Reliability Of Components Research Articles

Epoxy-Printed Circuit Board Interfacial Fracture Reliability Under Three-Point and Four-Point Bend Loading After Sustained Elevated Temperature Exposure

Abstract The survivability and reliability of commercial electronic components under very high thermo-mechanical loads are improved using underfilling and potting methods. Potting protects from operating conditions such as moisture, water, or corrosive agents. Furthermore, potting offers damping against shock and vibrations, heat dissipation, and structural support. Being one of the most cost-efficient methods, potting greatly increases reliability and therefore reduces costs for replacements and repairs. It also addresses trapped hot air issues better than other restraint technologies. In potted electronic assemblies, interfacial delamination at the epoxy and printed circuit board (PCB) interface has been one of the major failure modes. Interfacial delamination happens at the epoxy/PCB interface under dynamic shock loads, which leads to failures at the solder interconnects of the electronic components. Sustained operation and storage at elevated temperatures change the interfacial characteristics at the epoxy/PCB interface. This research is focused on interfacial failure mechanics at epoxy/PCB interfaces with high-temperature isothermal aging. In the selection of the epoxy potting material and the reliability assessments of the supplemental restraint systems, fracture parameters such as steady-state strain energy release rate stress and fracture toughness are critical. Rectangular beam specimens of the epoxy/PCB interface are fabricated for different potting compounds, and the fracture behavior is studied under quasi-static monotonic three-point and four-point bend loads. One of the main differences between three-point and four-point bend loading is that the maximum bending stress occurs at the midpoint under the point of loading of the specimen in three-point bending, whereas the peak stress is distributed over the section of the specimen between the loading points in four-point bending. Four different potting compounds with diverse properties have been studied. The recommended curing schedule from the manufacturer has been chosen and followed for all the potting compounds. The epoxy/PCB interfacial samples are aged at a high temperature of 100 °C for 30–180 days. Damage has been assumed to happen at the epoxy/PCB interface under dynamic loads. The critical load of crack initiation for the epoxy/PCB interface has been determined from the experimental findings, and it is used in the computation of fracture toughness values. The fracture toughness values are compared for the various epoxy/PCB systems based on the number of days of thermal aging and the method of flexure testing. A cohesive zone model has been constructed for predominantly mode-I delamination with four-point bend stress to predict the interfacial delamination behavior at the epoxy/PCB interfaces. It has been assumed that the bulk material is linear elastic during the bending load. The cohesive zone has been modeled at the interface, where the interfacial fracture has been assumed to occur. The fracture behavior in the simulation is predicted based on the fracture parameters determined through the experiment. The computed cohesive zone parameters are unique to the interfaces, and they can be used across various applications with the same epoxy/PCB interface to predict interfacial delamination and to select a more suitable potting material.

Which Global Moment Tensor Catalog Provides the Most Precise Non-Double-Couple Components?

Abstract The availability of digital seismic waveform data enabled compilation of seismic moment tensor catalogs that provide information about earthquake source processes beyond what could be derived from earlier methods that assume double-couple sources representing slip on planar faults. This additional versatility involves additional complexity. Moment tensors are determined by inversions minimizing the misfit between observed and synthetic waveforms, and depend on the specifics of the data inverted, the inversion algorithm, and the Earth structure assumed. Hence, substantial uncertainties arise in moment tensors and quantities derived from them, which can be assessed by comparing moment tensors from multiple global and regional catalogs using different data and inversion procedures. While the double-couple (DC) components of moment tensors are generally determined with greater certainty, non-double-couple (NDC) components for the same earthquake sometimes differ significantly between catalogs. This observation raises questions about the reliability of their determination and hence their geological significance. Using the correlation between NDC components in different catalogs, we quantify the reliability of NDC components in moment tensor catalogs through the determination of the effects of unmodeled and inaccurately modeled effects contained in them. We determine that the NDC components in the Global Centroid Moment Tensor catalog are, on average, more precise than in other catalogs, and thus studies on NDC components should be based on this catalog. Furthermore, their uncertainties are largely unrelated to uncertainties in the DC components. Therefore, the reliability of fault angles derived from a moment tensor is largely independent from the reliability of its NDC components.

Experimental characterisation of a launcher’s fairing separation shock and its influence on RF antennas’ supporting structures

Fairing separation is a critical event during a rocket’s launch as it generates mechanical shocks that can cause partial or total onboard equipment failure. This study details the experimental results of the fairing separation shock of the launcher RFA ONE and its influence on the supporting structures of RF antennas. Accelerometers were used at multiple points of neighbouring structures to characterise the separation devices’ shock during fairing separation tests. Moreover, the shock propagation on different material structures, such as aluminium, carbon fibre, and Viton® elastomer sealant, was investigated. The results showed that the presence of Viton® sealant increased shock transmissibility. Further investigation was conducted to study the influence of applied torque on the separation locks on the shock levels. The study revealed that higher torques lead to increased magnitudes of shock acceleration. Finally, the paper provides recommendations for reducing the shock levels. The experimental results and recommendations presented in this paper provide valuable insights for launcher designers and manufacturers to ensure the safety and reliability of shock-sensitive components during flight.

System risk modelling and decision-making – Reflections and common pitfalls

Since its foundation, the Joint Committee on Structural Safety (JCSS) has been engaged in the discussion of methods for determining the reliability of components, calibration of standards, as well as risk modelling of systems. In publications, it is regularly explained which methods have which advantages. In the literature, the drawbacks and pitfalls that challenge rational decisions and help to develop and find more appropriate methods for practice are often not documented.Such problems can lead to decisions, which are not rational from a decision-theoretic point of view, some of which are worse than a random decision. Especially events, with a very small probability of occurrence hardly give any feedback possibilities from reality and evidence-based analysis of decisions is not possible. Careful selection of methods and knowledge/information of the assumptions is crucial to rational decisions.This paper will discuss some of the identified pitfalls based on the discussions in the JCSS. It will span from aspects in the uncertainty quantification, uncertainty propagation, consequence assessment as well as approaches that are found and used in practice for decision-making (e.g. probability interpretations, risk aversion, risk matrices and FN diagrams). This paper can be seen as a documentation of outtakes from the discussions which led to the joint understanding and approach of the JCSS. The paper does not claim to be complete concerning all the possible pitfalls in risk assessments and system identification. But it does provide important reflections and indicates where the eyes must be kept open. Further, the paper points to a way of rational decision-making accounting for the uncertainties in information.

Reliability model for key components of urban rail transit train based on improved hunter-prey optimization

The reliability of key components of urban rail transit (URT) plays an important role in the maintenance plans of URT. It is necessary to establish the reliability model of URT trains. In the current research, the reliability model has a limited scope of application and fails to accurately depict the reliability of key components in URT trains. To solve the above problem, a multi-peak type mixture Weibull distribution model is established using several three-parameter Weibull distributions based on fault modes of components sourced from historical lifetime data. Due to the complexity of this model, parameter estimation is challenging. For this purpose, an improved hunter-prey optimization (IHPO) was proposed to improve parameter estimation accuracy. Firstly, an improved Hénon chaos map was introduced to improve the distribution of the initial population. Secondly, the Lévy flight was introduced to increase the probability of the individual spreading to the whole range at the late stage. Lastly, a nonlinear balance factor was proposed to enhance the algorithm’s global search capability. The simulation experiment was carried out with examples of the balanced pressing wheel and the wheelset. The IHPO algorithm-based parameter estimation method shows the highest R-square with values of 0.996 and 0.999, respectively, and the lowest root mean square error with values of 0.019 and 0.008, respectively. The simulation results demonstrate that the stability and optimization of the HPO are improved, and the multi-peak mixture Weibull distribution model based on the IHPO can accurately depict URT trains’ reliability.

Reliability Prediction of Radiation Induced Failures in Semiconductor Packages

The growth and usage of semiconductor components has risen greatly due to evolution of applications in industries such as aerospace, defense, and automotive, in both the commercial and government sectors. Among the different types of components that make their way into such applications, digital logic and memory-based devices are of prime importance due to the ever-demanding need to store and compute vast amounts of data. This brings to the forefront the reliability of such components, especially in demanding applications in aerospace and defense where components are exposed to extremely harsh environments where high performance is critical. This is where we find that reliability is largely dependent on the susceptibility of semiconductor components to radiation induced effects - total ionizing dose (TID) and single event effects (SEE). Optimization in design, process, and packaging could make microelectronics more reliable to the radiation effects. Packaging material and thickness affect the incident flux of radiation on microelectronics and can help mitigate both dose and SEE effects in electronics. Additionally, packaging materials should not generate a high flux of secondary particles when exposed to environmental radiation (an example is alpha emissions from impurities in package mold compound or underfill). In this paper, the behavior of semiconductors at the component level due to radiation effects is evaluated. A reduced order model approach is presented where the analysis is performed at the functional block level then aggregated into component. The behavioral model can be used to predict the behavior across different operating, design, and process conditions.

Effect of Strain Rate on Hydrogen Embrittlement of Ti6Al4V Alloy.

The phenomenon of hydrogen embrittlement (HE) in metals and alloys, which determines the performance of components in hydrogen environments, has recently been drawing considerable attention. This study explores the interplay between strain rates and solute hydrogen in inducing HE of Ti6Al4V alloy. For the hydrogen-charged sample, as the strain rate was decreased from 10-2/s to 10-5/s, the ductility decreased significantly, but the HE effect on mechanical strength was negligible. The low strain rate (LSR) conditions facilitated the development of high-angle grain boundaries, providing more pathways for hydrogen diffusion and accumulation. The presence of solute hydrogen intensified the formation of nano/micro-voids and intergranular cracking tendencies, with micro-crack occurrences observed exclusively in the LSR conditions. These factors expanded the brittle hydrogen-damaged region more deeply into the interior of the lattice. This, in turn, accelerated both crack initiation and intergranular crack propagation, finally resulting in a considerable HE effect and a reduction in ductility at the LSR. The current study underscores the influence of strain rate on HE, enhancing the predictability of longevity and improving the reliability of components operating in hydrogen-rich environments under various loading conditions.

Does user-generated content trigger university graduates’ online purchase intention? Mediating role of brand image

Academic interest in understanding the impact of user-generated content (UGC) on consumer behavior in digital marketing has grown exponentially. However, we know little about the effect of UGC on customers’ online purchase intention from developing country aspects. This underpins the current study to examine the impact of UGC on the purchase intentions of university graduates in Bangladesh. With a convenient sampling approach, a structured questionnaire was provided directly to 400 respondents; 275 usable and complete responses were extracted for data analysis. Data were empirically validated using principal component analysis, reliability test, correlation, and Hayes PROCESS macro for regression and simple mediation analysis. The findings revealed that bloggers’ recommendations, online communities, and social media content positively and significantly influence customers’ online purchase intention. Brand image also directly impacts purchase intention and mediates the relationship between bloggers’ recommendations, online community, social media content, and online purchase intention. The results of this study will facilitate policymakers and online marketers in devising UGC management policies and digital marketing strategies. The study’s results may also help online marketers, sellers, and brand representatives to understand how to enhance brand image and amplify customers’ online purchasing behavior.

A Comparative Investigation of the Reliability of Biodegradable Components Produced through Additive Manufacturing Technology.

Using the linear elastic finite element method, we investigated how defects significantly influence the integrity of 3D-printed parts made from biodegradable material by experimental techniques and numerical simulations. A defective flaw was incorporated into the tensile test dog-bone sample using Computer-Aided Design and processed by slicing software. Three distinct raster angles examine two sets of samples, one featuring intact specimens and the other with the introduced defects. An open-source 3D printer was used to fabricate both sets of samples, utilizing biodegradable PLA material. In finite element analysis, we employed a highly detailed model that precisely accounted for the geometry and dimensions of the extruded 3D-printed filament, accurately replicating the actual configuration of the 3D-printed samples to an extent. Our study involved a thorough comparative analysis between the experimental results and the FEA simulations. Our findings uncovered a consistent trend for the intact and defective samples under tensile load. Specifically, in the intact case, the samples with a zero-degree raster orientation presented the highest resistance to failure and displayed minimal elongation. Remarkably, these conclusions paralleled our observations of the defective samples as well. Finite element analysis revealed that the stresses, including Principal, Max shear, and Von Mises, were remarkably higher at the 3D-printed samples' outer surface than the inner layers, reflecting that the failure starts at the outer surface since they exceeded the theoretical values, indicating a significant discrepancy between the simulated and anticipated values.

A Computer Design Tool for Ceramic Receivers

Gen3 solar receivers and other components will experience a combination of high temperatures and high stress caused by thermal stress and internal pressure. Under these conditions metallic components, even those manufactured from nickel-based superalloys, have poor reliability. Engineering ceramics could be a solution, as these materials have excellent high temperature strength. However, accurately assessing the reliability of a ceramic component operating in these conditions requires an entirely different approach compared to metallic materials. This paper describes the implementation of statistical models for evaluating the reliability of high temperature ceramic components in srlife – an open-source software package for estimating the life of high temperature concentrating solar power equipment. This new capability allows users to make fair comparisons between competing metallic and ceramic component designs and to accurately assess the plant efficiency and economics of ceramic solar receivers and other components.

Enhancing Prescriptive Capabilities in Electrical Substations: A Systemic Impact Factor Approach for Failure Impact Analysis

This research looks into a systemic impact factor (SIF) as a complement to enhance the prescriptive capabilities of electric substations with the objective of improving the reliability and robustness of components. As electrical networks become increasingly complex, prescriptive analytical tools are needed to ensure sustained power delivery. The purpose is to develop a framework for evaluating failure effects, including both direct and indirect effects on substation performance. The study makes use of a multi-criteria method that incorporates safety, environment protection, reliability, and network robustness among other factors like SAIDI and SAIFI to determine the actual impact of failures to make better decisions. The methodology is illustrated using a criticality model, and a case study, focusing on operational contexts of the failure. The SIF proposal provides a better understanding of different aspects and their contribution, when a failure event occurs under a given operational context. This factor improves maintenance management by identifying critical equipment and projecting the effects of failure through a specific operation network. A case study in an electrical substation estimates the SIF for each element used in daily operations to improve support services and increase substation dependability. Therefore, SIF is an essential factor to consider in electrical substations for their maintainability and reliability evaluation.

A Comprehensive Performance Analysis of a 48-Watt Transformerless DC-DC Boost Converter Using a Proportional–Integral–Derivative Controller with Special Attention to Inductor Design and Components Reliability

In this research paper, a comprehensive performance analysis was carried out for a 48-watt transformerless DC-DC boost converter using a Proportional–Integral–Derivative (PID) controller through dynamic modeling. In a boost converter, the optimal design of the magnetic element plays an important role in efficient energy transfer. This research paper emphasizes the design of an inductor using the Area Product Technique (APT) to analyze factors such as area product, window area, number of turns, and wire size. Observations were made by examining its response to changes in load current, supply voltage, and load resistance at frequency levels of 100 and 500 kHz. Moreover, this paper extended its investigation by analyzing the failure rates and reliability of active and passive components in a 48-watt boost converter, providing valuable insights about failure behavior and reliability. Frequency domain analysis was conducted to assess the controller’s stability and robustness. The results conclusively underscore the benefits of incorporating the designed PID controller in terms of achieving the desired regulation and rapid response to disturbances at 100 and 500 kHz. The findings emphasize the outstanding reliability of the inductor, evident from the significantly low failure rates in comparison to other circuit components. Conversely, the research also reveals the inherent vulnerability of the switching device (MOSFET), characterized by a higher failure rate and lower reliability. The MATLAB® Simulink platform was utilized to investigate the results.

Effect of graphene nano-platelets on the low-velocity-impact and compression-after-impact strength of the glass fiber epoxy composite laminates

Detecting the low-velocity impact damage on the FRP composite structures can be challenging because the visible signs on the surface may be subtle. Mitigating the effects of BVID (Barely Visible Impact Damage) is crucial in ensuring the safety and reliability of composite components, especially in industries where these materials are commonly used, such as aerospace and automotive. This article explores the experimental investigations of the impact and post-impact damage propagation under compression in the Graphene Nano-Platelets (GNPs) infused glass fiber epoxy composite laminates. A comparative study of varying the percentage of the nano-platelets (0, 0.25, 0.5, and 0.75%) in the matrix material of the composite laminate is presented. The impact tests at low energies (15 J, 20 J, and 25 J), followed by the quasi-static compression tests, are carried out as per the procedures mentioned in the ASTM D7136/D7137. The digital image correlation technique (DIC) is used to measure strains and plot the strain field on the impacted face of the specimen under compression. Damage envelopes of the impact and compression tests are studied using X-ray CT scans. Micro-level failures are observed through Scanning Electron Microscopy (SEM) to get better insights into the failure mechanism of the composite materials under impact and compression loadings. Upon completing the study, it is found that the addition of the GNP into the matrix materials not only increased the impact performance but also increased the load-carrying capacity of the laminate under compressive loading. A decrement of 2–21% in the energy absorbed in the damage formation is seen with the incorporation of GNPs into composite materials. A maximum increment of 17% in the compressive strength is observed for the composite laminates with the 0.75% GNPs. However, for a particular percentage of the GNP, the compressive strength of the laminate is reduced with an increase in impact energy compared with its virgin counterpart. From X-ray CT scans, it is seen that the laminate under the compression tests fails due to excessive ply-splitting and the delamination at the damage site created during the impact. Fiber breakage, fiber brooming, matrix cracking, fiber-matrix debonding, etc., are some of the other failure modes observed in SEM studies.

Spatial-extent inference for testing variance components in reliability and heritability studies

Abstract Clusterwise inference is a popular approach in neuroimaging to increase sensitivity, but most existing methods are currently restricted to the General Linear Model (GLM) for testing mean parameters. Statistical methods for testing variance components, which are critical in neuroimaging studies that involve estimation of narrow-sense heritability or test-retest reliability, are underdeveloped due to methodological and computational challenges, which would potentially lead to low power. We propose a fast and powerful test for variance components called CLEAN-V (CLEAN for testing Variance components). CLEAN-V models the global spatial dependence structure of imaging data and computes a locally powerful variance component test statistic by data-adaptively pooling neighborhood information. Correction for multiple comparisons is achieved by permutations to control family-wise error rate (FWER). Through analysis of task-functional magnetic resonance imaging (fMRI) data from the Human Connectome Project across five tasks and comprehensive data-driven simulations, we show that CLEAN-V outperforms existing methods in detecting test-retest reliability and narrow-sense heritability with significantly improved power, with the detected areas aligning with activation maps. The computational efficiency of CLEAN-V also speaks of its practical utility, and it is available as an R package.

Enhancing Metal Forging Tools and Moulds: Advanced Repairs and Optimisation Using Directed Energy Deposition Hybrid Manufacturing

This article investigates the efficacy of directed energy deposition (DED) processes in repairing forging tools and moulds, comparing mechanical properties between specimens fabricated from conventional sheet metal and those manufactured by DED techniques. A comparative analysis reveals significant mechanical differences between subtractive and DED-manufactured specimens, emphasising the nuanced balance between tensile strength and ductility in DED-produced components influenced by layering. Notable insights from scatter plot analyses highlight distinct material behaviours, particularly layer-dependent tendencies in DED-manufactured specimens. Regression-based predictive models aid in understanding material behaviours, aiding in informed material selection for manufacturing processes. Additionally, this article underlines the advantages of DED-based repair processes, highlighting precision, material efficiency, reduced lead times, and cost-effectiveness. The article studies die and mould repair, tool restoration, and critical considerations like material compatibility and quality assurance. The study concludes by emphasising the role of hybrid manufacturing in extending product lifecycles, in conformity with specific mechanical requirements, and fabricating complex geometries, despite potential higher costs in materials and technologies. Overall, this research demonstrates the efficacy of DED processes in enhancing component reliability and lifespan in metalworking industries.

From athlete to entrepreneur? – Investigating the influence of sport characteristics on athlete’s entrepreneurial orientation competencies

ABSTRACT Purpose/Rationale This study aims to test to what extent athletes of different demographics, sports types, and sports skills differ in their entrepreneurial competencies. Design/Methodology/Approach We assessed athletes’ entrepreneurial competencies using a social entrepreneurship scale by Capella-Peris. We used principal component analysis and reliability testing to classify entrepreneurial competencies and One-way-ANOVA to distinguish athlete subgroups by entrepreneurial competencies (n = 189). Findings The study finds significant differences depending on national origin, age and educational background. Furthermore, athletes participating in closed skill sports have higher team-oriented creativity than those engaged in open skill sports. Relevant avenues for future research are highlighted. Finally, validated constructs of entrepreneurship competencies cannot be applied to the sport context. In contrast to the three-factorial construct by Capella-Peris, we suggest five reliable entrepreneurship competencies. Practical Implications The findings are beneficial for practitioners involved in sport entrepreneurship education. Athletes and coaches are advised on how to plan their entrepreneurial activity depending on prevalent competencies set in their sports field to best prepare them for this potential alternative career path. Research contribution The proposed more specific entrepreneurship competencies in the context of sport provide a foundation for future research in the increasingly important field of sport entrepreneurship. Originality/Value This paper provides important data and avenues for reflection on how to tailor entrepreneurial education programmes for athletes from different personal and sporting backgrounds.

Application of EMI technique in crack propagation under the block loading conditions for AA6061 alloy

The behaviour of a component under real/random loading conditions can be studied by converting the random load into block load. Therefore, knowledge of the initiation and propagation of a crack under block loading conditions is very important for the safety and reliability of machine components / structures. Electromechanical impedance (EMI) is a real-time damage evaluation technique in which simultaneous use of the high-frequency mechanical excitations and responses of the structure are made by employing a piezoelectric transducer. In the present study, an experimental methodology to monitor fatigue crack initiation and propagation under block loading conditions for AA6061 aluminium alloy has been studied with the help of the EMI technique. The piezoelectric sensor bonded on the Compact Tension (CT) specimen acts as an actuator and sensor both. The conductance signature provided a sufficient information about the damage and crack growth under high low and low high block loading conditions. The conventional crack growth rate versus range of stress intensity factor plot matches well with the crack growth rate versus shift in resonant frequency.

Advanced surface roughness characterization using 3D scanning technologies and YOLOv4

In modern manufacturing, providing high-quality surface finishes to mechanical parts is critical to maintaining product integrity and optimizing the performance of mechanical systems. Surface roughness directly affects various aspects of part functionality, including friction, wear resistance, and overall durability. Therefore, accurate and efficient assessment of surface finish quality is of paramount importance to ensure the reliability and longevity of mechanical components. To meet this need, this study proposes an intelligent system that leverages the capabilities of deep learning and computer vision technologies to estimate the surface roughness of machined steel parts. By combining these advanced techniques, manufacturers can automate and improve the surface quality inspection process, resulting in increased productivity and reduced costs associated with manual inspection methods. This paper proposes an innovative method for determining surface roughness after machining by combining 3D scanning technologies with the deep learning algorithm YOLOv4.

Fundamental Drivers of Metal Fatigue Failure and Performance

Understanding fatigue behavior is critical for ensuring the safety and reliability of various engineering components and structures. Fatigue-related failures have historically led to catastrophic events, including aviation accidents and infrastructure collapses, resulting in significant economic and reputational damage. This study delves into the fatigue processes, focusing on crack initiation, growth mechanisms, the impact of microstructure, stress concentrations, surface finish, mean stress, frequency, and environmental conditions on fatigue life. It also explores fatigue principles, stress cycles, S-N curves, fatigue limits, and the stages of crack formation and propagation. By comprehensively analyzing fatigue behavior, engineers can design safer components, optimize materials, and extend product lifespans, thus facilitating technological advancements, predictive maintenance, and risk reduction across industries such as aerospace, automotive, and biomedical sectors.

Testing the Model for Enhancing Administrative Transparency in Interaction with E-Government Development Programs in the Social Security Organization

Objective: The aim of this research is to examine and test the model for enhancing administrative transparency in interaction with e-government development programs in the Social Security Organization. Methodology: This research is applied in terms of purpose and descriptive-survey in terms of data collection method. Data were collected using a standardized researcher-made questionnaire. The statistical population in the quantitative section includes all employees of the Social Security Organization. The sampling method for the present study, considering the target population, is stratified sampling. Approximately 65,000 individuals are in the population, and based on Cochran's formula, a sample of 385 individuals was selected. Subsequently, the composite reliability and the reliability of each research component were calculated, with the results indicating the reliability of the measurement tool. Additionally, the divergent and convergent validity of the questionnaire suggests the validity of the instrument. For data analysis, structural equation modeling was employed using the Smart PLS4 software. Findings: The results indicate that e-government has a significant impact on the growth and development of the Social Security Organization. Administrative structure and processes significantly influence managerial oversight, public oversight, and public accountability. Environmental factors also significantly impact managerial oversight, public oversight, and public accountability. Furthermore, managerial factors have a significant effect on managerial oversight, public oversight, and public accountability. Organizational culture and atmosphere significantly affect managerial oversight, public oversight, and public accountability. Finally, managerial oversight, public oversight, and public accountability have a significant impact on e-government. Conclusion: The model for enhancing administrative transparency in interaction with e-government development programs in the Social Security Organization can be proposed as a comprehensive and practical package for all managers of executive agencies in general and for the Social Security Organization in particular.