasions: with a set of manufacturing companies and a group of companies. In both cases, feedback was gathered from the respondents. The article follows the maturity assessment development phases such as scope, design, populate, test, deploy and maintain, and reports the software implementation of the maturity tool. With the help of the developed maturity model and the tool, it was possible to make assessments in case companies, where the tool and its results were commented mostly positively. The tool can be applied in various ways. For example, a group of people can jointly submit their common understanding and have a thorough discussion or a group of company representatives submit their responses and the variation is discussed afterwards.
Digital twin technology develops virtual models of objects digitally, simulating their real-world behavior based on data. It aims to reduce product development cycles and costs through feedback between the virtual and real worlds, data fusion analysis, and iterative decision-making optimization. Traditional manufacturing processes often face challenges such as poor real-time monitoring and interaction during machining, difficulties in diagnosing equipment failures, and significant errors in machining. Digital twin technology offers a powerful solution to these issues. Initially, a comprehensive review of the research literature was conducted to assess the current research scope and trends. This was followed by an explanation of the basic concepts of digital twins and the technical pathway for integrating digital twins into intelligent manufacturing including outlining the essential technologies for creating a system of interaction between the virtual and real worlds, enabling multimodel fusion, data sensing, algorithm-based prediction, and intelligent decision-making. Moreover, the application of digital twins in intelligent manufacturing throughout the product life cycle was detailed, covering product design, manufacturing, and service stages. Specifically, in the manufacturing phase, a model based on heat conduction theory and visualization was used to construct a time-varying error model for the motion axis, leading to experiments predicting the time-varying error in the hole spacing of a workpiece. These experiments achieved a minimum prediction error of only 0.2 μm compared to the actual error. By compensating for time-varying errors in real time, the variability in the hole spacing error decreased by 69.19%. This paper concludes by summarizing the current state of digital twins in intelligent manufacturing and projecting future trends in key technologies, application areas, and data use, providing a basis for further research.
In the manufacturing process, in addition to the properties of material itself, the quality of a product is directly related to the cutting process. Cutting force and cutting heat are two crucial factors in cutting processing. Researchers can analyze various signals during cutting process, such as cutting force signal, vibration signal, temperature signal, etc., which can regulate force and temperature, optimize the cutting process, and improve product quality. Therefore, it is very important to pay attention to various signals in cutting process. Meanwhile, good-quality signal data sets will greatly reduce time, resource and labor costs for subsequent use or analysis of researchers. Therefore, how to collect high-quality signals effectively and accurately is the first step. At present, researchers prefer to use various sensors to collect signals. With the advancement of science and technology, intelligent tool holder appears in researchers’ vision. It integrates multiple systems such as sensors, data collection, data transmission, and power supply on the tool holder. It replaces traditional wired sensors, and it is highly interactive with CNC machine tools. This paper will carry out a systematic review and prospect from three aspects: the structural design of the intelligent tool holder, the signal monitoring technology of the intelligent tool holder, and the tool condition monitoring of the intelligent tool holder.
Providing rapid, efficient, inexpensive, and resilient solutions is an eminent and urgent need for emergency relief conditions, mainly and increasingly driven by the impacts of climate change. Under such disastrous circumstances, the current practice involves preparation, dispatching and managing significant amounts of materials, resources, manpower, and transportation of basic needs, which can be hindered remarkably by infrastructure damage and massive loss of lives. However, an emerging technology known as 3D printing (3DP) can play a significant role and rapidly bring unlimited innovative solutions in such conditions with much lesser resources to meet the necessities of large populations affected. Considering the recent progress of 3DP technology and applications in different industrial and consumer sectors, this study aims to provide an analysis of the status and current progress of 3DP technology in various fields to understand and present its potential for readiness and response to disasters, emergency and relief need driven by climate change. Secondly, this study also presents a sustainability assessment of 3DP technology for such cases to evaluate economic, environmental, and social impacts. Finally, policies and strategies are suggested to adapt 3DP technology in different sectors to prepare for large-scale emergencies.
Nickel-based alloys has important application value in modern industrial field, but there are a lot of problems that are difficult to solve in traditional processing, and it is a typical difficult-to-process material. In order to improve the machinability of nickel-based alloys, scholars try to use a variety of non-traditional processing methods to explore and study the processing of nickel-based alloys. In these studies, ultrasonic vibration assisted processing technology and minimum quantity lubrication (MQL) processing technology can achieve remarkable results. The intermittent separation cutting characteristics of ultrasonic vibration assisted processing technology can improve the processing quality by changing the tool path, while minimum quantity lubrication processing technology can improve the lubrication effect of cutting, combining ultrasonic vibration assisted MQL processing leverages the benefits of both methods, resulting in improved machinability and expanded application of nickel-based alloys. Summarize the current research status on the machining mechanism of nickel-based alloys assisted by ultrasonic vibration and micro lubrication, and anticipate its developmental trends. This provides a reference for future research on the efficient machining mechanisms and practical applications of nickel-based alloys.
The wheel hub is an important part of the automobile, and machining affects its service life and driving safety. With the increasing demand for wheel productivity and machining accuracy in the automotive transport sector, automotive wheel production lines are gradually replacing human production. However, the technical difficulties of conventional automotive wheel production lines include insufficient intelligence, low machining precision, and large use of cutting fluid. This paper aims to address these research constraints. The intelligent, sustainable manufacturing production line for automobile wheel hub is designed. First, the machining of automotive wheel hubs is analyzed, and the overall layout of the production line is designed. Next, the process equipment system including the fixture and the minimum quantity lubrication (MQL) system are designed. The fixture achieves self-positioning and clamping functions through a linkage mechanism and a crank–slider mechanism, respectively, and the reliability of the mechanism is analyzed. Finally, the trajectory planning of the robot with dual clamping stations is performed by RobotStodio. Results show the machining parameters for a machining a wheel hub with a diameter of 580 mm are rotational speed of 2500 rpm, cutting depth of 4 mm, feed rate of 0.5 mm/r, and minimum clamping force of 10881.75 N. The average time to move the wheel hub between the roller table and each machine tool is 27 s, a reduction of 6 s compared with the manual handling time. The MQL system effectively reduces the use of cutting fluid. This production line can provide a basis and reference for actual production by reasonably planning the wheel hub production line.
With the development of the manufacturing industry, there is an increasing demand for high-efficiency processing, high-precision processing, and high-temperature processing. The characteristics of ceramic tools, such as high hardness and wear resistance, make them suitable for high-precision processing. Additionally, their excellent high temperature resistance perfectly meets the requirements of high temperature processing. However, ceramic tools have a relatively low strength and are prone to breakage, which limits their application in some high-strength machining fields. Their low toughness and brittleness also lead to easy cracking and reduced tool life, resulting in frequent tool changes that further limit processing efficiency. Therefore, improving the service life of ceramic tool materials is crucial to enhance processing efficiency and achieve significant economic benefits. With the development of material science, solid additives with toughening and strengthening properties have greatly improved the performance of ceramic tool materials and given ceramic tools new life-enhancing properties, such as lubrication and repair. By utilizing the combined action of one or more solid additives and employing surface coating technology, the service life of ceramic cutting tools is significantly extended. This makes the application of ceramic tools in industrial cutting more and more widely, and the demand is also growing rapidly. However, the mechanism and methods of various solid additives to increase the life of ceramic tool materials have not been systematically reviewed. The analysis of the composition and functional properties of ceramic tool materials was used as a basis to summarize the mechanism by which various solid additives improve the service life of ceramic tool materials, and to provide points for attention in their use. The aim is to assist researchers in designing and preparing new ceramic tool materials that can meet processing requirements. Finally, the research status, challenges, and prospects of enhancing the service life of ceramic cutting tools with solid additives are summarized, providing a foundation for further research.
Despite that ocean current energy is one of the promising sources of electricity produced in the ocean, the development of ocean current energy is far behind compared to other ocean energy due to the low efficiency and high cost of installation and maintenance. Among many converting devices, the Savonius turbine has been proven to be effective and competitive in harnessing ocean current energy. The primary purpose of the present study is to search for the optimum shape of a Savonius rotor based on CFD simulation (Star-CCM+). A Savonius turbine composed of two rotating cup-shaped rotors is selected as a numerical model. We focus on the effect of two geometry parameters such as the overlap and gap ratio on the power coefficient. Throughout the parametric study, the shape of a Savonius rotor affects the power performance, and two geometry parameters with an overlap ratio of 0.15 and a gap ratio of −0.03 are found to be the optimum design. It demonstrates stable performance within the wide TSR (Tip Speed Ratio) range of 0.6 to 1.6, with the maximum power coefficient Cp of 0.34 achieved at a TSR of 0.8. According to the numerical results based on the new CFD model, the presence of a bottom wall does not significantly affect the performance of a Savonius turbine. It means that the present unbounded CFD model can be acceptable in the initial design stage for the determination of the geometry parameters of a Savonius turbine.
This research paper explores the financial adoption challenges of the Industrial Internet of Things (IIoT) in industry. Previous studies have mainly concentrated on designing affordable IIoT devices, reducing operational costs, and creating conceptual frameworks to assess the financial impact of IIoT adoption. The objective of this paper is to investigate whether IIoT adoption’s financial benefits outweigh the initial costs in small and medium-sized enterprises (SMEs). The data from the Industrial Assessment Centers (IAC) database were analyzed, focusing on 62 U.S. manufacturing SMEs across 10 states and 25 Standard Industrial Classifications (SICs), evaluating projected IIoT implementation costs and anticipated cost savings. Results from the analyses reveal that statistically, the difference between implementation costs and savings is significant at a 95% confidence level. Practically, this indicates that SMEs, despite facing high initial costs, can expect these investments to be counterbalanced by substantial savings. From an engineering perspective, this finding raises awareness among SMEs that, beyond overcoming financial barriers, IIoT technologies serve as a strategic enhancement to operational efficiency and competitive positioning. This study acknowledges the limitations including reliance on estimated projections and a narrow industry focus. Future research should broaden the sample and explore the lifecycle costs of IIoT.
Lithium batteries pave way for rapidly reducing greenhouse gas emissions. Still there are concerns associated with battery sustainability, such as the supply of key battery materials like cobalt, nickel and carbon emissions related to their manufacture. While LiMn2O4 spinel is a common cathode material for Li-ion batteries that remove Co and Ni, studies on over-stoichiometric variants and their behavior across a broad potential range may be limited. Research in this area could provide valuable insights into the performance, stability and electrochemical characteristics of such cathodes, offering potential benefits for the development and optimization of Li-ion battery technologies. This study investigates the electrochemical behavior of Li-rich Li1+yMn2−yO4−δ (LMO, y ≈ 0.03, δ ≈ 0.01) spinel as a cathode in Li-ion batteries, focusing on the phenomenon of extra capacity under the extended operating voltage 1.5–4.8 V vs. Li+/Li. The nanostructured LMO sample synthesized by sol-gel method and calcined at 900 °C is characterized by X-ray diffraction, scanning and transmission electron microscopy and surface area measurements. The Li-rich spinel electrode delivers a specific discharge capacity of 172 mAh g−1 at 1st cycle. It retains 123 mAh g−1 at the 100th cycle (71.5% capacity retention) at current density of 100 mA g−1 current density (i.e., ~0.7 C rate). An excellent stability is obtained in the 1.5–4.8 V potential window, with a discharge capacity of 77 mAh g−1 after 500 cycles at the same current density, owing to the reduction of the Jahn-Teller effect by Li doping. These results contrast with the specific capacity of 85 mAh g−1 (1st cycle) and the capacity retention of 54.3% after 100 cycles, obtained when the cell operates in the narrow potential range of 3.0–4.5 V.
Digital twin technology develops virtual models of objects digitally, simulating their real-world behavior based on data. It aims to reduce product development cycles and costs through feedback between the virtual and real worlds, data fusion analysis, and iterative decision-making optimization. Traditional manufacturing processes often face challenges such as poor real-time monitoring and interaction during machining, difficulties in diagnosing equipment failures, and significant errors in machining. Digital twin technology offers a powerful solution to these issues. Initially, a comprehensive review of the research literature was conducted to assess the current research scope and trends. This was followed by an explanation of the basic concepts of digital twins and the technical pathway for integrating digital twins into intelligent manufacturing including outlining the essential technologies for creating a system of interaction between the virtual and real worlds, enabling multimodel fusion, data sensing, algorithm-based prediction, and intelligent decision-making. Moreover, the application of digital twins in intelligent manufacturing throughout the product life cycle was detailed, covering product design, manufacturing, and service stages. Specifically, in the manufacturing phase, a model based on heat conduction theory and visualization was used to construct a time-varying error model for the motion axis, leading to experiments predicting the time-varying error in the hole spacing of a workpiece. These experiments achieved a minimum prediction error of only 0.2 μm compared to the actual error. By compensating for time-varying errors in real time, the variability in the hole spacing error decreased by 69.19%. This paper concludes by summarizing the current state of digital twins in intelligent manufacturing and projecting future trends in key technologies, application areas, and data use, providing a basis for further research.utf-8
In the manufacturing process, in addition to the properties of material itself, the quality of a product is directly related to the cutting process. Cutting force and cutting heat are two crucial factors in cutting processing. Researchers can analyze various signals during cutting process, such as cutting force signal, vibration signal, temperature signal, etc., which can regulate force and temperature, optimize the cutting process, and improve product quality. Therefore, it is very important to pay attention to various signals in cutting process. Meanwhile, good-quality signal data sets will greatly reduce time, resource and labor costs for subsequent use or analysis of researchers. Therefore, how to collect high-quality signals effectively and accurately is the first step. At present, researchers prefer to use various sensors to collect signals. With the advancement of science and technology, intelligent tool holder appears in researchers’ vision. It integrates multiple systems such as sensors, data collection, data transmission, and power supply on the tool holder. It replaces traditional wired sensors, and it is highly interactive with CNC machine tools. This paper will carry out a systematic review and prospect from three aspects: the structural design of the intelligent tool holder, the signal monitoring technology of the intelligent tool holder, and the tool condition monitoring of the intelligent tool holder.utf-8
Providing rapid, efficient, inexpensive, and resilient solutions is an eminent and urgent need for emergency relief conditions, mainly and increasingly driven by the impacts of climate change. Under such disastrous circumstances, the current practice involves preparation, dispatching and managing significant amounts of materials, resources, manpower, and transportation of basic needs, which can be hindered remarkably by infrastructure damage and massive loss of lives. However, an emerging technology known as 3D printing (3DP) can play a significant role and rapidly bring unlimited innovative solutions in such conditions with much lesser resources to meet the necessities of large populations affected. Considering the recent progress of 3DP technology and applications in different industrial and consumer sectors, this study aims to provide an analysis of the status and current progress of 3DP technology in various fields to understand and present its potential for readiness and response to disasters, emergency and relief need driven by climate change. Secondly, this study also presents a sustainability assessment of 3DP technology for such cases to evaluate economic, environmental, and social impacts. Finally, policies and strategies are suggested to adapt 3DP technology in different sectors to prepare for large-scale emergencies.utf-8
The wheel hub is an important part of the automobile, and machining affects its service life and driving safety. With the increasing demand for wheel productivity and machining accuracy in the automotive transport sector, automotive wheel production lines are gradually replacing human production. However, the technical difficulties of conventional automotive wheel production lines include insufficient intelligence, low machining precision, and large use of cutting fluid. This paper aims to address these research constraints. The intelligent, sustainable manufacturing production line for automobile wheel hub is designed. First, the machining of automotive wheel hubs is analyzed, and the overall layout of the production line is designed. Next, the process equipment system including the fixture and the minimum quantity lubrication (MQL) system are designed. The fixture achieves self-positioning and clamping functions through a linkage mechanism and a crank–slider mechanism, respectively, and the reliability of the mechanism is analyzed. Finally, the trajectory planning of the robot with dual clamping stations is performed by RobotStodio. Results show the machining parameters for a machining a wheel hub with a diameter of 580 mm are rotational speed of 2500 rpm, cutting depth of 4 mm, feed rate of 0.5 mm/r, and minimum clamping force of 10881.75 N. The average time to move the wheel hub between the roller table and each machine tool is 27 s, a reduction of 6 s compared with the manual handling time. The MQL system effectively reduces the use of cutting fluid. This production line can provide a basis and reference for actual production by reasonably planning the wheel hub production line.utf-8
This research paper explores the financial adoption challenges of the Industrial Internet of Things (IIoT) in industry. Previous studies have mainly concentrated on designing affordable IIoT devices, reducing operational costs, and creating conceptual frameworks to assess the financial impact of IIoT adoption. The objective of this paper is to investigate whether IIoT adoption’s financial benefits outweigh the initial costs in small and medium-sized enterprises (SMEs). The data from the Industrial Assessment Centers (IAC) database were analyzed, focusing on 62 U.S. manufacturing SMEs across 10 states and 25 Standard Industrial Classifications (SICs), evaluating projected IIoT implementation costs and anticipated cost savings. Results from the analyses reveal that statistically, the difference between implementation costs and savings is significant at a 95% confidence level. Practically, this indicates that SMEs, despite facing high initial costs, can expect these investments to be counterbalanced by substantial savings. From an engineering perspective, this finding raises awareness among SMEs that, beyond overcoming financial barriers, IIoT technologies serve as a strategic enhancement to operational efficiency and competitive positioning. This study acknowledges the limitations including reliance on estimated projections and a narrow industry focus. Future research should broaden the sample and explore the lifecycle costs of IIoT.utf-8
Nickel-based alloys has important application value in modern industrial field, but there are a lot of problems that are difficult to solve in traditional processing, and it is a typical difficult-to-process material. In order to improve the machinability of nickel-based alloys, scholars try to use a variety of non-traditional processing methods to explore and study the processing of nickel-based alloys. In these studies, ultrasonic vibration assisted processing technology and minimum quantity lubrication (MQL) processing technology can achieve remarkable results. The intermittent separation cutting characteristics of ultrasonic vibration assisted processing technology can improve the processing quality by changing the tool path, while minimum quantity lubrication processing technology can improve the lubrication effect of cutting, combining ultrasonic vibration assisted MQL processing leverages the benefits of both methods, resulting in improved machinability and expanded application of nickel-based alloys. Summarize the current research status on the machining mechanism of nickel-based alloys assisted by ultrasonic vibration and micro lubrication, and anticipate its developmental trends. This provides a reference for future research on the efficient machining mechanisms and practical applications of nickel-based alloys.utf-8
Despite that ocean current energy is one of the promising sources of electricity produced in the ocean, the development of ocean current energy is far behind compared to other ocean energy due to the low efficiency and high cost of installation and maintenance. Among many converting devices, the Savonius turbine has been proven to be effective and competitive in harnessing ocean current energy. The primary purpose of the present study is to search for the optimum shape of a Savonius rotor based on CFD simulation (Star-CCM+). A Savonius turbine composed of two rotating cup-shaped rotors is selected as a numerical model. We focus on the effect of two geometry parameters such as the overlap and gap ratio on the power coefficient. Throughout the parametric study, the shape of a Savonius rotor affects the power performance, and two geometry parameters with an overlap ratio of 0.15 and a gap ratio of −0.03 are found to be the optimum design. It demonstrates stable performance within the wide TSR (Tip Speed Ratio) range of 0.6 to 1.6, with the maximum power coefficient Cp of 0.34 achieved at a TSR of 0.8. According to the numerical results based on the new CFD model, the presence of a bottom wall does not significantly affect the performance of a Savonius turbine. It means that the present unbounded CFD model can be acceptable in the initial design stage for the determination of the geometry parameters of a Savonius turbine.utf-8
With the development of the manufacturing industry, there is an increasing demand for high-efficiency processing, high-precision processing, and high-temperature processing. The characteristics of ceramic tools, such as high hardness and wear resistance, make them suitable for high-precision processing. Additionally, their excellent high temperature resistance perfectly meets the requirements of high temperature processing. However, ceramic tools have a relatively low strength and are prone to breakage, which limits their application in some high-strength machining fields. Their low toughness and brittleness also lead to easy cracking and reduced tool life, resulting in frequent tool changes that further limit processing efficiency. Therefore, improving the service life of ceramic tool materials is crucial to enhance processing efficiency and achieve significant economic benefits. With the development of material science, solid additives with toughening and strengthening properties have greatly improved the performance of ceramic tool materials and given ceramic tools new life-enhancing properties, such as lubrication and repair. By utilizing the combined action of one or more solid additives and employing surface coating technology, the service life of ceramic cutting tools is significantly extended. This makes the application of ceramic tools in industrial cutting more and more widely, and the demand is also growing rapidly. However, the mechanism and methods of various solid additives to increase the life of ceramic tool materials have not been systematically reviewed. The analysis of the composition and functional properties of ceramic tool materials was used as a basis to summarize the mechanism by which various solid additives improve the service life of ceramic tool materials, and to provide points for attention in their use. The aim is to assist researchers in designing and preparing new ceramic tool materials that can meet processing requirements. Finally, the research status, challenges, and prospects of enhancing the service life of ceramic cutting tools with solid additives are summarized, providing a foundation for further research.utf-8
This manuscript describes the research path when extending a maturity model. The initial model—ManuMaturity—was for manufacturing companies aiming beyond Industry 4.0. The extended OSME model covers data sharing within a supply chain, an open innovation ecosystem and sustainable manufacturing. The OSME maturity model has five maturity levels: traditional factory, modern factory, agile factory, agile cognitive factory and agile cognitive industry and seven dimensions (such as infrastructure, data, customer, business model, employee, sustainability and processes). The tool was experimented with in manufacturing companies on two occasions: with a set of manufacturing companies and a group of companies. In both cases, feedback was gathered from the respondents. The article follows the maturity assessment development phases such as scope, design, populate, test, deploy and maintain, and reports the software implementation of the maturity tool. With the help of the developed maturity model and the tool, it was possible to make assessments in case companies, where the tool and its results were commented mostly positively. The tool can be applied in various ways. For example, a group of people can jointly submit their common understanding and have a thorough discussion or a group of company representatives submit their responses and the variation is discussed afterwards.utf-8