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Rotor-bearing systems play a vital role in machine tools, aero engines, and wind turbines. Generally, worn-induced degradation quantities and manufacturing errors of components are the main error sources that influence the precision reliability of rotor-bearing systems. The current precision reliability evaluation models are focusing on several error sources in only a few key components without agreeable results. Therefore, a precision reliability evaluation model is proposed considering all time-variant error sources and random error sources. Firstly, time-variant wear models for commonly occurred degradation types in a rotor-bearing system are developed. Secondly, the constructed time-variant wear models are inserted into the precision model with all moving components in the rotor-bearing system using meta-action structural decomposition method. Finally, the time-variant stochastic process discretization method is employed to establish the precision reliability evaluation model, and solve the precision reliability of the rotor-bearing systems. Case investigations are carried out to verify the performance of the present model, which provides a more accurate precision reliability evaluation model to estimate the conditions of rotor-bearing systems during the service period. [ABSTRACT FROM AUTHOR]

When a unit should provide reliability at mission time, the mission success probability or failure probability becomes an important constraint to plan inspection policies. From this viewpoint, this paper considers the optimization problems of periodic and sequential inspection policies with mission failure probabilities. In this paper, a mission time is considered as a renewal point for inspection polices, but the failure cost occurred at mission time is higher than the total cost of inspection and failure detection. We give an upper limit of the failure probability at mission time, that is, mission failure probability, to minimize the total expected costs and the expected cost rates of inspection policies. In addition, the extended models of inspection policies for an interval mission, possible random times, and operating interval are discussed. [ABSTRACT FROM AUTHOR]

This paper takes up the reliability and preventive replacement problems for a K -out-of- n system, where K is a stochastic parameter provided. Firstly, we consider the case when K is predefined as constant numbers as is done with the traditional method, and obtain the system reliability R ( t ), mean time to failure (MTTF), and replacement policies, in which the number n of units for replacement and replacement time T of operation are, respectively, optimized. Secondly, we focus on the above discussions again when K cannot be predefined constantly, but it is a random variable with an estimated probability function. Furthermore, we give approximate computations in an easier way for MTTF, optimal number n * and replacement time T *, respectively. [ABSTRACT FROM AUTHOR]

It has been assumed for a standby unit that periodic inspection is performed more easily to detect failures, but such a strict periodic mode would be impractical if the unit is executing some procedures without stops. From the above viewpoint, this paper first optimises a random inspection policy in accordance with random procedure times, compares it with periodic inspection and computes a modified checking cost for random inspection to determine the case where such a random inspection would be adopted. Second, this paper proposes three new inspection models in which inspections with deterministic policies are scheduled strategically while their performances need to be limited by completion times of operation procedures. These policies are called inspection first, inspection last and inspection overtime. The total expected inspection and downtime costs of each model until failure detection are obtained, and optimal policies which minimise them are derived analytically. Furthermore, the three inspection policies are compared with periodic inspection, inspection first and last are compared with each other, and a modified checking cost for inspection overtime is discussed when the policy would be better than periodic inspection. [ABSTRACT FROM AUTHOR]

Abstract: From the economical viewpoint of several combined PM policies in reliability theory, this paper takes up a standard cumulative damage model in which the notion of maintenance last is applied, i.e., the unit undergoes preventive maintenances before failure at a planned time T, at a damage level Z, or at a shock number N, whichever occurs last. Expected cost rates are detailedly formulated, and optimal problems of two alternative policies which combine time-based with condition-based preventive maintenances are discussed, i.e., optimal for N, for T, and for T are rigorously obtained. Comparison methods between such maintenance last and conventional maintenance first are explored. It is determined theoretically and numerically which policy should be adopted, according to the different methods in different cases when the time-based or the condition-based PM policy is optimized. [Copyright &y& Elsevier]

In some practical situations, it may be more economical to work a used system than do a new one. From this viewpoint, this article considers three basic preventive maintenance (PM) policies for a used system: the system with initial variable damage Y 0 begins to operate at time 0, and suffers damage due to shocks. It fails when the total damage exceeds a failure level K and corrective maintenance is made immediately. To prevent such failure, it undergoes PM at a planned time T, a shock number N and a damage level k, but maintenances are imperfect. However, failure rate of a used system maybe higher than that of a new one, so some maintenance is applied to the policies at each shock in the extended models. Using the theory of cumulative processes, expected cost rate models are obtained, optimal policies which minimise them are derived analytically and discussed numerically. [ABSTRACT FROM PUBLISHER]

This paper considers a parallel system with a random number of units according to a Poisson distribution. The fracture of an aircraft fuselage with multiple site damage serves as a real world application for this problem. The mean time to failure is obtained. Using this result, an optimal number of units and replacement time for the system which minimize the expected cost rates are derived analytically, and numerically, when the failure time has a Weibull distribution. It is of interest that these results also give good approximations to those of the system with a constant number of units. Further, similar discussions for a scheduling problem of a job with random working times are made, when a parallel system is provided. [ABSTRACT FROM AUTHOR]

It is well-known in the standard age replacement policy that a finite preventive replacement time does not exist when the failure time is exponential and the optimal preventive replacement time is nonrandom. It is shown that when the failure time is exponential, a finite time exists by introducing the shortage and excess costs. In addition, the random age replacement is proposed and similar discussions are made. Furthermore, the periodic and random inspection policies are taken up, and their optimal policies are shown to correspond theoretically to those of the age replacement ones. It is shown finally that when the random inspection cost is the half of the periodic one, two expected costs are almost the same. [ABSTRACT FROM AUTHOR]

Effective maintenance policies can improve the production system performance by alleviating product quality degradation and increasing system reliability and availability. However, reliability, product quality degradation, and availability are conflicting optimization objectives and are rarely considered together in maintenance policy optimization. Aiming at optimizing these three objectives simultaneously, this paper proposes a joint model for opportunistic maintenance (OM), and product quality and availability improvement of a series multi-machine production system (MMPS). First, a condition index (CI) is developed to characterize the condition of individual machines based on monitoring data, and the corresponding threshold functions are developed to realize maintenance decision-making for individual machines. Then, considering maintenance dependence in the MMPS, based on the CI, the dual dynamic threshold functions are introduced: the preventive maintenance (PM) and the OM threshold functions, and a novel dual-dynamic-thresholds-based OM policy is developed. Whenever the CI of a machine reaches its PM threshold, all the other machines whose CI reaches the OM zone will be maintained together with this machine. Finally, a case study and comparisons are performed to show that the proposed model can simultaneously provide good production economic performance, high quality, and availability. • A joint model for a series multi-machine production system is developed. • A quantitative index is introduced to characterize the condition of the machines. • A hybrid performance factor is developed to evaluate the joint effect of maintenance. • Economic dependence and availability dependence are considered in the PM schedule. [ABSTRACT FROM AUTHOR]