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Journal articles on the topic 'Failure physics'

Author: Grafiati

Published: 1 February 2025

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1

Pecht, Michael, and Abhijit Dasgupta. "Physics-of-Failure: An Approach to Reliable Product Development." Journal of the IEST 38, no. 5 (September 1, 1995): 30–34. http://dx.doi.org/10.17764/jiet.2.38.5.y3561m03801h0082.

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Reliability assessments based on physics-of-failure methods incorporate reliability into the design process to prevent parts from failing in service. An understanding of the physics-of-failure is necessary in applications that afford little opportunity for testing, or for reliability growth. This paper presents an overview of physics-of-failure and a case study of the application of physics-of-failure to a specific failure mechanism called conductive filament formation.

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THADURI, ADITHYA, A. K. VERMA, V. GOPIKA, RAJESH GOPINATH, and UDAY KUMAR. "FAILURE MODELING OF CONSTANT FRACTION DISCRIMINATOR USING PHYSICS OF FAILURE APPROACH." International Journal of Reliability, Quality and Safety Engineering 20, no. 03 (June 2013): 1340002. http://dx.doi.org/10.1142/s0218539313400020.

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Due to several advancements in the technology trends in electronics, the reliability prediction by the constant failure methods and standards no longer provide accurate time to failure. The physics of failure methodology provides a detailed insight on the operation, failure point location and causes of failure for old, existing and newly developed components with consideration of failure mechanisms. Since safety is a major criteria for the nuclear industries, the failure modeling of advanced custom made critical components that exists on signal conditioning module are need to be studied with higher confidence. One of the components, constant fraction discriminator, is the critical part at which the failure phenomenon and modeling by regression is studied in this paper using physics of failure methodology.

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3

Williams, Hollis. "Physics of Brittle Failure during Impact." Physics Teacher 62, no. 7 (October 1, 2024): 575–78. http://dx.doi.org/10.1119/5.0136324.

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4

SATO, Atsuro, Mikio SAKAI, and Seiichi KOSHIZUKA. "450 Slope Failure in Physics Based CG." Proceedings of The Computational Mechanics Conference 2008.21 (2008): 774–75. http://dx.doi.org/10.1299/jsmecmd.2008.21.774.

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5

Torigoe, Eugene T., and Gary E. Gladding. "Connecting symbolic difficulties with failure in physics." American Journal of Physics 79, no. 1 (January 2011): 133–40. http://dx.doi.org/10.1119/1.3487941.

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6

Jiao, Jian, Xinlin De, Zhiwei Chen, and Tingdi Zhao. "Integrated circuit failure analysis and reliability prediction based on physics of failure." Engineering Failure Analysis 104 (October 2019): 714–26. http://dx.doi.org/10.1016/j.engfailanal.2019.05.021.

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7

Rovelli, C., and I. A. Rybakova. "PHYSICS NEEDS PHILOSOPHY. PHILOSOPHY NEEDS PHYSICS." Metaphysics, no. 3 (December 15, 2021): 36–46. http://dx.doi.org/10.22363/2224-7580-2021-3-36-46.

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Contrary to claims about the irrelevance of philosophy for science, I argue that philosophy has had, and still has, far more influence on physics than is commonly assumed. I maintain that the current anti-philosophical ideology has had damaging effects on the fertility of science. I also suggest that recent important empirical results, such as the detection of the Higgs particle and gravitational waves, and the failure to detect supersymmetry where many expected to find it, question the validity of certain philosophical assumptions common among theoretical physicists, inviting us to engage in a clearer philosophical reflection on scientific method.

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Zhang, Ren Peng, Yi Yong Hu, and Jun Yao. "Reliability Enhancement Test on Undercarriage Signal Light Box." Applied Mechanics and Materials 291-294 (February 2013): 2403–7. http://dx.doi.org/10.4028/www.scientific.net/amm.291-294.2403.

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Based on the theory of failure physics, reliability enhancement test is a test technology of stimulation in order to improve reliability by discovering, researching and curing failure. In this paper, the main factors inducing failure modes of undercarriage light box were analyzed, and the environmental sensitive stresses affecting reliability were determined. The testing program was designed and test profiles were established based on the theory of reliability enhancement test. Additionally, the test results were analyzed based on failures of products in order to carry out improvement measures.

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Qiu, Wenhao, Guangyao Lian, Mingxi Xue, and Kaoli Huang. "Physics of failure-based failure mode, effects, and criticality analysis for Integrated Circuits." Systems Engineering 21, no. 6 (June 25, 2018): 511–19. http://dx.doi.org/10.1002/sys.21451.

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10

Osterman, M. D. "A Physics of Failure Approach to Component Placement." Journal of Electronic Packaging 114, no. 3 (September 1, 1992): 305–9. http://dx.doi.org/10.1115/1.2905455.

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Traditionally, placement techniques have focused on improving rotability based on minimizing the total wire length between interconnected components. However, electronic card assembly (ECA) reliability, which is measured in terms of time to failure, cycles to failure, or the hazard rates of the individual components, the interconnections, and the PWB, is also affected by component placement. This paper discusses component placement for reliability based on a failure model which incorporates component temperature, a base operating temperature, a threshold temperature, and change in temperature. Placement procedures are developed so as to minimize the time to failure or the total hazard rate of the components on a PWB utilizing a forced convection cooling.

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11

THADURI, ADITHYA, A. K. VERMA, V. GOPIKA, RAJESH GOPINATH, and UDAY KUMAR. "STRESS FACTOR AND FAILURE ANALYSIS OF CONSTANT FRACTION DISCRIMINATOR USING DESIGN OF EXPERIMENTS." International Journal of Reliability, Quality and Safety Engineering 20, no. 03 (June 2013): 1340003. http://dx.doi.org/10.1142/s0218539313400032.

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Reliability prediction using traditional approaches were implemented at earlier stages of electronics. But due to advancements in science and technology, the above models are outdated. The alternative approach, physics of failure provides exhaustive information on basic failure phenomenon with failure mechanisms, failure modes and failure analysis becomes prominent because this method depends on factors like materials, processes, technology, etc., of the component. Constant fraction discriminators which is important component in NFMS needs to study failure characteristics and this paper provides this information on failure characteristics using physics of failure approach. Apart from that, the combined physics of failure approach with the statistical methods such as design of experiments, accelerated testing and failure distribution models to quantify time to failure of this electronic component by radiation and temperature as stress parameters. The SEM analysis of the component is carried out by decapsulating the samples and studied the impact of stress parameters on the device layout.

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12

Watts, Milton, and K. Rob Harker. "Comparative Reliability Prediction Using Physics of Failure Models." Additional Conferences (Device Packaging, HiTEC, HiTEN, and CICMT) 2011, HITEN (January 1, 2011): 000189–95. http://dx.doi.org/10.4071/hiten-paper3-mwatts.

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Quartzdyne Electronics has invested millions of device test hours in life testing of circuits in both powered and un-powered tests. In addition to time at temperature, these tests include thermal cycling and high impact drop testing. Recent projects have required the use of larger packages and components as we have expanded the variety of circuits that we build. It is desirable to predict the effects of these changes on long-term reliability before investing in tooling. In this study we will compare a new design which contains these larger components to the simpler, smaller designs for which we have extensive life-test data. Using a physics-of-failure approach, component mounting stresses will be analyzed using finite element modeling. These results will be compared to pre and post-aging shear strengths of actual components of varying sizes. Aging models will then be developed to predict the reliability of the new design based on the comparative stress margins of the individual components coupled with circuit complexity. Once validated, the aging models will enable reliability prediction and trade-off analysis for future designs.

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13

Pecht, Michael, and Jie Gu. "Physics-of-failure-based prognostics for electronic products." Transactions of the Institute of Measurement and Control 31, no. 3-4 (June 2009): 309–22. http://dx.doi.org/10.1177/0142331208092031.

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Hall, Gavin D. R., and Derryl D. J. Allman. "Stress Migration Modeling Using Probabilistic Physics of Failure." IEEE Transactions on Device and Materials Reliability 18, no. 4 (December 2018): 508–19. http://dx.doi.org/10.1109/tdmr.2018.2880226.

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15

Family, Fereydoon. "Physics of Cell Adhesion Failure and Human Diseases." Physics Procedia 57 (2014): 24–28. http://dx.doi.org/10.1016/j.phpro.2014.08.126.

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16

Tilgner, Rainer. "Physics of failure for interconnect structures: an essay." Microsystem Technologies 15, no. 1 (May 8, 2008): 129–38. http://dx.doi.org/10.1007/s00542-008-0630-3.

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17

Pecht, Michael, Abhijit Dasgupta, Donald Barker, and Charles T. Leonard. "The reliability physics approach to failure prediction modelling." Quality and Reliability Engineering International 6, no. 4 (September 1990): 267–73. http://dx.doi.org/10.1002/qre.4680060409.

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18

Xu, Ming, Feng Ming Lu, and Chen Hui Zeng. "Research and Validation of ICs' TDDB Physics-of-Failure Model." Applied Mechanics and Materials 313-314 (March 2013): 281–86. http://dx.doi.org/10.4028/www.scientific.net/amm.313-314.281.

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In the new era, the reliability technology based on physics of failure (PoF) is playing an increasingly important role in development of electronic equipment. PoF models of electronic products, as the foundation and core of this advanced technology, are the main point of engineering application. With continual scaling of VLSI in electronic equipment, the electric field across gate oxide becomes higher and higher and affects the reliability of semiconductor device greatly. In this paper, TDDB failure mechanism and Physics-of-Failure model was researched firstly. Then the test sample was designed and processed, and the test verification program for TDDB Physics-of-Failure model was carried out to develop the test verification, collect and process test data. Through analyzing test data, the parameters of TDDB model were determined and modified to ensure the Physics-of-Failure model precision and the model could be used in engineering. Based on modified model, the reliability of integrated circuits can be evaluated at designing stage. And the inherent reliability of integrated circuits in electronic equipment could be improved by design optimization to reduce the risk in the process of using.

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19

Suhir, E. "Statistics-related and reliability-physics-related failure processes in electronics devices and products." Modern Physics Letters B 28, no. 13 (May 30, 2014): 1450105. http://dx.doi.org/10.1142/s021798491450105x.

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The well known and widely used experimental reliability "passport" of a mass manufactured electronic or a photonic product — the bathtub curve — reflects the combined contribution of the statistics-related and reliability-physics (physics-of-failure)-related processes. When time progresses, the first process results in a decreasing failure rate, while the second process associated with the material aging and degradation leads to an increased failure rate. An attempt has been made in this analysis to assess the level of the reliability physics-related aging process from the available bathtub curve (diagram). It is assumed that the products of interest underwent the burn-in testing and therefore the obtained bathtub curve does not contain the infant mortality portion. It has been also assumed that the two random processes in question are statistically independent, and that the failure rate of the physical process can be obtained by deducting the theoretically assessed statistical failure rate from the bathtub curve ordinates. In the carried out numerical example, the Raleigh distribution for the statistical failure rate was used, for the sake of a relatively simple illustration. The developed methodology can be used in reliability physics evaluations, when there is a need to better understand the roles of the statistics-related and reliability-physics-related irreversible random processes in reliability evaluations. The future work should include investigations on how powerful and flexible methods and approaches of the statistical mechanics can be effectively employed, in addition to reliability physics techniques, to model the operational reliability of electronic and photonic products.

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Le, G. T., L. Mastropasqua, J. Brouwer, and S. B. Adler. "Simulation-Informed Machine Learning Diagnostics of Solid Oxide Fuel Cell Stack with Electrochemical Impedance Spectroscopy." Journal of The Electrochemical Society 169, no. 3 (March 1, 2022): 034530. http://dx.doi.org/10.1149/1945-7111/ac59f4.

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This paper reports our initial development of simulation-informed machine learning algorithms for failure diagnostics in solid oxide fuel cell (SOFC) systems. We used physics-based models to simulate electrochemical impedance spectroscopy (EIS) response of a short SOFC stack under normal conditions and under three different failure modes: fuel maldistribution, delamination, and oxidant gas crossover to the anode channel. These data were used to train a support vector machine (SVM) model, which is able to detect and differentiate these failures in simulated data under various conditions. The SVM model can also distinguish these failures from simulated uniform degradation that often occurs with long-term operation. These encouraging results are guiding our ongoing efforts to apply EIS as a failure diagnostic for real SOFC cells and short stacks.

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21

Felixfu2022 and Nicolas P. Avdelidis. "Hybrid Prognostics for Aircraft Fuel System: An Approach to Forecasting the Future." PHM Society European Conference 8, no. 1 (June 27, 2024): 9. http://dx.doi.org/10.36001/phme.2024.v8i1.4130.

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The copious volumes of data collected incessantly from diverse systems present challenges in interpreting the data to predict system failures. The majority of large organizations employ highly trained experts who specialize in using advanced maintenance equipment and have specific certification in predictive maintenance (PdM). Prognostics and health management (PHM) connects research on deterioration models to strategies for PdM. Prognostics refer to the process of estimating the time until failure and the associated risk for one or more current and potential failure modes. Prognostics aim to provide guidance by alerting to imminent failures and predicting the remaining useful life (RUL). This eventually leads to improved availability, dependability, and safety, while also reducing maintenance costs. This research work diverges from existing established prognostic methodologies by emphasising the use of hybrid prognostics to predict the future performance of an aircraft system, especially the point in which the system will cease to operate as intended, often referred to as its time to failure. We have developed a new method that combines a physics-based model with the physics of failure (PoF) and a multiple-layered hyper-tangent-infused data-driven approach. The results are useful. The authors retrieved datasets for analysis using a laboratory aircraft fuel system and simulation model. Consequently, the comparative results demonstrate that the proposed hybrid prognostic approach properly estimates the RUL and demonstrates strong application, availability, and precision.

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22

Caswell, Greg. "Using Physics of Failure to Predict System Level Reliability for Avionic Electronics." International Symposium on Microelectronics 2013, no. 1 (January 1, 2013): 000031–38. http://dx.doi.org/10.4071/isom-2013-ta21.

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Today's analyses of electronics reliability at the system level typically use a “black box approach”, with relatively poor understanding of the behaviors and performances of such “black boxes” and how they physically and electrically interact. Box level analyses tend to use simplistic empirical predictive models, and the effort is typically driven by cost and time constraints. The incorporation of more rigorous and more informative approaches and techniques needs to better understand and to take advantage of the advances in user interfaces and intelligent data capture, which will allow for a broader range of users and for similar resource allocation. Understanding the Physics of Failure (PoF) is imperative. It is a formalized and structured approach to Failure Analysis/Forensics Engineering that focuses on total learning and not only fixing a particular current problem. It can involve material science, physics and chemistry; also variation theory and probabilistic mechanics. The approach necessitates an up-front understanding of failure mechanisms and variation effects. In this paper we will present an explanation of various physical models that could be deployed through this method, namely, wire bond failures; thermo-mechanical fatigue; and vibration. We will provide insight into how this approach is being accepted by system assemblers, as it allows for failure oriented accelerated testing, for substitution or “what if” analyses in lieu of the traditional accelerated life testing. This paper will also provide insight into a process to develop viable test plans and a tool that facilitates the entire process so that minimal testing is performed, thus reducing costs and schedule impacts. Examples of this approach will be presented.

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Tosney, William, and Andrew Quintero. "Orbital Experience from an Integration and Test Perspective." Journal of the IEST 41, no. 6 (November 17, 1998): 34–41. http://dx.doi.org/10.17764/jiet.41.6.731317376m64t38u.

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Space vehicle schedule and cost reduction strategies tend to focus on test optimization without a comprehensive analytical approach to the impact on mission success. This study provides valuable stochastic insights into orbital physics of failure while identifying potential relationships to ground integration and test processes by analyzing data across a large population of space vehicle programs. Failure data analysis uses reliability growth modeling techniques to provide greater insight into environmental test effectiveness. Results show correlations between orbital failures, environmental test, hardware retest, and hardware categories. Test strategies are discussed to mitigate risk of orbital failures for hardware subjected to varying degrees of retest and late integration.

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24

Ryspaeva, Cholpon, Gulmira Belekova, Kakhramonzhon Shakirov, Gulzat Mukambetova, and Mahfuza Ahunjanova. "Competence-based approach to formation of students� learning motivation." Scientific Herald of Uzhhorod University Series Physics 2024, no. 55 (January 12, 2024): 1880–89. http://dx.doi.org/10.54919/physics/55.2024.188ot0.

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Relevance. Building an educational process that can serve as a basis for the formation and growth of motivational spheres of students is one of the urgent problems facing modern education in the context of improving training in higher and secondary vocational educational institutions.Purpose. The research aims to study the process of formation of motivation in students of higher educational institutions of Kyrgyzstan, on the example of Pedagogical College of the Kyrgyz State University named after I. Arabaev, International University of Innovative Technologies and Batken State University.Methodology. The following methods were used: structural and functional method, method of synthesis, logical and comparative analysis, and method of generalisation. The following methods were used in the study of this issue: K. Zamfir�s methodology �Study of motivation of learning activity� (edited by A. Rean); A. Rean�s methodology �Diagnostics of personality on motivation to success and fear of failure�.Results. According to the study, most students are more motivated internally, they have an average level of motivation. Having analysed students� motivation for success and fear of failure, it was determined that most of the respondents have a strong motivation and desire for success, and only 14% of students have a predisposition to failure. The results emphasise the value of building an educational process based on a competency-based approach.Conclusions. Competency-based approach enhances student engagement by enabling them to apply new knowledge in their personal and professional lives. The practical significance of this study lies in the fact that all theoretical provisions, conclusions, and recommendations can be used in educational institutions by teachers and students to improve knowledge about the formation of the motivational sphere of students in the university, as well as by other scientists for a detailed study of this problem.

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Oyewole, O. K., D. O. Oyewole, M. G. Zebaze Kana, and W. O. Soboyejo. "Reliability and Physics Failure of Stretchable Organic Solar Cells." MRS Advances 1, no. 1 (2016): 21–26. http://dx.doi.org/10.1557/adv.2016.21.

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ABSTRACTOrganic solar (OPV) cells are cheap electronics that can replace the widely used high cost silicon-based electronics for electricity generation. They are cheap because of the easy techniques involved in their fabrication processes and they can be produced to cover a large surface area. However, the current low performance of organic electronics has been traced to failure due to interfacial adhesion problems, material processes, and service conditions. Therefore, transportation of charge carriers across the bulk heterojunction system of OPV cells becomes very difficult in the presence of these flaws. In this paper a combined experimental and computational technique is used to study the reliability and physics failure of stretchable OPV cells. Interfacial adhesion energies in the layered structures of OPV cells are measured and compared with theoretical estimated energies. The limit stresses/strains applied on layered OPV cells during service condition are estimated using critical values of the measured interfacial adhesion. The results obtained are, therefore, explained to improve the design of reliable OPV cells.

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26

Gassner, Gert, Franz Langmayr, and Peter Prenninger. "Physics of Failure based Damage Modeling for SOFC Development." ECS Transactions 25, no. 2 (December 17, 2019): 1263–72. http://dx.doi.org/10.1149/1.3205655.

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27

Billah, K. Yusuf, and Robert H. Scanlan. "Resonance, Tacoma Narrows bridge failure, and undergraduate physics textbooks." American Journal of Physics 59, no. 2 (February 1991): 118–24. http://dx.doi.org/10.1119/1.16590.

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28

Squiller, D., H. Greve, E. Mengotti, and F. P. McCluskey. "Physics-of-failure assessment methodology for power electronic systems." Microelectronics Reliability 54, no. 9-10 (September 2014): 1680–85. http://dx.doi.org/10.1016/j.microrel.2014.07.123.

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29

Kimseng, K., M. Hoit, N. Tiwari, and M. Pecht. "Physics-of-failure assessment of a cruise control module." Microelectronics Reliability 39, no. 10 (October 1999): 1423–44. http://dx.doi.org/10.1016/s0026-2714(99)00018-9.

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30

Shinn, Terry. "Failure or Success? Interpretations of 20th Century French Physics." Historical Studies in the Physical and Biological Sciences 16, no. 2 (January 1, 1986): 353–69. http://dx.doi.org/10.2307/27757569.

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31

Shinn, Terry. "Failure or Success? Interpretations of 20th Century French Physics." Historical Studies in the Physical and Biological Sciences 17, no. 2 (January 1, 1987): 361. http://dx.doi.org/10.2307/27757588.

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32

Guo, Xiao Xi, Chuan Ri Li, and Long Tao Liu. "Vibration Fatigue Analysis of the Solder Connector." Applied Mechanics and Materials 105-107 (September 2011): 294–98. http://dx.doi.org/10.4028/www.scientific.net/amm.105-107.294.

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With the increasing problems of fatigue failure of PCB in aeronautic and astronautic electronic chassis, the paper proposes a life prediction method of the solder connector based on physics of failure by simulation and physical test. The virtual modal and random vibration response of the box should be solved by finite element method in the ANSYS software, and these results have been verified by modal test and random vibration test. While the structure parameter and the environment stress of the box, the results of the simulation as the input of the vibration fatigue physics of failure model, the life of solder connector could be computed. There is a comparison between results from the CalcePWA software and it from physics of failure model and simulation.

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33

Lee, Hoyong, and Ighoon Lee. "Requirements Development for Intermittent Failure Detection of an Avionics Backplane based on Physics-of-Failure." Journal of the Korean Society for Aviation and Aeronautics 27, no. 3 (September 2019): 15–23. http://dx.doi.org/10.12985/ksaa.2019.27.3.015.

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34

Thaduri, Adithya, Ajit Kumar Verma, and Uday Kumar. "Comparison of failure characteristics of different electronic technologies by using modified physics-of-failure approach." International Journal of System Assurance Engineering and Management 6, no. 2 (October 5, 2014): 198–205. http://dx.doi.org/10.1007/s13198-014-0301-y.

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35

Zhang, Lingjie, Ning Hu, Zhe Lai, Jieyi Zhang, and Hongqi Yang. "Reliability simulation analysis technology for electronic products based on failure physics and failure propagate models." IET Conference Proceedings 2024, no. 12 (January 2025): 338–44. https://doi.org/10.1049/icp.2024.3455.

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Xu, Ren Xiao, and Yang Liu. "Failure Modes Mechanisms Effects Analysis for Refrigeration Device." Applied Mechanics and Materials 288 (February 2013): 69–74. http://dx.doi.org/10.4028/www.scientific.net/amm.288.69.

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FMMEA (failure mode, mechanisms, and effects analysis) is an effective tool for the life-cycle management of products and devices. We conducted an FMMEA for a refrigeration device at the request of a corporation. This paper demonstrates the process of our analysis of the compressor by employing Ganesan’s methodology. The results are listed in a table, including the physics of failures, risk priorities and parameters for monitoring. This paper also provides health-state assessment approaches based on FMMEA results and values of relevant parameters using fusion approach. Such assessment can be used for remaining useful life (RUL) estimation. Additionally, the paper illustrates our approach of computer-program-based automatic identification of failure using data of parameters retrieved from sensors.

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Zhang, F., Z. Zhou, Y. Wang, D. Wang, M. Wu, and L. Zhu. "An SEU fault injection platform for radiation-harden design debugging in the FPGA." Journal of Instrumentation 17, no. 08 (August 1, 2022): P08007. http://dx.doi.org/10.1088/1748-0221/17/08/p08007.

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Abstract An SEU fault injection platform was designed to ease the debugging of radiation-harden design in FPGA. The platform includes the FPGA being tested, the functional firmware being debugged, the essential-bit extraction algorithm based on Python, and the random fault injection algorithm. The platform can inject single-bit SEU failures, adjacent two-bit SEU failures, and three-bit SEU failures. It works in two modes: normal injection mode and essential-bit injection mode. Functional failure rate is the performance metric which used to evaluate the development. It is the probability of triggering a DUT function failure. In this experiment, the SEU fault injection platform is verified by measuring whether TCP/IP communication links are disconnected due to SEU faults. Experimental results show that the probability of TCP/IP link disconnection in normal injection mode is 0.13%, 0.23% and 0.25% respectively when random injection of single-bit SEU failure, adjacent two-bit SEU failure and multi-bit SEU failure occurs 10,000 times. In the essential-bit injection mode, the probability of TCP/IP link disconnection caused by single-bit SEUs failure, adjacent two-bit SEUs failure and three-bit SEUs failure is 0.87%, 6.97% and 11.76% respectively, indicating a significant increase in the functional failure rates. This shows that the essential-bit injection mode can be used to expose problems more quickly and accelerate the debugging process of FPGA radiation-harden design.

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38

Shao, Jiang, Cheng Hui Zeng, and Yong Hong Li. "Application of Physics of Failure Method in Reliability Design of Electronic Products." Applied Mechanics and Materials 44-47 (December 2010): 819–23. http://dx.doi.org/10.4028/www.scientific.net/amm.44-47.819.

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Based on reliability theory on physics of failure, reliability information of electronic products is predicted by modeling and simulation methods. Various engineering analysis techniques are utilized and the product’s reliability is analyzed and designed. Analysis results on an electronic product example show that physics of failure method can find week problems of reliability design, advance prevention measures, mend the design to eliminate potential faults, thus improve the inherent reliability of electronic product ultimately.

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Barela, Phillip, and Steven Cornford. "A Systematic Approach to Hardware Qualification." Journal of the IEST 39, no. 4 (July 31, 1996): 33–39. http://dx.doi.org/10.17764/jiet.2.39.4.k557h02814259621.

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A systematic approach for the development of a hardware qualification approach is described. This approach stems from the need to address the "Catch-22" of not flying new technology because it has not flown. A physics of failure approach is used to identify failure modes, and the impact and likelihood of these failures on the mission requirements is plotted in a Requirements Matrix. These same failure modes are plotted against the effectiveness of the available preventions, analyses, control, and tests (PACTs) at screening for, or eliminating, these failure modes in a test effectiveness matrix. Matrix multiplication results in a ranked set of PACTs that can be sorted according to cost and redundancy with other PACTs. This and other information resulting from the process allows project managers to make more informed decisions regarding the cost and risk tradeoffs inherent in any qualification program.

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Qin, Li, and An Li Shi. "Reliability Test and Evaluation Analysis of Silicon Pressure Sensor under Vibration Stress." Advanced Materials Research 383-390 (November 2011): 6969–74. http://dx.doi.org/10.4028/www.scientific.net/amr.383-390.6969.

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The model silicon pressure sensor was taken as the object; in this paper, we built failure physics equation of sensor under the vibration stress based on the failure modes and failure mechanism of pressure sensor, and using vibration stress as the acceleration factor to process accelerated life testing under invariableness stress. The results show that failure physics equation of sensor yields the inverse power law relationship. The estimated value of reliability character and accelerated life equation of sensor under the vibration stress was attained through analyzing testing data and the average life and reliable life of sensor has been attained through reliability evaluation.

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Shao, Jiang, and Chen Hui Zeng. "Application of Physics-of-Failure Method in Reliability Engineering of Electronic Products." Applied Mechanics and Materials 313-314 (March 2013): 697–701. http://dx.doi.org/10.4028/www.scientific.net/amm.313-314.697.

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Physics-of-Failure (PoF) represents one approach to reliability assessment based on modeling and simulation that relies on understanding the physical processes contributing to the appearance of the critical failures. Firstly the connotation and meaning of PoF method were analyzed here, the inherence relation between PoF and reliability was expatiated, the PoF based reliability method and current reliability method based on probability statistics were compared, their differences and relationships were discussed here. Then the application condition of PoF method in reliability engineering in European and American developed country and China were summarized, the PoF based reliability engineering technologies were introduced systemically from several aspects, such as reliability design and analysis, reliability test and validation, maintain and support. Finally, combining with the developing characteristics of military materiel during the new period, some future investigation directions and application foregrounds were prospected.

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Snook, Ian, Jane Marshall, and Robert Newman. "Physics of Failure as an Integrated Part of Design for Reliability." Journal of the IEST 47, no. 1 (September 14, 2004): 67–73. http://dx.doi.org/10.17764/jiet.47.1.74q481n144708775.

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A study of the use of Physics of Failure (PoF) methods was undertaken as part of a collaboratively funded United Kingdom Government Department of Industry (UK DTI) project for developing a holistic methodology and assessment model for the enhancement of electronics reliability. Several case studies were conducted to review the use of PoF techniques. The study concluded PoF methods, and in particular life modeling, are essential tools in design for reliability. PoF analysis can also be used to establish reliability enhancement testing (RET) and environmental stress screening (ESS) conditions. A guide for the effective use and inclusion of the PoF methods in the product design and development process was developed and described. Use of the techniques facilitates accurate design right, thereby avoiding redesign and retest cycles, with consequent cost savings and reduced product development times. The PoF method has limitations. It is essentially a bottom-up approach assessing time to failure due to known failure mechanisms. Consequently, it is difficult to apply to full systems, has limitations in assessing failure rate prior to the onset of life-limiting wear out, and is dependent on identifying and having a validated model for all potential failure mechanisms.

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Nakarmi, Upama, Mahshid Rahnamay Naeini, Md Jakir Hossain, and Md Abul Hasnat. "Interaction Graphs for Cascading Failure Analysis in Power Grids: A Survey." Energies 13, no. 9 (May 2, 2020): 2219. http://dx.doi.org/10.3390/en13092219.

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Understanding and analyzing cascading failures in power grids have been the focus of many researchers for years. However, the complex interactions among the large number of components in these systems and their contributions to cascading failures are not yet completely understood. Therefore, various techniques have been developed and used to model and analyze the underlying interactions among the components of the power grid with respect to cascading failures. Such methods are important to reveal the essential information that may not be readily available from power system physical models and topologies. In general, the influences and interactions among the components of the system may occur both locally and at distance due to the physics of electricity governing the power flow dynamics as well as other functional and cyber dependencies among the components of the system. To infer and capture such interactions, data-driven approaches or techniques based on the physics of electricity have been used to develop graph-based models of interactions among the components of the power grid. In this survey, various methods of developing interaction graphs as well as studies on the reliability and cascading failure analysis of power grids using these graphs have been reviewed.

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Burgess, David L. "Lessons from Sudoku." EDFA Technical Articles 8, no. 1 (February 1, 2006): 25–28. http://dx.doi.org/10.31399/asm.edfa.2006-1.p025.

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Abstract Failure analysis requires a working knowledge of physics, technology, materials, manufacturing practices, analytical techniques, and more. It is difficult to imagine what failure analysis would be like if all the laws of physics were perfectly apparent and all the challenges of sample preparation and testing were removed. Eliminating those considerations, failure analysis would be more like Sudoku. Sudoku is a simple number puzzle enjoyed by both children and adults. The simplicity of Sudoku compared to failure analysis is the point. Although Sudoku is starkly simple, the process is challenging to the best of us. Good and bad problem-solving practices are clearly exposed by the experience of solving a few Sudoku puzzles. Some insights that are brilliantly clear in Sudoku are equally true in failure analysis.

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Miller, Johanna L. "A solid-state failure of the Born–Oppenheimer approximation." Physics Today 76, no. 2 (February 1, 2023): 16–17. http://dx.doi.org/10.1063/pt.3.5172.

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Nguyen, Ryan, Shubhendu Kumar Singh, and Rahul Rai. "Physics-infused fuzzy generative adversarial network for robust failure prognosis." Mechanical Systems and Signal Processing 184 (February 2023): 109611. http://dx.doi.org/10.1016/j.ymssp.2022.109611.

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Kanert, W. "Robustness Validation – A physics of failure based approach to qualification." Microelectronics Reliability 54, no. 9-10 (September 2014): 1648–54. http://dx.doi.org/10.1016/j.microrel.2014.07.010.

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Tryon, Robert, Animesh Dey, and Ganapathi Krishnan. "Microstructural-Based Physics of Failure Models to Predict Fatigue Reliability." Journal of the IEST 50, no. 2 (October 1, 2007): 73–84. http://dx.doi.org/10.17764/jiet.50.2.70x66635u7q7322j.

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The fatigue life of materials is strongly influenced by their microstructure. The scatter in fatigue life is caused by the scatter in grain size, grain orientation, and stresses induced in each grain of the material due to external loading. A novel microstructural fatigue crack growth model that accounts for real-life variability in the material is presented in this study. Ti-6Al-4V, a common aerospace titanium alloy used in numerous turbine engines, has been studied to predict its fatigue life and scatter at load ratios of 0.1 and -1.0. The predictions have been compared with experimental data. Results indicate that the microstructural material models accurately predict the behavior of Ti-6Al-4V.

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Liu, Jingcun, Guogang Zhang, Bixuan Wang, Wanping Li, and Jianhua Wang. "Gate Failure Physics of SiC MOSFETs Under Short-Circuit Stress." IEEE Electron Device Letters 41, no. 1 (January 2020): 103–6. http://dx.doi.org/10.1109/led.2019.2953235.

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Zhang, Yongqiang, Zongchang Xu, and Chunyang Hu. "Computing environmental life of electronic products based on failure physics." Journal of Systems Engineering and Electronics 27, no. 2 (April 20, 2016): 493–500. http://dx.doi.org/10.1109/jsee.2016.00052.

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