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Rechargeable battery production should yield highly diversified batteries, overcoming performance degradation caused by the complexity of production processes, dynamic disturbances, and uncertainties. Resilience must be achieved to overcome these limitations while satisfying the core technical requirements. This study developed an architectural framework for a cyber-physical production system (CPPS) using a digital twin (DT) to achieve resilience. Activities for resilience, operational characteristics, and CPPS were analysed to determine the core requirements. This analysis presents a novel model of activities for resilience. Moreover, the DT-based CPPS architecture, service composition procedures, and the asset description for providing inputs to the elements in the CPPS were designed according to these requirements. The proposed architectural framework applies the asset administration shell principles for efficient interoperability. The service composition procedures are classified into the type and instance phases to ensure static and dynamic technical functionalities. Moreover, the asset description is suitable to indicate the required information elements of rechargeable battery production. The DT-based CPPS was applied in a rechargeable battery production for an industrial case study to verify and validate the proposed method. The average accuracy of the DT application was 95.24%, indicating that it can provide technical functions with high accuracy. As a result, these technical functions can be executed within a sufficient action time, and the high simulation accuracy prevents performance degradation during production. Additionally, the DT is suitable for event diagnosis and provides a dynamic response. Furthermore, the proposed method can eliminate the data, analysis, and decision latencies.

Self-configuration is the preparation required to facilitate smart-manufacturing (SM) with the inputs derived without user intervention for engineering applications. Thus, it is vital for achieving the highest maturity level of SM technologies. In context, digital twin (DT) is an advanced virtual factory with simulation as its core technical functionality. However, the requirement of several inputs limits the implementation of DT on a physical asset without user intervention. Moreover, surpassing this limitation requires extraction methods for deriving the necessary inputs for DT application. Therefore, this study proposes information fusion and systematic logic library (SLL)-generation methods to facilitate the self-configuration of an autonomous DT. The information fusion aggregates and extracts the information elements required for DT application from heterogeneous information sources. In addition, the SLL generation method created the SLL required for reflecting the functional units of agents within the physical asset. Both methods were proposed from available SM standards such as ISA-95, automation markup language, and OPC unified architecture. Furthermore, an autonomous DT-supporting framework was designed by analyzing the relationship between asset description and SM standards, which facilitated the artificial intelligence-based extraction of the asset description object and SLL. Additionally, the core functional engines within this framework were designed using machine learning and process-mining techniques. Consequently, the proposed methods reduced the input pre-processing time required for constructing and synchronizing an autonomous DT to aid the application of autonomous DT on the physical asset without user intervention.

At automotive manufacturing sites, meeting the delivery schedule is difficult owing to the occurrence of unpredictable abnormal scenarios such as product defects and equipment failures. To overcome this, manufacturing technologies developed as part of the Fourth Industrial Revolution are employed to meet the delivery schedule set by the customer. We propose a digital twin (DT)–based cyber-physical system (CPS) that can predict whether a product can be manufactured as per the schedule requested by a customer at an automotive body production line where abnormal scenarios occur. We designed a product, process, plan, plant, and resource information model for automotive body production lines; the proposed DT employs this model. Unlike in previous research on DTs focusing on independent engineering application development, we designed and implemented a CPS combined with a DT and other components for a Web-based integrated manufacturing platform. To the best of our knowledge, this is the first time a DT-based CPS is implemented for abnormal scenarios involving automotive body production lines; the capability of the proposed system was verified via experiments. The experimental results indicate that the proposed system achieved an average prediction performance of 96.83% for the actual production plan. We confirmed that the DT-based CPS can be applied to automotive body production lines, and it provides an advanced solution to predict whether production is possible according to the production plan.

In a re-entrant job shop (RJS), an entity can visit the same resource type multiple times; this is called re-entrancy, which occurs frequently in actual industries. Re-entrancy causes an NP-hard pr...

The asset administration shell (AAS) has a virtual representation as an asset description and technical functionality as a smart manufacturing service. A digital twin (DT) is an advanced virtual factory technology that has simulation as its core technical functionality, which it performs in the type and instance stages of the physical asset. For providing an efficient information object to the DT application, this paper proposes Virtual REpresentation for a DIgital twin application (VREDI): an asset description for the operation procedures of a work-center-level DT application. For the successful application of DT as a smart factory technology, VREDI is designed to meet four core technical requirements—DT definition, AAS property inheritance, improving the existing asset description, and supporting DT-based technical functionalities. Based on the analysis of the technical requirements, the elements of VREDI are derived and the reference relationships between them are designed. It is then possible to provide the required technical functionality using the VREDI header, and a detailed P4R structure and elements of the body are defined. VREDI is applied to the concept to support the main properties of the DT. It is designed to inherit the AAS properties for efficient information management and interoperability. The application of advanced concepts such as “type and instance” and supporting vertical integration and horizontal coordination overcomes the limitations of the existing asset descriptions. Additionally, VREDI designates elements for supporting six DT-based technical functionalities in the type and instance stages of the physical work center.

A process and systematic efficiency enhancement in sustainable manufacturing can enhance energy and production operations as well as the energy-related indicators. Simulations are frequently used to increase this type of efficiency through diagnosis and evaluation of a physical asset. In particular, digital twin (DT) is currently attracting considerable attention as it provides technical functionality at the type and instance stages of a work center. In addition, DT can support efficient control and decision making with less gap in the site through vertical integration and horizontal coordination. Moreover, DT can contribute to prevent energy-related inefficiency by providing the functionalities required for the service composition of the technical functionalities that are defined for the enhancement of process and systematic efficiency. However, in terms of the provision of service-composition-based technical functionality of DT, no research has defined each step of the operation procedures of work-center-level DT application at a detailed level. This study proposes detailed operation procedures to create, synchronize, and utilize a work-center-level DT to provide appropriate service-composition-based technical functionality. To this end, the technical requirements were derived from the analysis of the service-composition-based technical functionality. This study systematically defined the various service-composition-based technical functionalities through a combination of various types of operation procedures. Each type is defined for three steps, namely creation, synchronization, and utilization. In addition, a case study was conducted to clarify DT and provide a suitable definition for the requirements.

Personalized production is a manufacturing concept relevant to the fourth industrial revolution, which can satisfy various customer needs inexpensively. There are three main hurdles to the efficient implementation of this concept: access, cost, and performance. This paper proposes a digital twin-based cyber physical production system (CPPS) architectural framework that overcomes the performance hurdle. The proposed architectural framework comprises five services that are solutions to the performance hurdle of personalized production, and it operates on information based on the proposed product, process, plan, plant, and resource (P4R) information model. This information model is manufacturing abstraction for personalized production and is presented on a detailed level with object-orientation and the “type and instance” concept. Whereas previous studies on the digital twin concept considered one or several facilities and focused on the development of independent applications, this study focuses on the digital twin as a core technological element of the entire system and analyzes CPPS design and its operation from the system-of-systems perspective. The application of the digital twin-based CPPS to a micro smart factory (MSF) provides an advanced solution for the personalized production of various products. An average makespan improvement of ~ 26.87% was achieved using the implemented CPPS services in the MSF.

Recently, manufacturing companies have been making efforts to increase resource utilization while ensuring the flexibility of production lines to respond to rapidly changing market environments and customer demand. In the high-tech manufacturing industry, which requires expensive manufacturing facilities and is capital-intensive, re-entrant production lines are used for efficient production with limited resources. In such a production system, a part visits a specific station repeatedly during the production period. However, a re-entrant production line requires an appropriate scheduling system because other parts with different processing requirements are processed at the same station. In this study, a re-entrant production line was modeled as a manufacturing environment via simulation, and an adaptive scheduling system was developed to improve its operational performance by applying deep reinforcement learning (DRL). To achieve this, a software architecture for integrating DRL with the simulation was developed and the states, actions, and rewards of the reinforcement learning (RL) agent were defined. Moreover, a discrete-event simulation control module was designed to collect data from the simulation model and evaluate the policy network trained via DRL. Finally, the applicability and effectiveness of the developed scheduling system were verified by conducting experiments on a hypothetical re-entrant production line.

Hepatica is a small genus of Ranunculaceae with medicinal and horticultural value. We characterized nine complete chloroplast (cp) genomes of Hepatica, which ranged from 159,549 to 161,081 bp in length and had a typical quadripartite structure with a large single-copy region (LSC; 80,270–81,249 bp), a small single-copy region (SSC; 17,029–17,838 bp), and two copies of inverted repeat (IR; 31,008–31,100 bp). The cp genomes of Hepatica possess 76 protein-coding genes (PCGs), 29 tRNAs, and four rRNA genes. Comparative analyses revealed a conserved ca. 5-kb IR expansion in Hepatica and other Anemoneae; moreover, multiple inversion events occurred in Hepatica and its relatives. Analyses of selection pressure (dN/dS) showed that most of the PCGs are highly conserved except for rpl20 and rpl22 in Hepatica falconeri, Hepatica americana, and Hepatica acutiloba. Two genes (rps16 and infA) were identified as pseudogenes in Hepatica. In contrast, rpl32 gene was completely lost. The phylogenetic analyses based on 76 PCGs resolved the phylogeny of Hepatica and its related genera. Non-monophyly of Anemone s.l. indicates that Hepatica should be reclassified as an independent genus. In addition, Hepatica nobilis var. japonica is not closely related to H. nobilis.

The vasculature is an essential component of the circulatory system that plays a vital role in the development, homeostasis, and disease of various organs in the human body. The ability to emulate the architecture and transport function of blood vessels in the integrated context of their associated organs represents an important requirement for studying a wide range of physiological processes. Traditional in vitro models of the vasculature, however, largely fail to offer such capabilities. Here we combine microfluidic three-dimensional (3D) cell culture with the principle of vasculogenic self-assembly to engineer perfusable 3D microvascular beds in vitro. Our system is created in a micropatterned hydrogel construct housed in an elastomeric microdevice that enables coculture of primary human vascular endothelial cells and fibroblasts to achieve de novo formation, anastomosis, and controlled perfusion of 3D vascular networks. An open-top chamber design adopted in this hybrid platform also makes it possible to integrate the microengineered 3D vasculature with other cell types to recapitulate organ-specific cellular heterogeneity and structural organization of vascularized human tissues. Using these capabilities, we developed stem cell-derived microphysiological models of vascularized human adipose tissue and the blood-retinal barrier. Our approach was also leveraged to construct a 3D organotypic model of vascularized human lung adenocarcinoma as a high-content drug screening platform to simulate intravascular delivery, tumor-killing effects, and vascular toxicity of a clinical chemotherapeutic agent. Furthermore, we demonstrated the potential of our platform for applications in nanomedicine by creating microengineered models of vascular inflammation to evaluate a nanoengineered drug delivery system based on active targeting liposomal nanocarriers. These results represent a significant improvement in our ability to model the complexity of native human tissues and may provide a basis for developing predictive preclinical models for biopharmaceutical applications.

Recently, manufacturing concepts, such as personalized production and distributed manufacturing, have attracted attention owing to the ongoing revolution in industrial technology. Connected micro s...

The manufacturing industry has recently been focusing on improving energy efficiency to reduce greenhouse gas emissions and achieve sustainable growth. The focus is on combining existing energy technologies with new information and communication technologies as the Fourth Industrial Revolution approaches. Dyeing and finishing shops use the most energy in the textile industry and have below-average energy efficiency because of low technology and facility investment. Research into increasing the energy efficiency of dyeing and finishing shops has concentrated on developing equipment; however, it is difficult for small- and medium-sized factories to benefit from these advances. Thus, research into means of improving energy efficiency by improving the process and system efficiency of dyeing and finishing companies, who have difficulties with facility investment and operation, is necessary. In this study, a cyber physical energy system that improves the energy efficiency of the dyeing process by collecting and analyzing manufacturing big data was developed. Further, the implemented system was applied to actual dyeing and finishing shops, and its effects were verified. This research contributes to improving the situation of the dyeing process using machine learning techniques and manufacturing big data by adjusting cyber physical energy systems without utilizing expensive equipment. Inaccurate process instruction from the laboratory are also replaced by the cyber physical energy system, and the invalid and inefficient steps in the traditional process scenario derived from operator’s experience are replaced with more valid and usable actions.

Ensuring sustainability is a primary concern of the manufacturing industry. Not only does the enhancement of process and systematic efficiency secure sustainability through increased energy efficiency but it also improves the efficiency in terms of overall productivity. Dyeing and finishing industries consume massive amounts of energy and have large energy-related expenditures. The industry comprises small- and medium-sized enterprises, which have insufficient capital to pay for the energy-efficient equipment. This study proposes a service-oriented platform that can achieve process and systematic efficiency enhancement based on the industrial Internet of Things (IIoT). The platform reflects the requirements of dyeing and finishing shops in the industry and secures effective interoperability and services using a service-oriented architectural design. A smart operation enabled by the service-oriented platform to improve the efficiency of traditional processes is developed. The system architecture, P...

Background There are no data on comparison between clopidogrel monotherapy and prolonged dual antiplatelet therapy (DAPT) in patients at high-risk undergoing percutaneous coronary intervention (PCI). Methods Of 2,082 consecutive patients undergoing PCI using second-generation drug-eluting stent (DES), we studied 637 patients at high-risk either angiographically or clinically who received clopidogrel longer than 24 months and were event-free at 12 months after index PCI. Patients were divided into 2 groups: the clopidogrel monotherapy group and the prolonged DAPT group. The primary outcome was a composite of all-cause death, non-fatal myocardial infarction (MI), definite or probable stent thrombosis, or stroke between 12 months and 36 months after the index PCI. Results In propensity score-matched population (246 pairs), the cumulative rate of primary outcome was 4.5% in the clopidogrel monotherapy group and 4.9% in the prolonged DAPT group (hazard ratio, 1.21; 95% confidence interval, 0.54–2.75; P = 0.643). There was no significant difference in all-cause death, MI, stent thrombosis, stroke between the clopidogrel monotherapy group and the prolonged DAPT group. Conclusion Compared with prolonged DAPT, clopidogrel monotherapy showed similar long-term outcomes in patients at high-risk after second-generation DES implantation., Graphical Abstract

To achieve efficient personalized production at an affordable cost, a modular manufacturing system (MMS) can be utilized. MMS enables restructuring of its configuration to accommodate product changes and is thus an efficient solution to reduce the costs involved in personalized production. A micro smart factory (MSF) is an MMS with heterogeneous production processes to enable personalized production. Similar to MMS, MSF also enables the restructuring of production configuration, additionally, it comprises cyber-physical production systems (CPPSs) that help achieve resilience. However, MSFs need to overcome performance hurdles with respect to production control. Therefore, this paper proposes a digital twin (DT) and reinforcement learning (RL)-based production control method. This method replaces the existing dispatching rule in the type and instance phases of the MSF. In this method, the RL policy network is learned and evaluated by coordination between DT and RL. The DT provides virtual event logs that include states, actions, and rewards to support learning. These virtual event logs are returned based on vertical integration with the MSF. As a result, the proposed method provides a resilient solution to the CPPS architectural framework and achieves appropriate actions to the dynamic situation of MSF. Additionally, applying DT with RL helps decide what-next/where-next in the production cycle. Moreover, the proposed concept can be extended to various manufacturing domains because the priority rule concept is frequently applied.

Mass vaccination with the Pfizer-BioNTech coronavirus disease 2019 (COVID-19) vaccine (BNT162b2) in Korea has resulted in many reported adverse effects. These side effects are the object of much scrutiny in the medical community. We report the case of a 29-year-old male who was diagnosed with myopericarditis after his second dose of Pfizer-BioNTech COVID-19 vaccine. This patient is the second recognized case of Pfizer-BioNTech COVID-19 vaccine induced myopericarditis in Korea and the first to have recovered from it. He originally presented with chest discomfort and exertional chest pain. Lab tests revealed elevated cardiac marker levels and echocardiographic findings displayed minimal pericardial effusion, prompting diagnosis as myopericarditis. We decided on two weeks of outpatient treatment with non-steroidal anti-inflammatory drugs (NSAIDs) due to the patient's mild symptoms and his occupation in the military. When this proved insufficient, we shifted to combination therapy with low dose corticosteroids and NSAIDs. After two weeks of treatment, the patient's symptoms and pericardial effusion had improved, and he was recovered completely 37 days after the onset., Graphical Abstract

This study investigated a two-step thermochemical treatment process consisting of carbonization and halogenation for the removal of radionuclides from spent cation-exchange resin (CER). Based on a thermal analysis of cation-exchange resins, we propose a two-step thermochemical treatment process involving the conversion of spent CER into pyrocarbon and then the removal of radioactive elements from the carbonized CER by converting them volatile halides at very high temperatures. The proposed process mainly consists of a carbonization and halogenation reactor, a UHC (unburned hydrocarbon) combustor, and wet scrubber. A step-by-step experimental and numerical optimization study was conducted with the carbonization and halogenation reactor and the UHC combustor. The optimum operating conditions could be established based on the results of a thermal analysis of the CER, a nonisothermal kinetic analysis, a numerical modeling study of a plug flow reactor (PFR)-type combustor, and a thermodynamic equilibrium analysis of a system consisting of a mix of carbonized CER and halogenation gas. The results of this study present detailed design of a novel multifunctional reactor and operating conditions of a bench-scale carbonization and halogenation process. Basic performance tests using CER doped with nonradioactive Co and Cs, indicated as Cs-137/134 and Co-60/58, were conducted under the optimized conditions. The results of these tests showed that the novel thermochemical process proposed in this study is a viable process that effectively removes radioactive elements from spent CER.

The complete chloroplast genome of Centaurea maculosa (Asteraceae) was presented in this article. The genome size is 152,518 bp in length, with 43.1% of GC content. It consists of a large single-copy (LSC) region (83,959 bp) and a small single-copy region (SSC) (18,487 bp) which were separated by two inverted repeat (IRs) regions (25,218 bp). The complete chloroplast genome contains 111 unique genes, including 80 coding genes, 4 rRNA genes, and 27 tRNA genes.

Hepatica is a small genus of Ranunculaceae with medicinal and horticultural value. We characterized nine complete chloroplast (cp) genomes of Hepatica, which ranged from 159,549 to 161,081 bp in length and had a typical quadripartite structure with a large single-copy region (LSC; 80,270–81,249 bp), a small single-copy region (SSC; 17,029–17,838 bp), and two copies of inverted repeat (IR; 31,008–31,100 bp). The cp genomes of Hepatica possess 76 protein-coding genes (PCGs), 29 tRNAs, and four rRNA genes. Comparative analyses revealed a conserved ca. 5-kb IR expansion in Hepatica and other Anemoneae; moreover, multiple inversion events occurred in Hepatica and its relatives. Analyses of selection pressure (dN/dS) showed that most of the PCGs are highly conserved except for rpl20 and rpl22 in Hepatica falconeri, Hepatica americana, and Hepatica acutiloba. Two genes (rps16 and infA) were identified as pseudogenes in Hepatica. In contrast, rpl32 gene was completely lost. The phylogenetic analyses based on 76 PCGs resolved the phylogeny of Hepatica and its related genera. Non-monophyly of Anemone s.l. indicates that Hepatica should be reclassified as an independent genus. In addition, Hepatica nobilis var. japonica is not closely related to H. nobilis.

Background The invasive species Xanthium spinosum has been used as a traditional Chinese medicine for many years. Unfortunately, no extensive molecular studies of this plant have been conducted. Results Here, the complete chloroplast (cp) genome sequence of X. spinosum was assembled and analyzed. The cp genome of X. spinosum was 152,422 base pairs (bp) in length, with a quadripartite circular structure. The cp genome contained 115 unique genes, including 80 PCGs, 31 tRNA genes, and 4 rRNA genes. Comparative analyses revealed that X. spinosum contains a large number of repeats (999 repeats) and 701 SSRs in its cp genome. Fourteen divergences (Π > 0.03) were found in the intergenic spacer regions. Phylogenetic analyses revealed that Parthenium is a sister clade to both Xanthium and Ambrosia and an early-diverging lineage of subtribe Ambrosiinae, although this finding was supported with a very weak bootstrap value. Conclusion The identified hotspot regions could be used as molecular markers for resolving phylogenetic relationships and species identification in the genus Xanthium.

Ultra-thin two-dimensional semiconducting crystals in their monolayer and few-layer forms show promising aspects in nanoelectronic applications. However, the ultra-thin nature of two-dimensional crystals inevitably results in high contact resistance from limited channel/contact volume as well as device-to-device variability, which seriously limit reliable applications using two-dimensional semiconductors. Here, we incorporate rather thick two-dimensional layered semiconducting crystals for reliable vertical diodes showing excellent Ohmic and Schottky contacts. Using the vertical transport of WSe2, we demonstrate devices which are functional at various frequency ranges from megahertz AM demodulation of audio signals, to gigahertz rectification for fifth-generation wireless electronics, to ultraviolet–visible photodetection. The WSe2 exhibits an excellent Ohmic contact to bottom platinum electrode with record-low contact resistance (~50 Ω) and an exemplary Schottky junction to top transparent conducting oxide electrode. Our semitransparent vertical WSe2 Schottky diodes could be a key component of future high frequency electronics in the era of fifth-generation wireless communication., Two-dimensional materials show promise for 5G wireless communication applications. Here, the authors report vertical Schottky diodes based on thick mechanically exfoliated WSe2 flakes having low ohmic contact resistance of 50 Ω and ultrafast cutoff frequency of 27 GHz.

During the thin strip coiling process, it is necessary to use a sleeve with a mandrel to prevent excessive deformation of the strip. Stress distribution in the sleeve and in the strip is an important factor that determines the quality of the coil. However, owing to the accumulation of high pressure, it is difficult to determine the stress distribution through experimentation. Thus, stress analysis of the strip coiling process was conducted. Finite element analysis was used to investigate the effects of the weight of the strip and the mandrel on the stress distribution and stress concentration near the starting point of the coil. The radial stress was predicted for a coil with a stacked thickness of 384 mm, which corresponds to a strip length of 1486 m, using the stress analysis model developed in a preceding research. A method was presented to reduce the weight and radial stress of a strip coil. It was found that the deformation of the sleeve can be reduced by decreasing the gap between the mandrel segments. The thickness of the sleeve can be reduced from 120 to 106 mm using the stress analysis results. Furthermore, coiling tension can be reduced by 44% compared to the existing value considering the interlayer slip of the strip coil.