Systems and methods for failure prediction and maintenance planning are provided. A system for failure prediction and maintenance planning, comprises a statistical modeling module comprising a periodic impact evaluation module capable of identifying periodic effects on the failure risk, a balance equation systems module capable of constructing balance equations with respect to phases of failure times, and an initial phase estimation module capable of estimating an unknown initial phase, wherein one or more of the modules are implemented on a computer system comprising a memory and at least one processor coupled to the memory.

System and method for maintenance planning and failure prediction for equipment subject to periodic failure risk

A two-segment distribution is proposed for representation of the fatigue life of modern high-performance composite materials. Each segment is a two-parameter Weibull distribution. Equations of the maximum likelihood method in estimating parameters are derived, and an iterative solution scheme is presented. Several example problems are included.

Maximum Likelihood Estimation of a Two-Segment Weibull Distribution for Fatigue Life

: Static strength and fatigue life of unidirectional graphite/epoxy composites are studied in terms of statistical models of fatigue degradation and residual strength. A two-segment Weibull distribution for fatigue life, and a cumulative damage rule for fatigue are introduced. Experimental tests performed support the assumption that a specimen's rank in strength is equal to its rank in fatigue life. Fatigue weakens the matrix, and thus degrades the residual compression strength, and not the residual tension strength in early life. In some cases, residual tension strength initially increases. Proof tests can guarantee a minimum strength, and to a lesser extent, a minimum fatigue life. (Author)

Statistical Analysis of Strength and Life of Composite Materials.

This paper considers two life testing procedures (progressively censored samples and Bartholomew's experiment) under the assumption that the life of an item follows the exponential distribution. The failure rates are different under n different conditions of usage of the item at regular intervals of time. The maximum likelihood estimates of the n failure rates have been derived along with their asymptotic variances for both types of data (when failure times are recorded and when only the number of items failing in each interval are recorded). A numerical example illustrates the type of data and relevant calculations for the experiment involving progressively censored samples.

Estimation of Periodically Changing Failure Rate

Two life testing procedures, namely, the progressively censored samples and Bartholomew's experiment are discussed under the assumption that the life of an item follows a specialized Weibull distribution. The scale parameter is different under two different conditions of usage of the item at regular intervals of time, the shape parameter remains unchanged throughout the experiment. The maximum likelihood estimates of the two scale parameters have been derived along with their variances. A numerical example illustrates the type of data and relevant calculations for the experiment involving progressively censored samples.

Life Tests with Periodic Change in the Scale Parameter of a Weibull Distribution

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Life Tests with Periodic Change in the Scale Parameter of a Weibull Distribution