Operation Capability Research Articles

Research on Partner Selection in Enterprise Innovation Ecosystem

In the face of fierce market competition, enterprises must ensure the competitiveness of their products or services through technological innovation. However, the complexity of technology often surpasses the capabilities of individual enterprises, leading them to deepen cooperation with other organizations. The entities within the enterprise innovation ecosystem depend on each other, collaborate closely, and rely on core enterprises to integrate resources, thereby creating system value and enhancing competitiveness. The purpose of this paper is to explore the process of selecting appropriate ecosystem partners. It begins by providing an overview of relevant concepts, characteristics, selection factors, and methods. Subsequently, it analyzes the roles, resources, and synergy evolution of the entities within the ecosystem. An evaluation system encompassing operation, core, synergy, and development capability is then established. This system comprises 16 indicators, including organization scale and reputation, and is accompanied by a hierarchical evaluation model. Finally, the validity of the evaluation system is confirmed through empirical analysis, utilizing the Analytic Hierarchy Process (AHP) and the fuzzy comprehensive evaluation method.

Crafting Near‐Infrared Photonics via the Programmable Assembly of Organic Heterostructures at Multiscale Level

AbstractOrganic single crystals with near‐infrared (NIR) emission demonstrate their excellent optical communications from well photonic confinement and low optical waveguide loss, which are considered as competitive candidates toward advanced optoelectronics. However, the increasingly diverse and sophisticated application demands result in the complicated design of NIR devices, which is hardly realized solely by the intrinsic properties of individual crystals. Herein, a programmable assembly strategy is presented to fabricate organic heterostructures. Triphenylene (TP), pyrene (Py) and 7,7,8,8‐tetracyanoquinodimethane (TCNQ) are primary selected to prepared organic cocrystals with narrow band gap and near‐infrared emission. Importantly, the charge‐transfer alloy with tunable emission from 700 nm to 850 nm and branched heterostructures with multichannel characteristics are prepared from these organic cocrystals by following the growth kinetics process at molecular level and lattice matching principle at structural level, respectively. Theses prepared heterostructures exhibit optical logic operation capabilities, which can serve as optical modulators. This work provides new insights into the manufacturing of organic NIR heterostructures applied in advanced optoelectronics.

The Effects of Business Digitalization and Knowledge Management Practices on Business Performance

The relentless advance of digitalization has transformed the business landscape, offering new opportunities and challenges for enterprises across industries. This study explores the intricate interplay between business digitalization, knowledge management practices, and business performance, with a specific focus on Micro, Small, and Medium Enterprises (MSMEs). By analyzing data from a diverse group of entrepreneurs and organizations, this research sheds light on the critical factors driving success in the digital age. The study's findings reveal that digitalization is not merely a buzzword but a tangible force shaping the destiny of businesses. It highlights the positive and significant impact of digitalization on knowledge management practices within MSMEs. Moreover, it underscores the mediating role of knowledge management in the relationship between digitalization and business performance, emphasizing the importance of holistic approaches to these domains. Key dimensions of digital capability, including basic digital capabilities, digital operation capabilities, and digital integration capabilities, are identified as significant drivers of business performance. Additionally, business model innovation emerges as a potent catalyst, propelled by digital capabilities, for enhancing organizational outcomes. The study underscores the importance of business leaders adopting digital strategies, fostering a culture of continuous learning, and leveraging social media platforms for market engagement. Furthermore, the study provides a nuanced understanding of the demographic and organizational profiles of MSMEs, shedding light on factors such as gender diversity, educational backgrounds, firm size, and age. These factors are shown to influence the adoption and impact of digitalization and knowledge management practices. In conclusion, this research underscores the transformative power of digitalization and knowledge management in shaping the performance of MSMEs. It offers actionable insights for business leaders, policymakers, and researchers, emphasizing the need for proactive engagement with digital technologies and the cultivation of knowledge-centric organizational cultures. As the digital landscape continues to evolve, this study contributes valuable perspectives to navigate the complexities of the digital age.

Efficient Methods to Reduce Arc Effects in Circuit Breakers

Abstract: This paper investigates the opening and non-opening processes of low voltage circuit breakers, the arc effects during short-circuit currents, and seeks to identify practical solutions to minimize potential damage. The reliable operation and protective capabilities of circuit breakers are crucial in power systems, especially during adverse conditions. Arc currents are a significant component of short-circuit scenarios in power systems. Additionally, arc currents typically occur between contacts during the opening of circuit breakers under normal conditions. Therefore, the components of circuit breakers play a vital role in mitigating the current flowing through the system. To diminish the destructive effects of electric arcs on circuit breaker parts, maintaining constant current values in the system is necessary, alongside conducting requisite tests and data collection. Understanding the properties and impacts of the components within the circuit breaker is also beneficial.

A flexible energy management for distributed energy supplied smart home in microgrid connection with grid‐connection/islanding mode functionality

AbstractIn this study, a flexible control approach is presented for smart home with DES system in microgrid connection. The smart home with DES has operation capability under GC‐Mode and I‐Mode functions with the proposed control algorithm. The control algorithm is also developed in terms of international standards IEEE 929 and IEC 61727 for grid connection requirements. Additionally, a PLL‐less control algorithm is embedded in the proposed control algorithm for the active/reactive power management and the grid synchronization. Thus, slow dynamic response and calculation burden issues in controller is avoided and the power flow capability of the grid‐connected DES in smart home is enhanced. Furthermore, the coordinate transformation is fulfilled for the power flow control in the control loop via the generation of cosine and sinus functions. Besides, the mathematical formulations of the proposed control algorithm are presented in detail. To show the effectiveness of the proposed control algorithm, a smart home with a photovoltaic DES model is designed and constructed in a simulation environment. The proposed control method is tested under various operation cases such as dynamic environmental conditions, GC‐Mode/I‐Mode, reactive power support and voltage variations. The proposed method shows efficient performance under applications of the different operation situations. Moreover, the international requirements are satisfied for GC‐Mode and I‐Mode transitions.

A Study of an Agricultural Indoor Robot for Harvesting Edible Bird Nests in Vietnam

This study demonstrates robot technology for harvesting edible bird’s nests within swiftlet houses. A comprehensive manipulator’s movement analysis of harvesting operation with a separating tool is provided for precisely collecting swiftlet nests. A robotic manipulator mounted on a mobile platform with a vision system is also analyzed and evaluated in this study. The actual harvesting or separating the swiftlet nests is performed with visual servo feedback. The manipulator performs the gross motions of separating tools and removing the nests under computer control with velocity and position feedback. The separating principle between the objective nest and wooden frame has been applied to a demonstration removal of nests using a four-degrees-of-freedom manipulator to perform the gross movements of tool. The actual separations using this system are accomplished as fast as the manipulator can be controlled to perform the necessary deceleration and topping at the end of separating. This is typically 2.0 s. This efficiency underscores the system’s capability for swift and precise operation in harvesting an edible bird nest task.

Object Detection Algorithm of Transmission Lines Based on Improved YOLOv5 Framework

Foreign objects easily attach to the transmission lines because of the various laying methods and the complex, changing environment. They have a significant impact on the safe operation capability of transmission lines if these foreign objects are not detected and removed in time. An improved YOLOv5 technique is provided to detect foreign objects in transmission lines due to the low-foreign object recognition accuracy image detection. The method first reduces the computation and memory consumption by introducing the RepConv structure, further improves the detection accuracy and speed of the model by embedding the C2F structure. This method finally is further optimized neural network by the Meta-ACON activation function. The results indicate that the average detection accuracy of the improved YOLOv5 network can reach 96.9%, which is 2.2% higher than before. Additionally, corresponding detection speed can reach 258.36 frames/second, which surpasses existing mainstream target detection models, performing better in terms of the balance of inference speed and detection accuracy. Consequently, the effectiveness and superiority of the algorithm have been proved.

Statistical process control and PDCA for quality improvement in the mexican automotive industry

Despite the advancements witnessed in the realm of quality improvement, Statistical Process Control (SPC) perseveres as a universally embraced and extensively employed tool within manufacturing companies across the globe. This enduring popularity can be attributed to its adherence to the time-tested principles established by Shewhart, which have withstood the test of time since their inception in 1924. Over the years, SPC has consistently proven its efficacy in optimizing manufacturing processes, enhancing product quality, and fostering continuous improvement initiatives. Quality is an utmost necessity in the automotive industry, which ranks as the 3rd most significant industry in Mexico and the 5th globally in terms of volume and transactional activity. This research focuses on a successful real case study that demonstrates the enhancement of capability in a critical machining operation within an automotive plant located in Mexico, specifically dedicated to truck engine remanufacturing. This improvement was achieved through the analysis of x̅ and R control charts, followed by the implementation of the Plan-Do-Check-Act (PDCA) cycle. The results obtained were derived from a comparative analysis of data from two distinct time periods in the machining process of bushing diameters. This analysis revealed a significant increase in process capacity, with a 13.08% improvement in the Process Capability Index (Cpk) and a 17.2% enhancement in the Process Performance Index (Ppk). The decrease in expected out-of-specification parts showed a remarkable improvement of 72.7%. Additionally, there was an enhancement in process variability, with a notable 8.33% reduction in the mean range. The significance of this research lies in its empirical identification of gaps and opportunities within the realms of quality assurance and quality control, utilizing methodologies for quality improvement. By uncovering these gaps and opportunities, this study provides valuable insights that can guide future efforts to enhance quality practices and drive continuous improvement in the field.

Unmanned Surface Vehicle for Automatic Water Quality Monitoring

This paper presents an affordable, yet efficient approach to Unmanned Surface Vehicle (USV) design for automated water quality monitoring. Mechanically, the USV employs a catamaran design with robust hardware components, including aluminium structural frames, PVC inflatable tubes, and waterproof enclosures for housing electronics and batteries. The water quality monitoring function is achieved through a multi-parameter sonde controlled by an onboard processing unit, enabling fully automated environmental data collection. With the capability of both GPS-guided and telemetry operation, the USV is suitable to perform various missions/tasks of vast environmental surveillance application on both static water and river setting while maintaining communication with ground control station and server via wireless RF/4G/LTE/GPRS/Wi-Fi networks.

First operation of an ACHINOS-equipped spherical proportional counter with individual anode read-out

The multi-anode sensor ACHINOS revolutionised the capabilities of the spherical proportional counter by enabling large-size, high-pressure, operation and TPC-like reconstruction capabilities through individual anode read-out. First measurements with an individually read out ACHINOS are performed, which enables improved calibration and response homogenisation. Experimental results demonstrating the improvement in energy resolution brought by the individual anode calibration are presented. These are complemented by detailed simulation studies on the effect of sensor design and manufacturing imperfections, and how they may be corrected both in hardware and analysis.

Demonstration of a novel majority logic in a memristive crossbar array for in-memory parallel computing.

A memristive crossbar array can execute Boolean logic operations directly within the memory, which is highly noteworthy as it addresses the data bottleneck issue in traditional von Neumann computing. Although its potential has been widely demonstrated, achieving practical levels of operational reliability and computational efficiency remains a challenge. Here, we introduce a three-input majority logic gate supported by near-memory operations, serving as a universal gate and achieving both robust reliability and high efficiency in versatile logic operations. We fabricated a highly reliable HfOx-based memristive array, incorporating a series resistor to increase the reset voltage of the memristor, thereby increasing the operational voltage margin of the gate operation. This ensured reliable operation of the majority gate, resulting in successful experimental proof of combined 1-bit full adder and subtractor operations performed in 5 steps using 7 cells. Additionally, we propose that an N-bit parallel prefix adder (PPA) operation is possible in O(log2 N) steps, by taking advantage of the parallel operation capability of the majority gate. This achieves 8.5× higher spatiotemporal efficiency than the previously reported NOR-based logic system in 64-bit adder operation. Moreover, as N increases, the spatiotemporal efficiency further improves, which significantly enhances the applicability of memristive logic-in-memory.

Ultraviolet-sensitive and power-efficient oxide phototransistor enabled by nanometer-scale thickness engineering of InZnO semiconductor and gate bias modulation

Amorphous oxide semiconductor photodetectors (PDs) are promising ultrasensitive and power-efficient ultraviolet (UV) PDs because they generate low dark current in the dark and exhibit high photoresponse under UV irradiation owing to their superior UV absorption and photocarrier transport characteristics. Herein, we demonstrate UV-sensitive and power-efficient oxide phototransistors through the nanometer-scale engineering of oxide semiconductors and appropriate modulation of gate bias conditions. The dark current and photocurrent of an oxide phototransistor exhibit a trade-off relationship in terms of the thickness of the oxide semiconductor film. Ultrathin InZnO is disadvantageous for fabricating UV-sensitive PDs because of its low photoresponse. In contrast, excessively thick InZnO is disadvantageous for fabricating power-efficient UV PDs owing to its high dark current. However, the InZnO film with an optimal film thickness of 8 nm can simultaneously provide the advantages of both ultrathin and excessively thick cases owing to its low intrinsic carrier concentration and sufficient UV absorption depth. Consequently, an InZnO phototransistor with high UV-sensing performance (Smax = 1.25 × 106), low-power operation capability (Idark = ∼10−13A), and excellent repeatability is realized by using an 8-nm-thick InZnO semiconductor and applying appropriate gate bias modulation (constant gate bias for maximized photosensitivity and temporal positive bias pulse for persistence photocurrent elimination).

Gadolinia Doped Ceria with Engineered Grain Boundaries as Potential Electrolyte Material for Thin-Film Solid Oxide Fuel Cells

Thin-film solid oxide fuel cells are receiving increasing attention within the scientific community thanks to their high energy density and high efficiency in different temperature ranges. To be utilized as power supply systems for portable electronic devices, thin-film solid oxide fuel cells must demonstrate high power supply and low-temperature operation capabilities. Both capabilities are highly dependent on the function of the electrolyte layer, commonly comprised of ceramic mixed-ionic-electronic conductors [1]. The state-of-the-art thin-film solid oxide fuel cells utilize yttrium stabilized zirconia as an electrolyte material, despite its relatively low ionic conductivity within the typical working-temperature range of solid oxide fuel cells (up to 1000 °C). Moreover, the ionic conductivity of yttrium stabilized zirconia dramatically reduces with decreased temperature, limiting its performance as an electrolyte material for low-temperature (below 600 °C) solid oxide fuel cells [2].Gadolinia doped ceria is an alternative promising electrolyte material for low temperature solid oxide fuel cells. Its relatively high ionic conductivity below 600 °C makes it attractive as an electrolyte material although its partial electronic conductivity is a significant drawback [3]. This drawback is more pronounced in ultra-thin layers (sub-micron scale) solid oxide fuel cells devices. As a result, gadolinia doped ceria have been utilized only to a limited extent for thin-film solid oxide fuel cells.The issue of partial electronic conductivity might be resolved thanks to a non-conventional deposition technique of polycrystalline gadolinia doped ceria thin films. The proposed sputtering technique includes metallic alloy target and results in a granular morphology, as opposed to the columnar morphology obtained using the conventional sputtering method. As electrical conductivity of polycrystalline thin films is higher along the grain boundaries [4], gadolinia doped ceria layers with random crystallographic orientation are expected to be less electronically conductive. Here, we investigated the integration and the performance of granular gadolinia doped ceria as an electrolyte material for thin-film solid oxide fuel cells. The electronic-conduction properties along the grain boundaries of gadolinia doped ceria were studied, and a thin-film solid oxide fuel cell prototype was fabricated. Such devices with engineered grain boundaries hold the potential for low-temperature operation, high power output, and silicone-compatibility for novel integration opportunities and bulk-fabrication.

Hot Tool Welding of Pipelines from Polyethylene for Gas Supply with a Diameter of 90-315 mm

Purpose of research. GOST P 55276-2012 applied in the Russian Federation does not regulate concrete data on the choice of this or that procedure under various conditions of welding and standard sizes of the applied pipes, leaving it to the discretion of the consumer. Unlike the procedure of the welding with only low pressure which is well fulfilled and widely applied in domestic practice, the welding according to the procedure with the only high pressure allowing to reduce three times time of a welding cycle is practically not used and specially intended welding machines in Russia are not issued. In this regard this work is devoted to development of the modes of hot tool welding of abutting connections of pipes from polyethylene with a diameter from 90 to 315 mm for SDR 13.6 - SDR 9.0 with the only high pressure, to the choice of possible domestic welding equipment and experimental check of the developed modes.Methods. In this article for butt welding by the heated tool of pipes from polyethylene with a diameter from 90 to 315 mm, using a design technique, main parameters of welding procedure are determined with the only high pressure. When choosing the welding machine necessary for tube welding of the considered range on welding procedure with the only high pressure, by results of the carried-out analysis of technical datas of domestic welding machines and features of their operation capabilities it is preferred as the welding machine with the hydraulic drive "Native of the Volga Region of SSPT-315". For experimental check of the executed payment of parameters of the procedure of welding under the cyclogram with the only high pressure four joints of pipes with a diameter of 110 mm with thickness of a wall of 10 mm from PE-100 (SDR 11.0) have been welded and visual and measuring quality control of the executed connections and short-term tests of technological samples on axial stretching by the R-50 machine is made.Results. Mechanical tests of technological samples of all joints of the pipes from PE-100 with a diameter of 110 mm (SDR 11.0) executed on the SSPT-315 welding machine on welding procedure with the only high pressure have shown 100% - ny result of plastic nature of destruction at the size of lengthening from 500 to 600%.Conclusion. The high quality of experimental joints of pipes from PE-100 assumes a possibility of use of the SSPT- 315 machine for hot tool welding of pipes from polyethylene of everything of the range regulated by technical datas on welding procedure with the only high pressure.

Research on the Transformation of Traditional Retail Industry in the Context of Digital Economy -Taking Douyin as an Example

During the COVID-19 pandemic, the government has introduced various measures to restrict people's travel in order to curb the spread of the virus. These bans make it difficult for the traditional retail industry to survive. However, the development of the digital economy has brought new opportunities to the traditional retail industry. As one of the media of the digital economy, Douyin can effectively help traditional enterprises out of difficulties. However, at present, for most traditional retailers, there are many difficult problems in the process of integrating and using new media. Therefore, this paper mainly summarizes the necessity of the transformation of the traditional retail industry from the perspective of the traditional retail industry, taking Douyin as an example, and analyzes the problems existing in the traditional retail industry in the initial stage of Douyin, such as insufficient content operation capability, difficulty in product selection, and scene setting. Finally, this paper analyzes how to solve the above challenges from the three dimensions of controlling "people," "goods," and "field". Finally, it puts forward countermeasures and suggestions for the transformation of merchants.

A hierarchical reinforcement learning GPC for flexible operation of ultra-supercritical unit considering economy

With the growing proportion of renewable energy sources in power grid, the demands for deep peak shaving and rapid load regulation of ultra-supercritical (USC) unit to provide more flexible and stable power services is further enhanced. Simultaneously, the load tracking speed is no longer the only significant task in the flexible operation of USC unit, the operational economy is more and more important. To this end, a hierarchical reinforcement learning GPC control scheme with a better economy is proposed and apply to USC unit. Firstly, the model mismatch problem in control process is taken into account, and an integral mode is added into the GPC to eliminate the steady state error during the load regulation. Secondly, the hierarchical reinforcement learning GPC scheme integrated the GPC and twin delayed deep deterministic policy gradient algorithms is presented. The complex flexibility demand problem is decomposed into rapid load regulation and economic operation and then respectively solved in the GPC-based upper layer and reinforcement learning agent-based lower layer. Thirdly, under the flexibility demand, a multi-criteria optimization function including the load tracking cost, main steam throttling loss and coal consumption rate of unit is constructed. Then, via the accurate trajectory tracking by GPC and on-line control sequence optimization by reinforcement learning agent, the operational flexibility and economy of USC unit are simultaneously improved within safe boundaries. Finally, to verify the availability of the proposed hierarchical reinforcement learning GPC strategy, large-scale load variations and disturbance rejection ability tests cover the 30%–100 % rated load of a 1000 MW USC unit are carried out, and the load regulation performance is compared to other strategies. Results confirm that the designed hierarchical reinforcement learning GPC control scheme is profit for the flexible and economic operation capability promotion of USC unit.

Enhanced four-port dual-active-bridge converter employing power decoupling capability for DC microgrid islanding mode operation

Enhanced four-port dual-active-bridge converter employing power decoupling capability for DC microgrid islanding mode operation

An Improved DC Power Electronic Transformer Based on Voltage Balancing Converter for Bipolar Distribution System

This paper proposes a bipolar dc power electronic transformer (DCPET) with monopole fault operation capability for medium voltage / low voltage DC (MV / LVDC) distributions. Compared with the conventional bipolar LVDC topology, the proposed DCPET considers the reduced number of switching devices and the normal operation under monopole faults, which improves power supply reliability. The dc fault ride-through (FRT) strategy is further proposed in this paper to increase the power supply reliability under LVDC short-circuit faults. To reduce the short-circuit current and maintain the LVDC voltage, the switching device reversely series with the capacitor is blocked after the fault. Thus, the fault current is restricted, and power supply recovery time after fault clearance is reduced. Moreover, the LLC resonant converter adopting phase shift control outputs stable fault criterion current to assist the fault location and removal for the protection system. Finally, a downscaled prototype is built to verify the proposed topology and FRT strategy by experiments.

Adjustable Robust Optimization for Water Distribution System Operation Under Uncertainty

AbstractThe optimal operation of water distribution systems (WDS) is a paramount objective for water utilities due to the substantial energy consumption associated with pumping. A major challenge in optimizing WDS operation is addressing uncertainties such as those related to consumer demands. Real‐time operation under uncertainty necessitates a dynamic approach that can utilize the newly observed information and adjust the operational policy accordingly. This study presents an adjustable robust optimization (ARO) approach to tackle this challenge. Unlike static optimization methods, ARO generates a decision rule policy that is dynamically adjusted as new data becomes available and the operational horizon evolves, thereby ensuring adaptability to changing conditions. Furthermore, the study includes a quantitative analysis of typical demand uncertainty that supports the formulation of the ARO model. The proposed method is evaluated through two case studies and compared with traditional folding horizon approaches. The results indicate that the ARO method is competitive with traditional methods in terms of objective value and surpasses them in terms of robustness. An additional advantage of the method is its offline operation capability which enables it to produce decision rules independent of real‐time programs. This feature facilitates various practical applications such as what‐if analyses, maintenance work planning, and preparation for other special events.

Optimal dispatch approach for rural multi-energy supply systems considering virtual energy storage

In response to the underutilization of energy and insufficient flexible operation capability of rural energy supply systems in China, this study proposes an optimal dispatch approach for a rural multi-energy supply system (RMESS) considering virtual energy storage (VES). First, to enable the flexible utilization of rural biomass resources and the thermal inertia of residential building envelopes, this study constructed VES-I and VES-II models that describe electrical-thermal and electrical-gas coupling from an electrical viewpoint. Subsequently, an RMESS model encompassing these two types of VES was formulated. This model delineates the intricate interplay of multi-energy components within the RMESS framework and facilitates the precise assessment of the adjustable potential for optimizing RMESS operations. Based on the above models, a day-ahead optimal dispatch model for an RMESS considering a VES is proposed to achieve optimal economic performance while ensuring efficient energy allocation. Comparative simulations validated the effectiveness of the VES modeling and the day-ahead optimal dispatch approach for the RMESS.