An Extreme-Value Event Approach for Frequency-Domain Performance Reliability

With time and usage, systems become less reliable as performance measures continuously degrade. In frequency-domain design, a sufficiently large number of performance measures are selected at discrete frequencies to act as surrogates for the frequency bands. Over discretized life-time, the system failure event grows into an ever larger number of highly correlated elementary failure events in terms of both frequency and time. This paper replaces the complex system failure event with an equivalent minimum extreme-value event: it is shown that this single event retains all of the original correlation information and is invariant to the number of elemental events. The novelty of the new and elegant approach is that it standardizes the failure probability evaluation via one-dimensional pdfs at either selected times, or importantly, selected frequencies. Further, pdfs of the frequencies causing failure over life-time are shown to be a useful design tool. The pdfs are easily represented by sampling techniques. Error analysis identifies three errors and the paper gives strategies to control. Case studies of an analogue filter show the proposed methodology has engineering applications. The impact of the proposed methodology is two-fold: it presents a standard way to assess and manage the uncertainty in the degradation process, and it provides a launching platform for timely design optimization.

[1]  Muhammad Ashraful Alam,et al.  Reliability- and Process-variation aware design of integrated circuits — A broader perspective , 2008, 2011 International Reliability Physics Symposium.

[2]  Jeremy E. Oakley,et al.  Probabilistic uncertainty analysis of an FRF of a structure using a Gaussian process emulator , 2011 .

[3]  K. Antreich,et al.  Design centering by yield prediction , 1982 .

[4]  Jianbing Chen,et al.  Advances of the probability density evolution method for nonlinear stochastic systems , 2012 .

[5]  Bruno Sudret,et al.  The PHI2 method: a way to compute time-variant reliability , 2004, Reliab. Eng. Syst. Saf..

[6]  Kailash C. Kapur,et al.  Issues in modeling system reliability from customer's perspective , 1998, SMC'98 Conference Proceedings. 1998 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.98CH36218).

[7]  G. Schuëller,et al.  Chair of Engineering Mechanics Ifm-publication 2-374 a Critical Appraisal of Reliability Estimation Procedures for High Dimensions , 2022 .

[8]  Gordon J. Savage,et al.  Set theoretic formulation of performance reliability of multiple response time‐variant systems due to degradations in system components , 2007, Qual. Reliab. Eng. Int..

[9]  William J. Kolarik,et al.  Multivariate performance reliability prediction in real-time , 2001, Reliab. Eng. Syst. Saf..

[10]  W. Nelson Statistical Methods for Reliability Data , 1998 .

[11]  R. Yam,et al.  Approaches for reliability modeling of continuous-state devices , 1999 .

[12]  William Q. Meeker,et al.  A Review of Accelerated Test Models , 2006, 0708.0369.

[13]  Mahesh D. Pandey,et al.  An efficient method for system reliability analysis of planar mechanisms , 2013 .

[14]  Jianbing Chen,et al.  Probability density evolution analysis of engineering structures via cubature points , 2012 .

[15]  Jianbing Chen,et al.  The equivalent extreme-value event and evaluation of the structural system reliability , 2007 .

[16]  Xin Pan,et al.  Reliability optimization of analog integrated circuits considering the trade-off between lifetime and area , 2012, Microelectron. Reliab..

[17]  Pingfeng Wang,et al.  A Nested Extreme Response Surface Approach for Time-Dependent Reliability-Based Design Optimization , 2012 .

[18]  Hong-Zhong Huang,et al.  An Approach to Reliability Assessment Under Degradation and Shock Process , 2011, IEEE Transactions on Reliability.

[19]  N. Sinnadurai,et al.  The Aging Behavior of Commercial Thick-Film Resistors , 1982 .

[20]  Robert Spence,et al.  Tolerance Design of Electronic Circuits , 1997 .

[21]  Georges G. E. Gielen,et al.  Variability-aware reliability simulation of mixed-signal ICs with quasi-linear complexity , 2010, 2010 Design, Automation & Test in Europe Conference & Exhibition (DATE 2010).

[22]  Gordon Johnston,et al.  Statistical Models and Methods for Lifetime Data , 2003, Technometrics.

[23]  K. Singhal,et al.  Statistical design centering and tolerancing using parametric sampling , 1981 .

[24]  John W. Bandler,et al.  Automated network design with optimal tolerances , 1974 .

[25]  J. Bert Keats,et al.  Statistical Methods for Reliability Data , 1999 .

[26]  Gordon J. Savage,et al.  Interrelating Quality and Reliability in Engineering Systems , 2002 .

[27]  M. Pandey,et al.  System reliability analysis of the robotic manipulator with random joint clearances , 2012 .

[28]  J. L. Bogdanoff,et al.  Application of Physical Laws to Parameter Estimation for Probabilistic Models of Cumulative Damage , 1990 .

[29]  Gordon J. Savage,et al.  A New Sample-Based Approach to Predict System Performance Reliability , 2008, IEEE Transactions on Reliability.

[30]  Hoang Pham,et al.  Reliability modeling of multi-state degraded systems with multi-competing failures and random shocks , 2005, IEEE Trans. Reliab..

[31]  A.C. Brombacher,et al.  A method for reliability optimization through degradation analysis and robust design , 2003, Annual Reliability and Maintainability Symposium, 2003..

[32]  C. Fornell,et al.  The American Customer Satisfaction Index: Nature, Purpose, and Findings , 1996 .

[33]  M. D. Pandey,et al.  The influence of temporal uncertainty of deterioration on life-cycle management of structures , 2009 .

[34]  V. Roshan Joseph,et al.  Reliability improvement experiments with degradation data , 2006, IEEE Transactions on Reliability.

[35]  William Q. Meeker,et al.  Reliability: The Other Dimension of Quality , 2004 .

[36]  Kai Yang,et al.  Continuous state reliability analysis , 1996, Proceedings of 1996 Annual Reliability and Maintainability Symposium.

[37]  G. Hulsken,et al.  Using dynamic reliability models to extend the economic life of strongly innovative products , 2004, IEEE International Symposium on Electronics and the Environment, 2004. Conference Record. 2004.

[38]  M. A. Styblinski Formulation of the drift reliability optimization problem , 1991 .

[39]  Wei Huang,et al.  An alternative degradation reliability modeling approach using maximum likelihood estimation , 2005, IEEE Transactions on Reliability.

[40]  W. J. Padgett,et al.  Accelerated Degradation Models for Failure Based on Geometric Brownian Motion and Gamma Processes , 2005, Lifetime data analysis.

[41]  J. F. Pinel,et al.  Tolerance assignment in linear networks using nonlinear programming , 1972 .

[42]  Zhen Hu,et al.  A Sampling Approach to Extreme Value Distribution for Time-Dependent Reliability Analysis , 2013 .

[43]  Min Huang,et al.  Drift reliability optimization in IC design: generalized formulation and practical examples , 1993, IEEE Trans. Comput. Aided Des. Integr. Circuits Syst..

[44]  Yaping Wang,et al.  Modeling the Dependent Competing Risks With Multiple Degradation Processes and Random Shock Using Time-Varying Copulas , 2012, IEEE Transactions on Reliability.