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The purpose of this paper is to focus on an optimizing maintenance policy with repair limit time for a new type of aircraft component, in which the lifetime is assumed to be an uncertain variable due to no historical operation data, and the repair time is a random variable that can be described by the experimental data.

To describe this repair limit time policy over an infinite time horizon, an extended uncertain random renewal reward theorem is firstly proposed based on chance theory, involves uncertain random interarrival times and stochastic rewards. Accordingly, the uncertain random programming model, which minimized the expected maintenance cost rate, is formulated to find the optimal repair limit time.

A numerical example with sensitivity analysis is provided to illustrate the utility of the proposed policy. It provides a useful reference and guidance for aircraft optimization. For maintainers, it plays an important guiding role in engineering practice.

The proposed uncertain random renewal reward process proved useful for the optimization of maintenance strategy with maintenance limited time for a new type of aircraft components, which provides scientific support for aircraft maintenance decision-making for civil aviation enterprises.

Usually the renewal stochastic processes are used for description of repairable systems performance in the fixed environment. The main characteristic that arises in applications is the mean number of failures or repairs and this is very significant for the spares assessment. In this paper the situation is generalized for the case of changing environment (deterministic or random). The renewal equations for various types of repair, ranging from perfect to minimal via general, are analyzed from the maintenance point of view. Several simple examples are considered.

The paper aims to explore unavailability of dormant systems that are under both preventive and corrective maintenance. Preventive maintenance is considered as a failure based maintenance model, where full renew is realized at the occurrence of every nth failure. It proposes the imperfect corrective maintenance model, where each restoration process deteriorates the system lifetime, probability distribution of which is gradually changed via increasing failure rate.

Basic reliability mathematics necessary for unavailability quantification of a system which undergoes a real aging process with maintenance has been derived proceeding from renewal theory. New renewal cycle was defined to cover the real aging process and the expectation of its length was determined. All events resulting in the failure of studied system were explored to determine their probabilities. An integral equation where the unavailability function characterizing studied system is its solution was derived.

Preventive maintenance is closely connected with the occurrence of the nth failure, which starts its renew. The number n can be considered as a parameter which significantly influences the unavailability course. The paper shows that the real aging process characterized by imperfect repairs can significantly increase the unavailability courses in contrast with theoretical aging. This is true for both monitored and dormant systems.

Although mathematical methods used in this article were inspired and influenced by the work of reference (van der Weide and Pandey, 2015), derivation of final formulas for unavailability quantification considering the new renewal cycle is original. Idea of the real aging process is new as well. This paper fulfils an identified need to manage the maintenance of realistically aging systems.

The purpose of this paper is to estimate the required number of robots consisting of some non-repairable components, by employing a renewal model. Considering the importance of the availability of standby autonomous robots for reducing and preventing down-times of advanced production systems, which imposes a considerable loss, the present research tries to introduce a practical model for the determination of the required number of autonomous robots.

Most of the available research on the estimation of the required standby components based on the reliability characteristics of components has not considered the environmental factors influencing the reliability characteristics. Therefore, such estimations are not accurate enough. In contrast, this paper focuses on the influence of the environmental and human factors (e.g. the operators’ skill) on the robot reliability characteristics.

A model based on the Weibull renewal process combined with the cold standby strategy is developed for reliability evaluation of the system. The effectiveness of the proposed integrated reliability evaluation model is worked out in some cases.

Determining a required number of robots is an important issue in availability and utilization of a complex robotic production system. In an advanced production system, while the estimation process of a required number of robots can be performed through different approaches, one of the realistic estimation methods is based on the system’s reliability that takes into consideration the system operating environment. To forecast the required number of robots for an existing production system, in some cases, the assumption of a constant failure rate does not differ much from the assumption of a non-constant failure rate and can be made with an acceptable error.

The purpose of this paper is to present the results of the application of various models to estimate the reliability in railway repairable systems.

The methodology proposed by the International Electrotechnical Commission (IEC), using homogeneous Poisson process (HPP) and non-homogeneous Poisson process (NHPP) models, is adopted. Additionally, renewal process (RP) models, not covered by the IEC, are used, with a complementary analysis to characterize the failure intensity thereby obtained.

The findings show the impact of the recurrent failures in the times between failures (TBF) for rejection of the HPP and NHPP models. For systems not exhibiting a trend, RP models are presented, with TBF described by three-parameter lognormal or generalized logistic distributions, together with a methodology for generating clusters.

For those systems that do not exhibit a trend, TBF is assumed to be independent and identically distributed (i.i.d.), and therefore, RP models of “perfect repair” have to be used.

Maintenance managers must refocus their efforts to study the reliability of individual repairable systems and their recurrent failures, instead of collections, in order to customize maintenance to the needs of each system.

The stochastic process models were applied for the first time to electric traction systems in 23 trains and to 40 escalators with ten years of operating data in a railway company. A practical application of the IEC models is presented for the first time.

The purpose of this paper is to develop a double-objective economic statistical design (ESD) of (X ‾) control chart under Weibull failure properties with the Linex asymmetric loss function. The authors have expressed the probability of type II error (β) as the statistical objective and the expected cost as the economic objective.

The design used in this study is based on a double-objective economic statistical design of (X ‾) control chart with Weibull shock model via applying Banerjee and Rahim's model for non-uniform and uniform schemes with Linex asymmetric loss function. The results in the least average cost and β in uniform and non-uniform schemes by Linex loss function, compared with the same schemes without loss function.

Numerical results indicate that it is not possible to reduce the second type of error and costs at the same time, which means that by reducing the second type of error, the cost increases, and by reducing the cost, the second type of error increases, both of which are very important. Obtained based on the needs of the industry and which one has more priority has the right to choose. These designs define a Pareto optimal front of solutions that increase the flexibility and adaptability of the X ‾ control chart in practice. When the authors use non-uniform schemes instead of uniform schemes, the average cost per unit time decreases by an average and when the authors apply loss function, the average cost per unit time increases by an average. Also, this quantity for double-objective schemes with loss function compared to without loss function schemes in cases uniform and non-uniform increases. The reason for this result is that the model underestimated the costs before using the loss function.

This research adds to the body of knowledge related to flexibility in process quality control. This article may be of interest to quality systems experts in factories where the choice between cost reduction and statistical factor reduction can affect the production process.

The cost functions for double-objective uniform and non-uniform sampling schemes with the Weibull shock model based on the Linex loss function are presented for the first time.

The aim of this study is to present the economic‐statistical design of an EWMA control chart for monitoring the process dispersion.

The optimal economic‐statistical design of the S EWMA chart was determined for a wide benchmark of examples organized as a two level factorial design and was compared with the designs obtained for the S Shewhart chart. Both the two charts have been designed so that an equal number of false alarms (in‐control Average Run Length) is expected.

The S EWMA allows significant hourly cost savings to be achieved for the entire set of process scenarios with respect to the S Shewhart; a mean percentage cost saving of 6.77 per cent is obtained for processes characterized by a reduction in process dispersion (i.e. processes whose natural variability is reduced through an external technological intervention), whereas up to a 9.78 per cent saving is achieved for processes whose dispersion is increased by the occurrence of an undesired special cause.

The proposed S EWMA chart can be considered as an effective tool when statistical process control procedures should be implemented on a process with the aim of monitoring its data dispersion.

In literature the economic design of EWMA charts covers only the process cost evaluation when the sample mean is monitored; here, the study is extended to the sample standard deviation to investigate if the EWMA scheme still outperforms the Shewhart chart. An extensive analysis is proposed to evaluate the influence of the process operating parameters on the EWMA chart design variables.

Degradation of repairable components may not be similar after each maintenance activity; thus, the classic (traditional-time based) maintenance policies, which consider preventive maintenance (PM), age-based maintenance and overhauls to be done at fixed time interval, may fail to monitor the exact condition of the component. Thus, a progressive maintenance policy (PMP) may be more appropriate for the industries that deal with large, complex and critical repairable systems (RS) such as aerospace industries, nuclear power plants, etc.

A progressive maintenance policy is developed, in which hard life, PM scheduled time and overhaul period of the system are revised after each service activity by adjusting PM interval and mean residual life (MRL) such that the risk of failure is not increased.

A comparative study is then carried out between the classic PM policy and developed PMP, and the improvement in availability, mean time between failures and reduction in maintenance cost is registered.

The proposed PMP takes care of the equipment degradation more efficiently than any other existing maintenance policies and is also flexible in its application as the policy can be continuously amended as per the failure profile of the equipment. Similar maintenance policies assuming lifetime distributions are available in the literature, but to ascertain that the proposed PMP is more suitable and applicable to the industries, this paper uses Kijima-based imperfect maintenance models. The proposed PMP is demonstrated through a real-time data set example.

Industries generally require good maintenance, repair and overhaul (MRO) facilities. Maintenance activities at MRO cover the normal scheduled check-ups known as scheduled preventive maintenance (SPM) whereas an overhaul reviews and rejuvenates the complete system at a scheduled time. The literature is reasonably stocked with reliability modelling of repairable systems considering both the corrective maintenance (CM) and SPM as imperfect. However, in all these situations the overhaul is modelled as perfect repair. Thus, the purpose of this research paper is to develop a mathematical model for the estimation of reliability parameters considering the complete MRO as imperfect.

The paper proposes arithmetic reduction of age (Kijima I) based virtual age model to estimate reliability parameters by considering the complete MRO as imperfect and provides the likelihood and log-likelihood functions for parameter estimation of the proposed model and also presents the various extensions of the proposed model.

For analysis, two real-time data sets of two components, i.e. turbostarter and plunger pump are considered. The analysis mainly focuses on intensity function and availability of components. The availability analysis of the components directly affects the cost analysis. It is very important to analyze the realistic trend of availability, and the comparative analysis shows that the assumption of perfect overhaul overestimates and minimal overhaul underestimates the performance of the components whereas assumption of imperfect overhaul portraits more sensible deteriorating and availability trend of the components.

The proposed methodology in this paper is a novice and not available in the literature.

Option to review land rents to prevailing market rents and option to renew leases for another term are two important options embedded in the public industrial land leases in Singapore, managed by the Jurong Town Corporation (JTC). The land rents of JTC leases are reviewed every year subject to a cap on the land rent increase. The rent cap, which is historically lower than the prevailing market growth rate, widens the gap between the contract rent and the prevailing market rent as the lease progresses. This creates disincentives to the lessor for not exercising the rent review option, because the option is in‐the‐money. The rent gap, on the other hand, is also translated into substantial profit rents for lessees who hold onto the leasehold interests of industrial lands. By assuming two different probability distributions for the ex‐ante prevailing market rents, the profit rents were simulated to derive at the values of a hypothetical 30‐year lease, which range from US$47.93 (S$86.45) per square meter (psm) (Sungei Kadut, Kranji) to US$236.05 (S$425.74) psm (West Coast Highway). Based on these simulated 30‐year leasehold values and assumptions of other input parameters: equated yield (e = 10 percent), risk free rate (R_f = 4.52), volatility of leasehold value (σ = 15 percent), term of lease (T = 30 years) and rental growth cap (g = 7.6 percent), the premiums for the lease renewal options were estimated to be in a range of US$4.55 (S$8.21) psm to US$22.26 (S$40.15) psm.