Abstract
Background: In the face of the development trend of high-end manufacturing servitization, the reliability standard of manufacturing products gradually increases.
Objective: In order to accurately predict the product life cycle, the accelerated degradation evaluation technology could be applied to significantly shorten the experiment duration. As the technologies of intelligent manufacturing and industrial big data develop, the theory of accelerated degradation evolves as well.
Methods: Based on the scientific knowledge mapping, co-author network and co-existence network, 22283 pertinent articles since the year 2010 have been collected to conduct a bibliometric study.
Results: The results show that the accelerated degradation reliability assessment spans over many research fields, and achieves great development in the mathematical modeling and experiment verification.
Conclusion: To further the study, more efforts are expected in the areas such as building effective evaluation systems and enhancing the credibility of the assessment outcomes, as more advanced sensory data and wireless communication technologies become available.
Keywords: Accelerated degradation, bibliometric analysis, evaluation system, manufacturing, reliability, construction industry.
[1]
Huang Q, He J. The core capability, function and strategy of Chinese manufacturing industry: Comment on “Chinese Manufacturing 2025”. China Industrial Economics 2015; (06): 5-17.
[2]
Shi J, Liu Z, Zhang H, et al. Life cycle assessment: State of the art and future perspectives. Recent Pat Mech Eng 2015; 8(3): 211-21.
[http://dx.doi.org/10.2174/2212797608666150729231737]
[http://dx.doi.org/10.2174/2212797608666150729231737]
[3]
Nobile L, Gentilini C. Three dimensional frame structures with edge-cracks of uncertain depth and location. Recent Pat Mech Eng 2008; 1(1): 12-21.
[http://dx.doi.org/10.2174/2212797610801010012]
[http://dx.doi.org/10.2174/2212797610801010012]
[4]
Simoni L, Mazzanti G, Montanari GC, et al. A general multi-stress life model for insulation materials with or without evidence for thresh-olds. IEEE Trans Electr Insul 1993; 28(3): 349-64.
[http://dx.doi.org/10.1109/14.236212]
[http://dx.doi.org/10.1109/14.236212]
[5]
Lu CJ, Meeker WQ. Using degradation measures to estimate a time to failure distribution. Technometric 1993; 35(2): 161-7.
[http://dx.doi.org/10.1080/00401706.1993.10485038]
[http://dx.doi.org/10.1080/00401706.1993.10485038]
[6]
Lawless J, Crowder M. Covariates and random effects in a gamma process model with application to degradation and failure. Lifetime Data Anal 2004; 10(3): 213-27.
[http://dx.doi.org/10.1023/B:LIDA.0000036389.14073.dd] [PMID: 15456104]
[http://dx.doi.org/10.1023/B:LIDA.0000036389.14073.dd] [PMID: 15456104]
[7]
Li Q. Research on accelerated life test of electrical connectors under environment multiple stresses. Hangzhou: Zhejiang University 2004.
[8]
Yao J, Cao X, Jiang T. Quantitative assessment approach of RET based on interference model. J Beijing Univ Aero Astro 2006; 32(1): 117-20.
[9]
Jia Z, Cai J, Liang Y, Han C. Reliability assessment technology for electronic equipment based on step-up-stress accelerated degradation testing. Syst Eng Theor Prac 2010; 30(07): 1279-85.
[10]
Pan Z, Balakrishnan N, Sun Q. Bivariate constant-stress accelerated degradation model and inference. Commun Stat Simul Comput 2011; 40(2): 247-57.
[http://dx.doi.org/10.1080/03610918.2010.534227]
[http://dx.doi.org/10.1080/03610918.2010.534227]
[11]
Pan Z, Balakrishnan N. Reliability modeling of degradation of products with multiple performance characteristics based on Gamma pro-cesses. Reliab Eng Syst Saf 2011; 96(8): 949-57.
[12]
Kalbfleisch JD, Prentice RL. The statistical analysis of failure time data. Hoboken: John Wiley & Sons 2002.
[http://dx.doi.org/10.1002/9781118032985]
[http://dx.doi.org/10.1002/9781118032985]
[14]
You Q, Zhao Y, Hu G, Wu L. Reliability assessment using accelerated degradation data based on time series model. Syst Eng Theor Prac 2011; 31(02): 328-32.
[15]
Yang YF, Zheng J, Di CC, et al. Reliability enhancement test of shock abrasion based on virtual testing. J Vibrat Shock 2013; 32(22): 32-5.
[16]
Cai ZY, Chen YX, Xiang H, et al. Reliability assessment method with integrated prior accelerated degradation and field degradation data. J Syst Eng Electron 2016; 38(04): 970-6.
[17]
Teng F, Wang H, Chen Y, et al. Statistical analysis method for accelerated degradation data of accelerometers. J Chinese Inertial Technol 2017; 25(02): 275-80.
[18]
Ismail AA. Estimating the parameters of Weibull distribution and the acceleration factor from hybrid partially accelerated life test. Appl Math Model 2012; 36(7): 2920-5.
[http://dx.doi.org/10.1016/j.apm.2011.09.083]
[http://dx.doi.org/10.1016/j.apm.2011.09.083]
[19]
Dong J, Chen J, Hu Y, et al. Accelerated degradation test failure mechanism of accelerated degradation test based on inverse Gaussian process. Struc Environ Eng 2019; 46(05): 23-9.
[20]
Saxena S, Xing Y, Kwon D, Pecht M. Accelerated degradation model for C-rate loading of lithium-ion batteries. Int J Electr Power Energy Syst 2019; 107: 438-45.
[http://dx.doi.org/10.1016/j.ijepes.2018.12.016]
[http://dx.doi.org/10.1016/j.ijepes.2018.12.016]
[21]
Sun B, Fan X, Qian C, et al. PoF-simulation-assisted reliability prediction for electrolytic capacitor in LED drivers. IEEE Trans Ind Electron 2016; 63(11): 6726-35.
[http://dx.doi.org/10.1109/TIE.2016.2581156]
[http://dx.doi.org/10.1109/TIE.2016.2581156]
[22]
Wang L, Pan R, Li X, et al. A Bayesian reliability evaluation method with integrated accelerated degradation testing and field information. Reliab Eng Syst Saf 2013; 112: 38-47.
[http://dx.doi.org/10.1016/j.ress.2012.09.015]
[http://dx.doi.org/10.1016/j.ress.2012.09.015]
[23]
Woo SW, Neal D. Reliability design of mechanical systems subject to repetitive stresses. Recent Pat Mech Eng 2015; 8(3): 222-34.
[http://dx.doi.org/10.2174/2212797608666150813001703]
[http://dx.doi.org/10.2174/2212797608666150813001703]
[24]
Wang H. Accelerated degradation data modeling and statistical analysis methods and engineering applications. Beijing: Science Press 2019.
[25]
Wang H, Teng K. Review of reliability evaluation technology based on accelerated degradation data. J Syst Eng Electron 2017; 39(12): 2877-85.
[26]
Tian W, Chao Q, Chen Z. Failure mechanisms and reliability analysis of RF MEMS switches. Recent Pat Mech Eng 2015; 8(3): 201-10.
[http://dx.doi.org/10.2174/2212797608666151006010538]
[http://dx.doi.org/10.2174/2212797608666151006010538]
[27]
Schaeffer LL, Muller I. Corrosion behaviour and biocompatibility of titanium screws produced by Powder Injection Moulding (PIM) for temporary applications. Recent Pat Mech Eng 2011; 4(1): 47-54.
[http://dx.doi.org/10.2174/2212797611104010047]
[http://dx.doi.org/10.2174/2212797611104010047]
[28]
Li Z, Pu P. Research progress of the sponge city in English literature: A scientific knowledge mapping based on CiteSpace and VOSviewer. Modern Urban Res 2016; (07): 12-8.
[29]
Fu J, Ding J. Comparison of visualization principles between Citespace and VOSviewer. Agri Libr Inform 2019; 31(10): 31-7.
[30]
Chen C. CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature. J Am Soc Inf Sci Technol 2006; 57(3): 359-77.
[http://dx.doi.org/10.1002/asi.20317]
[http://dx.doi.org/10.1002/asi.20317]
[31]
Li J, Chen C. Citespace: Text mining and visualization in scientific literature. Beijing: Capital University of Economics and Business Press 2016.
[32]
Han Z, Li B, Zhang K, et al. Knowledge structure of china’s marine economy research: An analysis based on CiteSpace Map. Dili Kexue 2016; 36(5): 643-52.
[33]
Wang P, Wang Q, An P, et al. Bibliometric analysis on international studies of environmental migration. World Regional Stud 2016; 25(3): 162-9.
[34]
Yan Z, Du D, Liu C, et al. Visualization analysis of mapping knowledge domain on Western geography of innovation. Acta Geogr Sin 2018; 73(2): 362-79.
[35]
Chen Y, Chen Y, Pei Z, et al. Digital twin: Recent development and future trend from bibliometrics perspective. Zhongguo Jixie Gongcheng 2020; 31(07): 797-807.
[36]
Yin X, Zhang G, Li X. A research situation analysis of information sciences based on keywords statistics. J Intell 2019; 28(11): 1-4.
[37]
Song X, Chi P. Comparative study of the data analysis results by Vosviewer and Citespace. Inf Sci 2016; (34): 108-12.
[38]
Gao K. Research on the application of bibliometric analysis software VOSviewer. Sci-Tech Inform Develop Econ 2015; 25(12): 95-8.
[39]
Meneghesso G, Meneghini M, Tazzoli A, et al. Reliability issues of gallium nitride high electron mobility transistors. Int J Microw Wirel Technol 2010; 2(1): 39.
[http://dx.doi.org/10.1017/S1759078710000097]
[http://dx.doi.org/10.1017/S1759078710000097]
[40]
Tan CM, Singh P. Time evolution degradation physics in high power white LEDs under high temperature-humidity conditions. IEEE Trans Device Mater Reliab 2014; 14(2): 742-50.
[http://dx.doi.org/10.1109/TDMR.2014.2318725]
[http://dx.doi.org/10.1109/TDMR.2014.2318725]
[41]
Hernández-López AM, Aguilar-Garib JA, Guillemet-Fritsch S, et al. Reliability of X7R multilayer ceramic capacitors during high accelerat-ed life testing (HALT). Materials (Basel) 2018; 11(10): 1900.
[http://dx.doi.org/10.3390/ma11101900] [PMID: 30287768]
[http://dx.doi.org/10.3390/ma11101900] [PMID: 30287768]
[42]
Ndiaye A, Charki A, Kobi A, Kébé CMF, Ndiaye PA, Sambou V. Degradations of silicon photovoltaic modules: A literature review. Sol Energy 2013; 96: 140-51.
[http://dx.doi.org/10.1016/j.solener.2013.07.005]
[http://dx.doi.org/10.1016/j.solener.2013.07.005]
[43]
Gebraeel NZ, Lawley MA, Rong LI, et al. Residual-life distributions from component degradation signals: A Bayesian approach. IIE Trans 2005; 37(6): 543-57.
[http://dx.doi.org/10.1080/07408170590929018]
[http://dx.doi.org/10.1080/07408170590929018]
[44]
Hu CH, Lee MY, Tang J, et al. Optimum step-stress accelerated degradation test for Wiener degradation process under constraints. Eur J Oper Res 2015; 241(2): 412-21.
[http://dx.doi.org/10.1016/j.ejor.2014.09.003]
[http://dx.doi.org/10.1016/j.ejor.2014.09.003]
[45]
Liu X, Tang LC. A Bayesian optimal design for accelerated degradation tests. Quality Relia Eng 2010; 26(8): 863-75.
[http://dx.doi.org/10.1002/qre.1151]
[http://dx.doi.org/10.1002/qre.1151]
[46]
Duan M, Zhang JF, Ji Z, et al. New insights into defect loss, slowdown, and device lifetime enhancement. IEEE Trans Electron Dev 2013; 60(1): 413-9.
[http://dx.doi.org/10.1109/TED.2012.2223702]
[http://dx.doi.org/10.1109/TED.2012.2223702]
[47]
Strus MC, Chiaramonti AN, Kim YL, Jung YJ, Keller RR. Accelerated reliability testing of highly aligned single-walled carbon nanotube networks subjected to DC electrical stressing. Nanotechnology 2011; 22(26)265713
[http://dx.doi.org/10.1088/0957-4484/22/26/265713] [PMID: 21586818]
[http://dx.doi.org/10.1088/0957-4484/22/26/265713] [PMID: 21586818]
[48]
Silfvenius C, Sun Y, Blixt P, et al. Nitride facet passivation raises reliability, COMD, and enables high-temperature operation of InGaAsP, InGaAs, and InAlGaAs lasers. Proc SPIE 2005; 189-200.
[http://dx.doi.org/10.1117/12.590358]
[http://dx.doi.org/10.1117/12.590358]
[49]
Medjaher K, Tobonmejia DA, Zerhouni N, et al. Remaining useful life estimation of critical components with application to bearings. IEEE Trans Reliab 2012; 61(2): 292-302.
[http://dx.doi.org/10.1109/TR.2012.2194175]
[http://dx.doi.org/10.1109/TR.2012.2194175]
[50]
Li X. Summary of the research on the Lotka law in China in recent years. Sci/Tech Inform. Develop Econ 2005; 15(13): 27-8.
[51]
Lim H, Yum B. Optimal design of accelerated degradation tests based on Wiener process models. J Appl Stat 2011; 38(2): 309-25.
[http://dx.doi.org/10.1080/02664760903406488]
[http://dx.doi.org/10.1080/02664760903406488]
[52]
Ye Z, Wang Y, Tsui K, et al. Degradation data analysis using Wiener processes with measurement errors. IEEE Trans Reliab 2013; 62(4): 772-80.
[http://dx.doi.org/10.1109/TR.2013.2284733]
[http://dx.doi.org/10.1109/TR.2013.2284733]
[53]
Wang X. Wiener processes with random effects for degradation data. J Multivariate Anal 2010; 101(2): 340-51.
[http://dx.doi.org/10.1016/j.jmva.2008.12.007]
[http://dx.doi.org/10.1016/j.jmva.2008.12.007]
[54]
Tseng S, Balakrishnan N, Tsai C, et al. Optimal step-stress accelerated degradation test plan for Gamma degradation processes. IEEE Trans Reliab 2009; 58(4): 611-8.
[http://dx.doi.org/10.1109/TR.2009.2033734]
[http://dx.doi.org/10.1109/TR.2009.2033734]
[55]
Ye Z, Chen L, Tang LC, et al. Accelerated degradation test planning using the inverse Gaussian process. IEEE Trans Reliab 2014; 63(3): 750-63.
[http://dx.doi.org/10.1109/TR.2014.2315773]
[http://dx.doi.org/10.1109/TR.2014.2315773]
[56]
Ye Z, Chen N. The inverse Gaussian process as a degradation model. Technometrics 2014; 56(3): 302-11.
[http://dx.doi.org/10.1080/00401706.2013.830074]
[http://dx.doi.org/10.1080/00401706.2013.830074]
[57]
Bryant MD, Khonsari MM, Ling FF, et al. On the thermodynamics of degradation. Proc- Royal Soc, Math Phys Eng Sci 2008; 464(2096): 2001-14.
[http://dx.doi.org/10.1098/rspa.2007.0371]
[http://dx.doi.org/10.1098/rspa.2007.0371]
[58]
Shen Z, He Z, Chen X, Sun C, Liu Z. A monotonic degradation assessment index of rolling bearings using fuzzy support vector data de-scription and running time. Sensors (Basel) 2012; 12(8): 10109-35.
[http://dx.doi.org/10.3390/s120810109] [PMID: 23112591]
[http://dx.doi.org/10.3390/s120810109] [PMID: 23112591]
[59]
Pedersen KB, Pedersen KM. Dynamic modeling method of electro-thermo-mechanical degradation in IGBT modules. IEEE Trans Power Electron 2016; 31(2): 975-86.
[http://dx.doi.org/10.1109/TPEL.2015.2426013]
[http://dx.doi.org/10.1109/TPEL.2015.2426013]
[60]
Duan R, Zhou J, Liu J, Xu Y. A performance degradation prediction approach for turbo-generator bearing considering complex working conditions based on clustering indicator and self-optimized deep learning model. Meas Sci Technol 2021; 32(6)
[61]
Paulina A, Maria AP, Alexander P. Degradation of glass fiber reinforced polymer (GFRP) bars in concrete environment. Constr Build Mater 2021; 293123451
[62]
Koo YD, Na MG. Collapse moment estimation for wall-thinned pipe bends and elbows using deep fuzzy neural networks. Nucl Eng Technol 2020; 52(11): 2678-85.
[http://dx.doi.org/10.1016/j.net.2020.05.006]
[http://dx.doi.org/10.1016/j.net.2020.05.006]
[63]
Wen C, Xie B, Song Z, et al. Methodology for designing tractor accelerated structure tests for an indoor drum-type test bench. Biosyst Eng 2021; 205: 1-26.
[http://dx.doi.org/10.1016/j.biosystemseng.2021.02.007]
[http://dx.doi.org/10.1016/j.biosystemseng.2021.02.007]
[65]
Bergera C, Eulitz KG, Heuler P, et al. Betriebsfestigkeit in Germany-an overview. Int J Fatigue 2002; 24(6): 603-25.
[http://dx.doi.org/10.1016/S0142-1123(01)00180-3]
[http://dx.doi.org/10.1016/S0142-1123(01)00180-3]
[66]
Tian K-W, Zhang Y-T. Effect of ambient temperature on the formation mechanism of PTFE liner transfer film of spherical plain bearings. Mech Ind 2021; 22: 11.
[http://dx.doi.org/10.1051/meca/2021007]
[http://dx.doi.org/10.1051/meca/2021007]
[67]
Lin L. Aging life evaluation of coal mining flexible EPR cables under multi-stresses IEEE Access 2020; 8: 53539-46.
[http://dx.doi.org/10.1109/ACCESS.2020.2981359]
[http://dx.doi.org/10.1109/ACCESS.2020.2981359]
[68]
Afshar A, Mihut D, Chen P. Effects of environmental exposures on carbon fiber epoxy composites protected by metallic thin films. J Compos Mater 2019; 54(2): 167-77.
[69]
Lu Y. Aluminum carbide hydrolysis induced degradation of thermal conductivity and tensile strength in diamond/aluminum composite. J Compos Mater 2018; 52(20): 2709-17.
[http://dx.doi.org/10.1177/0021998317752504]
[http://dx.doi.org/10.1177/0021998317752504]
[70]
Liu X, Qu Y, Yang X, et al. Load spectrum compiling and fatigue life estimation of the automobile wheel hub. Recent Pat Mech Eng 2021; 14(3): 366-79.
[http://dx.doi.org/10.2174/2212797613999201231200939]
[http://dx.doi.org/10.2174/2212797613999201231200939]
[71]
Wang J. Vibration-induced acceleration of infiltration in loess. Sci China Earth Sci 2021; 64(4): 611-30.
[http://dx.doi.org/10.1007/s11430-020-9741-x]
[http://dx.doi.org/10.1007/s11430-020-9741-x]
[72]
Alía C. Mechanical behaviour of vinylester adhesive joints used in laminated material for steel structures. Mar Structures 2020; 69102687
[73]
Grogan DM. Influence of microstructural defects and hydrostatic pressure on water absorption in composite materials for tidal energy. J Compos Mater 2018; 52(21): 2899-917.
[http://dx.doi.org/10.1177/0021998318755428]
[http://dx.doi.org/10.1177/0021998318755428]
[74]
Zhang Z. Life prediction for anticorrosive coatings on steel bridges. Corrosion 2020; 76(8): 773-85.
[http://dx.doi.org/10.5006/3504]
[http://dx.doi.org/10.5006/3504]
[75]
Selvaraj K, Sivanandam K. Influence of controlled permeable formwork liner on the service life of reinforced concrete. J Mater Civ Eng 2021; 33(6)04021103
[http://dx.doi.org/10.1061/(ASCE)MT.1943-5533.0003716]
[http://dx.doi.org/10.1061/(ASCE)MT.1943-5533.0003716]
[76]
Bagale N, Bhat MR. Evaluation of hygrothermal ageing in CFRP composite material using a non-destructive approach. J Compos Mater 2020; 55(10): 1309-14.
[77]
Galio AF, Muller IL. Active coatings: Examples and applications. Recent Pat Mech Eng 2008; 1(1): 68-71.
[http://dx.doi.org/10.2174/2212797610801010068]
[http://dx.doi.org/10.2174/2212797610801010068]
[78]
Chowdhury MA, Nuruzzaman DM, Rahaman ML. Erosive wear behavior of composite and polymer materials-a review. Recent Pat Mech Eng 2009; 2(2): 144-53.
[http://dx.doi.org/10.2174/2212797610902020144]
[http://dx.doi.org/10.2174/2212797610902020144]
[79]
He D, Liu L, Cao M. A doubly accelerated degradation model based on the inverse Gaussian process and its objective Bayesian analysis. J Stat Comput Simul 2020; 91(8): 1485-503.
[http://dx.doi.org/10.1080/00949655.2020.1858083]
[http://dx.doi.org/10.1080/00949655.2020.1858083]
[80]
Zhao X, Chen P, Gaudoin O, et al. Accelerated degradation tests with inspection effects. Eur J Oper Res 2021; 292(3): 1099-114.
[http://dx.doi.org/10.1016/j.ejor.2020.11.041]
[http://dx.doi.org/10.1016/j.ejor.2020.11.041]
[81]
Koshiji H, Ohkubo T, Azato K, et al. Selective laser thermoregulation system for accelerated Deg-radation Test of SiC/SiC CMCs. J Laser Micro Nanoeng 2020; 15(3): 174-7.
[82]
Lee CY, Chen CH, Jung GB, Li SC, Zeng YZ. Internal microscopic diagnosis of accelerated aging of proton exchange membrane water electrolysis cell stack. Micromachines (Basel) 2020; 11(12)E1078
[http://dx.doi.org/10.3390/mi11121078] [PMID: 33291618]
[http://dx.doi.org/10.3390/mi11121078] [PMID: 33291618]
[83]
Khera N, Khan SA. Prognostics of power MOSFET using artificial neural network approach. J Electr Eng Technol 2019; 15(1): 487-99.
[http://dx.doi.org/10.1007/s42835-019-00272-0]
[http://dx.doi.org/10.1007/s42835-019-00272-0]
[84]
Chan HA. Environmental Stress Testing. ATT Tech J 1994; 73(2): 77-85.
[http://dx.doi.org/10.1002/j.1538-7305.1994.tb00581.x]
[http://dx.doi.org/10.1002/j.1538-7305.1994.tb00581.x]
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