Reliability Requirements Research Articles

Analisa Faktor-Faktor Yang Mempengaruhi Pendapatan Pedagang Ritel Dikabupaten Karanganyar

This research aims to analyze the factors that influence the income of retail traders in Karanganyar Regency, namely analysis of business capital, marketing strategies, and entrepreneurial characteristics on the income of retail traders in Karanganyar Regency.. This research uses a quantitative approach with primary data collected through questionnaires. The research sample was selected using a purposive sampling technique, which includes various types of retail businesses in Karanganyar Regency. The data analysis methods used include instrument testing, classical assumption testing, and hypothesis testing using SPSS for Windows. The research results show that business capital, marketing strategies, and entrepreneurial characteristics have a significant positive effect on retail traders' income. The Adjusted R² value of 0.872 shows that the three independent variables are able to explain 87.2% of the variation in retail traders' income, while 12.8% is explained by other factors. Validity and reliability tests show that the instruments used meet the validity and reliability requirements. The classical assumption test also shows that the data used meets the assumptions of normality, there is no multicollinearity, heteroscedasticity and autocorrelation. Based on the results of the analysis, it is recommended that retail traders increase creativity and innovation in entrepreneurial characteristics, as well as optimize business capital and marketing strategies, especially in the use of technology digital. Future research is recommended to take a larger sample and add other independent variables that might influence retail traders' income to obtain more comprehensive results. Keywords: Business Capital, Marketing Strategy, Entrepreneurial Characteristics, Retailer Income

COMPARATIVE ANALYSIS OF WIRED AND WIRELESS SENSORS IN STRUCTURAL HEALTH MONITORING

Structural Health Monitoring (SHM) systems play a critical role in ensuring the safety and longevity of civil engineering infrastructure. This paper presents a comparative analysis of wired and wireless sensor technologies within SHM applications, drawing insights from scholarly literature, expert interviews, and case studies. The significance of SHM in safeguarding infrastructure durability is emphasised, considering the substantial investment and long service lifespans associated with civil engineering structures. Thematic analysis was utilized and revealed key performance criteria such as reliability, flexibility, environmental adaptability, cost-effectiveness, and maintenance requirements. Wired sensors are lauded for their reliability and accuracy, particularly in critical infrastructure projects, while wireless sensors offer greater flexibility and ease of deployment, especially in remote monitoring scenarios. Environmental adaptability remains crucial for both sensor types, with fiber optic sensors demonstrating effectiveness in harsh conditions. Expert interviews further enrich the understanding of sensor performance, highlighting opportunities for advancements in wireless sensor technology and data analytics. The paper concludes with recommendations for future research and development efforts to address existing constraints and meet the evolving needs of SHM in civil infrastructure monitoring. Overall, this comparative analysis provides valuable insights for guiding advancements in sensor technology and SHM procedures to ensure the continued safety and integrity of essential infrastructure.

Обробка даних на основі швидкого перетворення Фур’є в кореляційному течешукачі

Fast Fourier transform (FFT) algorithms are widely used in correlation leak detectors (CD) in the implementation of digital data processing. The combination of the computa-tional efficiency of FFT with modern high-performance mobile computing means pro-vides acceptable data processing time during leak detection. Due to the increase in the general wear and tear of pipeline networks in many countries, the requirements for reliabil-ity and efficiency in detecting and repairing damage are increasing. Meeting these re-quirements means complicating data processing algorithms to more fully take into ac-count the diversity of the acoustic environment. This is the reason for the special interest in FFT as a basic, universal algorithm, on the basis of which it is promising to further develop data processing in CD. The article describes the experience of the authors in the application of FFT in parametric CD, in particular, the use of FFT in spectral evaluation and digital filtering of signals, calculations of digital filters, calculation and further pro-cessing of correlation functions is considered.

Effects of gravity and anisotropy on the convective instability in a nanofluid porous medium

Controlling thermal loads in heat transfer systems that produce high heat flux is a real mechanical challenge. Various cooling/heating techniques are available to achieve the reliability requirements of electronic devices. Among them, the use of nanofluids is one of the important techniques that provide long term stability, higher cooling rates, decreased pumping power needs, and cost-effectiveness. Instability in fluids typically occurs when a disturbance affects the equilibrium of forces of external, inertial, or viscous origin acting on a system. The disturbances may arise from the surroundings due to small changes in the boundary conditions, surface roughness, free stream turbulence, noise, etc. In several circumstances, these disturbances are very small and hence cannot be measured with the available instruments but can be observed after the instability sets in. In this study, we focus on examining the effect of time-periodic vertical gravity modulation on the initiation of natural convection in a porous medium saturated with a nanofluid. The porous medium is characterized by being heated at the bottom and possessing anisotropic properties in terms of permeability and thermal diffusivity. Specifically, we investigate the onset of convection in water-based nanofluids that contain metallic (Cu) and metal oxide ( A l 2 O 3 ) particles. The Khanafer-Vafai-Lightstone (KVL) nanofluid model is employed to describe the behavior of the nanofluids, and the thresholds for convective instability are determined using the Mathieu functions. In addition, we study the instabilities of synchronous and subharmonic modes and explore their transitions along with practical applications.

Lifetime Prediction of Permanent Magnet Synchronous Motor in Selective Compliance Assembly Robot Arm Considering Insulation Thermal Aging.

The direct-drive selective compliance assembly robot arm (SCARA) is widely used in high-end manufacturing fields, as it omits the mechanical transmission structures and has the advantages of high positioning accuracy and fast movement speed. However, due to the intensifying dynamic coupling problem of structures in the direct-drive SCARA, the permanent magnet synchronous motors (PMSMs) located at the joints will take on nonstationary loads, which causes excessive internal temperature and reduces the lifetime of PMSMs. To address these issues, the lifetime prediction of PMSMs is studied. The kinematic and dynamic models of the SCARA are established to calculate the torque curve required by the PMSM in specific typical motion tasks. Additionally, considering thermal stress as the main factor affecting lifetime, accelerated degradation tests are conducted on insulation material. Then, the reliability function of the PMSM is formulated based on the accelerated degradation model. Based on the parameters and working conditions of the PMSM, the temperature field distribution is obtained through simulation. The maximum temperature is used as the reference temperature to conduct reliability evaluation and lifetime prediction of the PMSM. The research results show that for a typical point-to-point task, the PMSM can run for 102,623 h while achieving the reliability requirement of 0.99.

Research on vibration test method of electric actuator

Abstract The stable, safe, and reliable operation of electric actuator valve systems is of great significance in industrial production. This paper proposes a vibration test method for electric actuators, employing the test to meet the test severity level as the first priority, with random frequency vibration within 10 Hz to 1000 Hz. The vibration acceleration is loaded with a Gaussian distribution, which can be used to simulate the irregular vibration of electric actuators in the actual working conditions of the working environment. The test is divided into up and down vibration (z-axis), left and right vibration (x-axis), and front and rear vibration (y-axis) in three directions independently to verify the electric actuator from the mechanical structure and the circuit structure in order to meet the reliability requirements of the actual production.

P‐82: Analysis and Validation of TFT‐LCD Data Open Mechanism

In this paper we reported a novel technology to improve Data Open. The relationship between process material and data open was analyzed between many materials. After a lot of experimental verification and analysis of the mechanism. A method to assess Data Open risk is developed with corresponding Cu acid standards process change to ensure product reliability requirements are met.

Investigation on memory package crack and prevention under temperature cycling test

Memory package with multiple die stacking in one package faced package crack issue during package level temperature cycling test (TCT) and the failure cycle cannot meet reliability requirement. Failure analysis showed epoxy molding compound (EMC) cracking located at the center area of package surface. Finite element modeling and simulation was conducted to study package stress and failure mechanism under cyclic temperature loading condition. Simulation results showed that the center of package surface is subjected to higher stress and stress variation during stringent TCT test due to high and tight die stacking structure. Several parametric studies were conducted to further understand failure mechanism and provide solution for crack prevention. Design guideline was proposed to eliminate or reduce package crack risk for multi-chip package (MCP) in memory chip package.

Pengaruh Media Sosial Dalam Meningkatkan Niat Beli Karang Hias (Coral) Pada PT. Dirga Mega Cipta Bekasi, Jawa Barat

This study aims to determine which of Facebook and Instagram has the most dominant effect on increasing the purchase intention of Ornamental Coral at PT Dirga Mega Cipta Bekasi. The type of research used in this research is quantitative research. The population in this study were all Facebook and Instagram social media followers on the @coral education and @coral_educational accounts. The sample in this study amounted to 39 people using random sampling analysis techniques, The data collection technique used a questionnaire with a Likert scale, each of which had been tested and had met the validity and reliability requirements. The data processing technique used SPSS version 22. The data analysis technique used in this study is multiple linear regression. The results of this study can show that Facebook and Instagram social media have the most dominant influence in increasing purchase intention on Ornamental Corals is Facebook Social Media.

Study of Fixed Point Message Scheduling Algorithm for In-Vehicle Ethernet

With the rapid development of advanced driver assistance systems (ADASs) and autonomous driving technology, in-vehicle networks are facing huge challenges in real-time operation and data loss. Traditional vehicle bus network systems such as LIN, CAN, and FlexRay are insufficient to meet the real-time requirements of intelligent connected vehicles. In-vehicle Ethernet meets the requirements of high reliability, low electromagnetic radiation, low power consumption, bandwidth allocation, low latency, and real-time synchronization of intelligent connected vehicles. In-vehicle Ethernet has become one of the trends in the next generation of in-vehicle network architecture. This research focuses on the delay problem existing in the real-time data transmission process of in-vehicle Ethernet, and innovatively proposes a fixed point message scheduling algorithm (FPMS) based on time-sensitive network (TSN) technology. By building an experimental platform based on the CANoe simulation tool, the high-efficiency message transmission performance of the fixed point message scheduling algorithm was verified. Experimental results show that the fixed point message scheduling algorithm proposed in this study improves message transmission efficiency by 66%, laying a solid foundation for improving the real-time and reliability performance of in-vehicle Ethernet.

Key Issues on Integrating 5G into Industrial Systems

Under the auspice of further developing 5G mobile communication technology and integrating it with the latest advancements in the field of Industrial Internet-of-Things, this study conducts in-depth research and detailed analysis on the combination of 5G with industrial systems based on composite structures, communication network architectures, wireless application scenarios, and communication protocols. The status quo, development trend, and necessity of 5G mobile communication technology are explored and its potential in industrial applications is analyzed. Based on the current practical development level of 5G technology, by considering different requirements for bandwidth, real-time performance, and reliability in communication networks of industrial systems, this study proposes three feasible paths for the integration between 5G and industrial systems, including the method to use 5G in place of field buses. Finally, by introducing real-world cases, this study has successfully demonstrated the integration of 5G and industrial systems by extending 5G terminals as field bus gateways. This study provides valuable references for research and practice in related fields.

A simplified reliability-based design method for multiple design variables considering different limit states

A generalized reliability model comprising the objective, constraint, and judgment functions is established for the reliability index approach (RIA), taking parameters’ properties of engineering practice and negative reliability index into consideration. Based on this, the reliability-based design (RBD) problem with multiple design variables is translated into the solution to the nonlinear equations, and a simplified method consisting of a simple variant of the Newton iteration method and the finite difference method (FDM) is proposed. Numerical examples are presented to verify the efficiency of the proposed reliability approach and to determine the incremental step size for FDM. RBD of a simply supported beam is illustrated and the variabilities of design variables are investigated considering the uncertainties in the manufacturing process and practical operations. Results reveal that the variations of the design variables should not be ignored. Moreover, analysis results show that the design value might not intuitively increase with the increase of its coefficient of variation (CoV), and it might not increase with the increasing reliability requirement for problems involving multiple variables. The reasons for this phenomenon are very complicated, and it is a systematic problem. One should be aware of this phenomenon, and specific analysis is required for specific problems.

Replica fault-tolerant scheduling with time guarantee under energy constraint in fog computing

Fog computing offers stronger local computing power and reduces data transmission load, making it an ideal solution to meet the energy-saving and efficient requirements of intelligent connected vehicle applications. As intelligent networked vehicles and vehicle–road collaboration technologies advance rapidly, optimizing scheduling under fog computing architecture has become a prominent research area. However, existing studies primarily concentrate on parallel task scheduling with low energy consumption or high real-time performance, failing to address the requirement for high reliability in intelligent networked vehicle scenarios. To achieve time and reliability optimization for vehicular applications in fog computing architecture, this paper proposes a fog computing task scheduling algorithm and explores its extension using replication techniques. Subsequently, the algorithm underwent evaluation utilizing randomly generated directed acyclic graph models as well as real-life automotive application instances. The experimental findings indicate that in comparison to existing methods, the proposed algorithm exhibits a notable improvement in reliability while ensuring time optimization, thereby demonstrating a distinct level of advancement and practicality.

A Remaining Useful Life Prediction Method of Mechanical Equipment Based on Particle Swarm Optimization-Convolutional Neural Network-Bidirectional Long Short-Term Memory

In industry, forecast prediction and health management (PHM) is used to improve system reliability and efficiency. In PHM, remaining useful life (RUL) prediction plays a key role in preventing machine failures and reducing operating costs, especially for reliability requirements such as critical components in aviation as well as for costly equipment. With the development of deep learning techniques, many RUL prediction methods employ convolutional neural network (CNN) and long short-term memory (LSTM) networks and demonstrate superior performance. In this paper, a novel two-stream network based on a bidirectional long short-term memory neural network (BiLSTM) is proposed to establish a two-stage residual life prediction model for mechanical devices using CNN as the feature extractor and BiLSTM as the timing processor, and finally, a particle swarm optimization (PSO) algorithm is used to adjust and optimize the network structural parameters for the initial data. Under the condition of lack of professional knowledge, the adaptive extraction of the features of the data accumulated by the enterprise and the effective processing of a large amount of timing data are achieved. Comparing the prediction results with other models through examples, it shows that the model established in this paper significantly improves the accuracy and efficiency of equipment remaining life prediction.

Energy-efficient triple modular redundancy scheduling on heterogeneous multi-core real-time systems

Triple modular redundancy (TMR) fault tolerance mechanism can provide almost perfect fault-masking, which has the great potential to enhance the reliability of real-time systems. However, multiple copies of a task are executed concurrently, which will lead to a sharp increase in system energy consumption. In this work, the problem of parallel applications using TMR on heterogeneous multi-core platforms to minimize energy consumption is studied. First, the heterogeneous earliest finish time algorithm is improved, and then according to the given application's deadline constraints and reliability requirements, an algorithm to extend the execution time of the copies is designed. Secondly, based on the properties of TMR, an algorithm for minimizing the execution overhead of the third copy (MEOTC) is designed. Finally, considering the actual situation of task execution, an online energy management (OEM) method is proposed. The proposed algorithms were compared with the state-of-the-art AFTSA algorithm, and the results show significant differences in energy consumption. Specifically, for light fault detection, the energy consumption of the MEOTC and OEM algorithms was found to be 80% and 72% respectively, compared with AFTSA. For heavy fault detection, the energy consumption of MEOTC and OEM was measured at 61% and 55% respectively, compared with AFTSA.

A multifaceted suite of metrics for comparative myoelectric prosthesis controller research.

Upper limb robotic (myoelectric) prostheses are technologically advanced, but challenging to use. In response, substantial research is being done to develop person-specific prosthesis controllers that can predict a user's intended movements. Most studies that test and compare new controllers rely on simple assessment measures such as task scores (e.g., number of objects moved across a barrier) or duration-based measures (e.g., overall task completion time). These assessment measures, however, fail to capture valuable details about: the quality of device arm movements; whether these movements match users' intentions; the timing of specific wrist and hand control functions; and users' opinions regarding overall device reliability and controller training requirements. In this work, we present a comprehensive and novel suite of myoelectric prosthesis control evaluation metrics that better facilitates analysis of device movement details-spanning measures of task performance, control characteristics, and user experience. As a case example of their use and research viability, we applied these metrics in real-time control experimentation. Here, eight participants without upper limb impairment compared device control offered by a deep learning-based controller (recurrent convolutional neural network-based classification with transfer learning, or RCNN-TL) to that of a commonly used controller (linear discriminant analysis, or LDA). The participants wore a simulated prosthesis and performed complex functional tasks across multiple limb positions. Analysis resulting from our suite of metrics identified 16 instances of a user-facing problem known as the "limb position effect". We determined that RCNN-TL performed the same as or significantly better than LDA in four such problem instances. We also confirmed that transfer learning can minimize user training burden. Overall, this study contributes a multifaceted new suite of control evaluation metrics, along with a guide to their application, for use in research and testing of myoelectric controllers today, and potentially for use in broader rehabilitation technologies of the future.

Legal basis of defense standardization of the European Union

Legal basis of defense standardization of the European Union

Dynamic human error risk assessment of group decision-making in extreme cooperative scenario

For groups in extreme environments, their reliability requirements in complex operational systems are high due to isolation from society, physical constraints for extended periods of time, and exposure to significant hazards. This study attempts to solve the problem of dynamic quantitative risk analysis of decision-making process for extreme group during complex cooperative scenarios. Based on an extended IDA team cognitive model, typical failure modes and performance quantification mechanisms of team communication were analyzed. The performance curve was utilized to distinctively model the cognitive behaviors of operators within the team, driving the cognitive transmission paths of group decision-making in a hybrid event tree. Error calibration of human error due to time uncertainty was conducted. The steps and techniques for dynamic risk analysis of decision-making of extreme groups under complex, dynamic, and ambiguous scenarios were summarized. The proposed method was validated through simulation in a typical powered diving task of manned submarine.

Sustainable astronomy: A comparative life cycle assessment of off-grid hybrid energy systems to supply large telescopes

PurposeSupplying off-grid facilities such as astronomical observatories with renewable energy–based systems (RES) instead of diesel generators can considerably reduce their environmental impact. However, RES require oversized capacities to counter intermittency and comply with reliability requirements, hence shifting the environmental impact from operation to construction phase. We assess whether 100% RES scenarios are favorable from an environmental point of view and discuss the trade-offs in systems with backup fossil generators versus 100% renewable ones.MethodsIn this comparative life cycle assessment (LCA), we study various RES supply systems to power a new telescope in the Atacama Desert, Chile. We compare six setups, including 100% RES scenarios, namely, photovoltaics (PV) with batteries and hydrogen energy storage; high-renewable scenarios, with fossil fuel power generation next to RES and storage; and a system combining PV with diesel generation. We base system sizing on a techno-economical optimization for the start of operation in 2030. Foreground data stem from life cycle inventories of RES components since 2015 and 2030 electricity mix assumptions of production countries. We assess environmental impact in the categories climate change, mineral resource depletion, and water use.Results and discussionWe find that 100% RES and high-renewable scenarios result in emissions of 0.077–0.115 kg CO2e/kWh supplied, compared to 0.917 kg CO2e/kWh in the reference case with solely diesel generation. One hundred percent RES scenarios have a lower CO2e impact than high-renewable scenarios. However, the latter lower the mineral resource depletion and water use by about 27% compared to 100% RES scenarios. Applying hybrid energy storage systems increases the water use impact while reducing the mineral resource depletion.ConclusionsNone of the six energy systems we compared was clearly the best in all environmental impacts considered. Trade-offs must be taken when choosing an energy system to supply the prospective off-grid telescope in Chile. We find high-renewable systems with some fossil generation as the better option regarding power reliability, mineral resource depletion, and water use, while inducing slightly higher greenhouse gas emissions than the 100% RES scenarios. As remote research facilities and off-grid settlements today are mainly supplied by fossil fuels, we expect to motivate more multifaceted decisions for implementing larger shares of RES for these areas. To advance the LCA community in the field of energy systems, we should strive to incorporate temporal and regional realities into our life cycle inventories. To ease the path for upcoming studies, we publish this work’s inventories as detailed activity level datasets.

Thermal-magnetic coupling inhomogeneous temperature field analysis of cylindrical eddy current brakes

With the increasing requirements for safety and reliability, it is now necessary to analyze the thermal characteristics to the same extent as the electromagnetic design for eddy current brakes(ECB), because the working characteristic will be greatly influenced by temperature. In this paper, the transient thermal-magnetic coupling analysis of permanent magnet cylindrical eddy current brake, which is used as the recoil mechanism in artillery, is presented. First, the structure and working principle of this ECB are described in detail. Second, the analytical electromagnetic model is established by multilayer theory to derive the heat source of this ECB. Thirdly, the thermal-magnetic coupling model is established to calculate the dynamic inhomogeneous temperature field of the ECB. The heat conduction equation is solved in different regions with inhomogeneous internal heat source by Finite Difference method(FDM) in two-dimensional cylindrical coordinate. Finally, the validity of the proposed model is verified by commercial Finite Element software. The thermal characteristic and its effects on braking force is analyzed during working. The maximum value of temperature approximately rises by 16℃ in each firing. The braking force will decline by 8% considering temperature.