Assessment of Accrued Damage and Remaining Useful Life in Leadfree Electronics Subjected to Multiple Thermal Environments of Thermal Aging and Thermal Cycling

Author(s):  
Pradeep Lall ◽  
Rahul Vaidya ◽  
Vikrant More ◽  
Kai Goebel
Author(s):  
Pradeep Lall ◽  
Mahendra Harsha ◽  
Jeff Suhling ◽  
Kai Goebel ◽  
Jim Jones

Field deployed electronics may accrue damage due to environmental exposure and usage after finite period of service but may not often have any macro-indicators of failure such as cracks or delamination. A method to interrogate the damage state of field deployed electronics in the pre-failure space may allow insight into the damage initiation, progression, and remaining useful life of the deployed system. Aging has been previously shown to effect the reliability and constitutive behavior of second-level leadfree interconnects. Prognostication of accrued damage and assessment of residual life can provide valuable insight into impending failure. In this paper, field deployed parts have been extracted and prognosticated for accrued damage and remaining useful life in an anticipated future deployment environment. A subset of the field deployed parts have been tested to failure in the anticipated field deployed environment to validate the assessment of remaining useful life. In addition, some parts have been subjected to additional know thermo-mechanical stresses and the incremental damage accrued validated with respect to the amount of additional damage imposed on the assemblies. The presented methodology uses leading indicators of failure based on micro-structural evolution of damage to identify accrued damage in electronic systems subjected to sequential stresses of thermal aging and thermal cycling. Damage equivalency methodologies have been developed to map damage accrued in thermal aging to the reduction in thermo-mechanical cyclic life based on damage proxies. The expected error with interrogation of system state and assessment of residual life has been quantified. Prognostic metrics including α-λ metric, sample standard deviation, mean square error, mean absolute percentage error, average bias, relative accuracy, and cumulative relative accuracy have been used to compare the performance of the damage proxies.


Author(s):  
Pradeep Lall ◽  
Shantanu Deshpande

Wire bonding is predominant mode of interconnect in electronics packaging. Traditionally material used for wire bonding is gold. But industry is slowly replacing gold wire bond by copper-aluminum wire bond because of the lower cost and better mechanical properties than gold, such as high strength, high thermal conductivity etc. Numerous studies have been done to analyze failure mechanism of Cu-Al wire bonds. Cu-Al interface is a predominant location for failure of the wirebond interconnects. In this paper, the use of intermetallic thickness as leading indicator-of-failure for prognostication of remaining useful life for Cu-Al wire bond interconnects has been studied. For analysis, 32 pin chip scale packages were used. Packages were aged isothermally at 200°C and 250°C for 10 days. Packages were withdrawn periodically after 24 hours and its IMC thickness was measured using SEM. The parts have been prognosticated for accrued damage and remaining useful life in current or anticipated future deployment environment. The presented methodology uses evolution of the IMC thickness in conjunction with the Levenberg-Marquardt Algorithm to identify accrued damage in wire bond subjected to thermal aging. The proposed method can be used for equivalency of damage accrued in Cu-Al parts subjected to multiple thermal aging environments.


2005 ◽  
Vol 48 (2) ◽  
pp. 208-217 ◽  
Author(s):  
Matthew Watson ◽  
Carl Byington ◽  
Douglas Edwards ◽  
Sanket Amin

2020 ◽  
Vol 14 ◽  
Author(s):  
Dangbo Du ◽  
Jianxun Zhang ◽  
Xiaosheng Si ◽  
Changhua Hu

Background: Remaining useful life (RUL) estimation is the central mission to the complex systems’ prognostics and health management. During last decades, numbers of developments and applications of the RUL estimation have proliferated. Objective: As one of the most popular approaches, stochastic process-based approach has been widely used for characterizing the degradation trajectories and estimating RULs. This paper aimed at reviewing the latest methods and patents on this topic. Methods: The review is concentrated on four common stochastic processes for degradation modelling and RUL estimation, i.e., Gamma process, Wiener process, inverse Gaussian process and Markov chain. Results: After a briefly review of these four models, we pointed out the pros and cons of them, as well as the improvement direction of each method. Conclusion: For better implementation, the applications of these four approaches on maintenance and decision-making are systematically introduced. Finally, the possible future trends are concluded tentatively.


Author(s):  
Renxiong Liu

Objective: Lithium-ion batteries are important components used in electric automobiles (EVs), fuel cell EVs and other hybrid EVs. Therefore, it is greatly important to discover its remaining useful life (RUL). Methods: In this paper, a battery RUL prediction approach using multiple kernel extreme learning machine (MKELM) is presented. The MKELM’s kernel keeps diversified by consisting multiple kernel functions including Gaussian kernel function, Polynomial kernel function and Sigmoid kernel function, and every kernel function’s weight and parameter are optimized through differential evolution (DE) algorithm. Results : Battery capacity data measured from NASA Ames Prognostics Center are used to demonstrate the prediction procedure of the proposed approach, and the MKELM is compared with other commonly used prediction methods in terms of absolute error, relative accuracy and mean square error. Conclusion: The prediction results prove that the MKELM approach can accurately predict the battery RUL. Furthermore, a compare experiment is executed to validate that the MKELM method is better than other prediction methods in terms of prediction accuracy.


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