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Failure Rate Function (failure + rate_function)

Distribution by Scientific Domains
Mathematics and Statistics75%

Selected Abstracts

Optimal burn-in procedure for periodically inspected systems

NAVAL RESEARCH LOGISTICS: AN INTERNATIONAL JOURNAL, Issue 7 2007
Ji Hwan Cha
Abstract Burn-in is a widely used method to improve the quality of products or systems after they have been produced. In this paper, we study burn-in procedure for a system that is maintained under periodic inspection and perfect repair policy. Assuming that the underlying lifetime distribution of a system has an initially decreasing and/or eventually increasing failure rate function, we derive upper and lower bounds for the optimal burn-in time, which maximizes the system availability. Furthermore, adopting an age replacement policy, we derive upper and lower bounds for the optimal age parameter of the replacement policy for each fixed burn-in time and a uniform upper bound for the optimal burn-in time given the age replacement policy. These results can be used to reduce the numerical work for determining both optimal burn-in time and optimal replacement policy. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007 [source]

Bounding the optimal burn-in time for a system with two types of failure

NAVAL RESEARCH LOGISTICS: AN INTERNATIONAL JOURNAL, Issue 8 2004
Ji Hwan Cha
Abstract Burn-in is a widely used method to improve the quality of products or systems after they have been produced. In this paper, we consider the problem of determining bounds to the optimal burn-in time and optimal replacement policy maximizing the steady state availability of a repairable system. It is assumed that two types of system failures may occur: One is Type I failure (minor failure), which can be removed by a minimal repair, and the other is Type II failure (catastrophic failure), which can be removed only by a complete repair. Assuming that the underlying lifetime distribution of the system has a bathtub-shaped failure rate function, upper and lower bounds for the optimal burn-in time are provided. Furthermore, some other applications of optimal burn-in are also considered. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004 [source]

Maintenance contract assessment for aging systems

QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, Issue 5 2008
Anatoly Lisnianski
Abstract This paper considers an aging system, where the system failure rate is known to be an increasing function. After any failure, maintenance is performed by an external repair team. Repair rate and cost of repair are determined by a corresponding maintenance contract with a repair team. There are many different maintenance contracts suggested by the service market to the system owner. In order to choose the best maintenance contract, a total expected cost during a specified time horizon should be evaluated for an aging system. In this paper, a method is suggested based on a piecewise constant approximation for the increasing failure rate function. Two different approximations are used. For both types of approximations, the general approach for building the Markov reward model is suggested in order to assess lower and upper bounds of the total expected cost. Failure and repair rates define the transition matrix of the corresponding Markov process. Operation cost, repair cost and penalty cost for system failures are taken into account by the corresponding reward matrix definition. A numerical example is presented in order to illustrate the approach. Copyright © 2008 John Wiley & Sons, Ltd. [source]

Optimal corrective maintenance contract planning for aging multi-state system

APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY, Issue 5 2009
Yi Ding
Abstract This paper considers an aging multi-state system, where the system failure rate varies with time. After any failure, maintenance is performed by an external repair team. Repair rate and cost of each repair are determined by a corresponding corrective maintenance contract with a repair team. The service market can provide different kinds of maintenance contracts to the system owner, which also can be changed after each specified time period. The owner of the system would like to determine a series of repair contracts during the system life cycle in order to minimize the total expected cost while satisfying the system availability. Operating cost, repair cost and penalty cost for system failures should be taken into account. The paper proposes a method for determining such optimal series of maintenance contracts. The method is based on the piecewise constant approximation for an increasing failure rate function in order to assess lower and upper bounds of the total expected cost and system availability by using Markov models. The genetic algorithm is used as the optimization technique. Numerical example is presented to illustrate the approach. Copyright © 2009 John Wiley & Sons, Ltd. [source]