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The Duane reliability growth model has a number of inherent limitations that make it unsuitable for monitoring reliability improvement progress. These limitations are explored and a model based on variance‐stabilizing transformation theory is explained. This model retains the ease of use while also avoiding the disadvantages of the Duane model. It represents a more useful graphical model for portraying reliability improvement at development team meetings. Computer simulations have shown that the new model provides a better fit to the data over the range of Duane slopes normally observed during a reliability growth program. The instantaneous mean time between failures (MTBF) equation for the new model is developed. Computer simulations show that its use results in higher values of instantaneous MTBF than that achieved by the Duane model. The new model also reduces the total test time for achieving a particular specified instantaneous MTBF. Finally, software failure data from an actual project illustrates the calculations and benefits of the new model.

The purpose of this paper is to define reliability requirements to be imposed on electric engines to assure similar or higher value of mean time between failures (MTBF) for mixed piston-electric propulsion configurations when compared to classic and unconventional piston engine configurations.

Reliability estimation was done using mathematical model of safety of light aircraft commercial operations. The model was developed on the basis of Federal Aviation Administration and National Transport Safety Board data. The analysis was conducted for numerous piston and electric configurations. It allowed comparison of selected solutions and definition of relation between electric engine MTBF and MTBF calculated for entire mixed piston-electric propulsion system.

It was found that, from reliability point of view, mixed piston-electric engine propulsion is attractive alternative for classic single- and twin-piston configuration. It would allow to at least doubling of MTBF for propulsion without increase of operational cost.

Rationale behind exploiting electric propulsion in aviation is provided. Relation between electric engine reliability and entire propulsion reliability was identified and defined. Minimum requirements concerning MTBF value for electric engine application in aviation was assessed. Conclusions from this study can be used for definition of requirements for new aircraft and by the regulatory authorities.

Originality consists in use of real accident statistics included in mathematical model of safety for assessment of MTBF for various classic and novel piston and piston-electric engine configurations of light aircraft. Output from the study can be exploited by the industry.

The aim of this paper is to explore the usefulness of repairable parts simple historical databases in assisting the human factors experts to identify candidate areas for applying human factors methods. Therefore, also contributing to the search for maintenance quality improvement.

The study was based on the failure history of part fleets installed on the same type of jet engines, and used mean time between failures (MTBF) and failure rates plots, the Laplace trend test, the AMSAA‐Crow‐Duane model and serial correlations.

Increasing and decreasing trends in failure rates indicated factors that cause deflection from the literature assumptions of constant failure mode and “as good as new” maintenance philosophy. Further statistical calculations revealed patterns between MTBF and frequency of maintenance, specific serial numbers (SN) vulnerability to replacement and depot maintenance tasks, correlations between MTBF and number of both installations and maintenances, and influence of the maintenance month on the maintenance‐failure hours' interval.

The literature refers to the relation between the parts reliability and the human factors in the maintenance domain. The research confirmed the literature references in data collection problems coming from human factors interferences; the patterns found were attributed to system deficiencies related to workload management, parts configuration management, supervision and manufacturing problems.

The application of this research in combination with methods such as field observations and interviews of personnel involved in the maintenance domain can uncover specific maintenance working environment weaknesses and lead to suitable remedies.

The purpose of this paper is to further develop the Decision Making Grid (DMG) proposed by Ashraf Labib (e.g. Labib, 1998, 2004; Fernandez et al., 2003; Aslam-Zainudeen and Labib, 2011; Stephen and Labib, 2018; Seecharan et al., 2018) by proposing an innovative solution for determining proactive maintenance tactics based on mean time between failures (MTBF) and mean time to repair (MTTR) indicators.

First, the influence of MTTR and MTBF indicators on proactive maintenance tactics was computed. The tactics included risk-based maintenance (RBM), reliability-centered maintenance (RCM), total productive maintenance (TPM), design out maintenance (DOM), accessibility-centered maintenance (ACM) and business-centered maintenance (BCM). Then, the tactics were allocated to the cells of a DMG with MTTR and MTBF axes. The proposed approach was examined on 32 pieces of equipment of the Esfahan Steel Company and appropriate maintenance tactics were consequently determined.

The findings indicate that the DOM, BCM, RBM and ACM tactics with weights of 0.86, 0.94, 0.68 and 1.00 are located at the corners of the DMG, respectively. The two remaining tactics of TPM and RCM are located at the middle corners. Also, the results indicate that the share of tactics per spotted equipment in the grid as 62, 22 and 16 percent for RCM, DOM and BCM, respectively.

While reactive and preventive maintenance strategies include corrective, prospective, predetermined, proactive and predictive policies, the focus of this study was merely on the tactics of proactive maintenance policy. The advantage of the developed DMG over Labib’s DMG lies in its application for equipment with the unique condition of the bathtub curve.

While the basic DMG has been mostly used regardless of the type of maintenance policies, this study provides a DMG for a specific application regarding the proactive policy. In addition, the heuristic approach proposed for the development of DMG distinguishes this study from other studies.

Key performance indicators (KPIs) of maintenance systems serve as benchmarks to workers and organizations to compare their goals for decision-making purposes. Unfortunately, the effects of one KPI on the other are least known, restraining decisions on prioritization of KPIs. This article examines and prioritizes the KPIs of the maintenance system in a food processing industry using the novel Taguchi (T) scheme-decision-making trial and evaluation laboratory (DEMATEL) method, Taguchi–Pareto (TP) scheme–DEMATEL method and the DEMATEL method.

The causal association of maintenance process parameters (frequency of failure, downtime, MTTR, MTBF, availability and MTTF) was studied. Besides, the optimized maintenance parameters were infused into the DEMATEL method that translates the optimized values into cause and effect responses and keeping in view the result of analysis. Data collection was done from a food processing plant in Nigeria.

The results indicated that downtime and availability have the most causal effects on other criteria when DEMATEL and T-DEMATEL methods were respectively applied to the problem. Furthermore, the frequency of failure is mostly affected by other criteria in the key performance indication selection using the two methods. The combined Taguchi scheme and DEMATEL method is appropriate to optimize and establish the causal relationships of factors.

Hardly any studies have reported the joint optimization and causal relationship of maintenance system parameters. However, the current study achieves this goal using the T-DEMATEL, TP-DEMATEL and DEMATEL methods for the first time. The applied methods effectively ease decisions on prioritization of KPIs for enhancement.

The reliability and maintainability of tunnel infrastructure and systems is an important factor in assuring normal operation of a tunnel. Evaluating availability of a large‐scale tunnel that includes civil, electrical, mechanical and electronic systems is a difficult task. The purpose of this paper is to present a methodology for performing such assessments, featuring the use of the Markov model.

The methodology involves application of failure mode, effect and criticality analysis (FMECA), state space diagram construction, formulation of state space equations, and development of transitional matrices. It also involves transformation of multi‐state models into two‐state models (each comprises of an “up” state and a “down” state) through the use of the frequency and duration method for determining the failure and repair rates, as well as the mean‐time‐between‐failures (MTBF) of the entire tunnel. By using the proposed bottom‐up approach, a MTBF tree linking the availability measures of individual equipment with those of sub‐systems, and ultimately the whole tunnel can be developed.

The tunnel availability measures obtained by this analysis can be used in making comparisons between different tunnel designs so as to determine the value for money of various options. Furthermore, weaknesses in a tunnel design can be identified in the analysis. The information obtained from this method can also be used to evaluate adequacy, security and maintainability of a tunnel.

The reliability and maintainability of tunnel infrastructure and systems are crucial factors for ensuring safety of tunnel operation. Unsafe conditions will cause closure of a tunnel. Efforts to improve availability of a tunnel often increase the tunnel's construction cost. Due to the complexity of tunnel systems, it is difficult to compare different tunnel designs, and trade‐off analyses to strike a balance between target availability and construction cost of a tunnel design are seldom performed. This paper presents a systematic methodology to address these issues. This methodology allows tunnel management to evaluate the adequacy, security and maintainability of a tunnel so that design weaknesses can be identified and the value of design improvements can be determined. The methodology can also be used to evaluate designs of other complex systems such as power generation or petrochemical processing plants.

A worked example demonstrating the application of the proposed methodology is presented in this paper.

Recently many European countries have incurred crises in public finance despite the fact that EU institutions have pushed the national governments toward the sustainability of public finance with compulsory and voluntary rules regarding fiscal governance. This paper investigates the relations between the quality of fiscal governance and the financial virtuosity of national fiscal policy. We proposed a general framework for analyzing the fiscal governance issue and we empirically tested the correlation between the dimensions of fiscal governance and the budgetary performance of EU countries. The results showed a positive correlation between the quality of fiscal governance in the EU countries and financial surplus in the period concerned. However further investigations are needed and an effort should be made to collect uniform data on fiscal governance in the European Union.

This study aims to obtained the failure probability distributions of subsystems for industrial robot and filtrate its fault data considering the complicated influencing factors of failure rate for industrial robot and numerous epistemic uncertainties.

A fault data screening method and failure rate prediction framework are proposed to investigate industrial robot. First, the failure rate model of the industrial robot with different subsystems is established and then the surrogate model is used to fit bathtub curve of the original industrial robot to obtain the early fault time point. Furthermore, the distribution parameters of the original industrial robot are solved by maximum-likelihood function. Second, the influencing factors of the new industrial robot are quantified, and the epistemic uncertainties are refined using interval analytic hierarchy process method to obtain the correction coefficient of the failure rate.

The failure rate and mean time between failure (MTBF) of predicted new industrial robot are obtained, and the MTBF of predicted new industrial robot is improved compared with that of the original industrial robot.

Failure data of industrial robots is the basis of this prediction method, but it cannot be used for new or similar products, which is the limitation of this method. At the same time, based on the series characteristics of the industrial robot, it is not suitable for parallel or series-parallel systems.

This investigation has important guiding significance to maintenance strategy and spare parts quantity of industrial robot. In addition, this study is of great help to engineers and of great significance to increase the service life and reliability of industrial robots.

This investigation can improve MTBF and extend the service life of industrial robots; furthermore, this method can be applied to predict other mechanical products.

This method can complete the process of fitting, screening and refitting the fault data of the industrial robot, which provides a theoretic basis for reliability growth of the predicted new industrial robot. This investigation has significance to maintenance strategy and spare parts quantity of the industrial robot. Moreover, this method can also be applied to the prediction of other mechanical products.

This paper aims to address the problem of real‐time control and monitoring of a failure prone manufacturing system in an intelligent and optimum way. This paper also aims to bridge the existence of a gap between maintenance systems and production systems.

A fuzzy logic based controller is used to achieve the desired target. Monitoring the process is performed by means of using supervisory control and data acquisition (SCADA) system. The integration between the fuzzy logic controller (FLC) and SCADA system is also presented. The software is developed and used to monitor and control a miniaturised system in online and real‐time condition.

This paper shows that by using fuzzy logic, the relationship between inputs and outputs is clearly shown, which eventually provide more tractable result than the dynamical analysis one. Moreover, the response surface generated by the fuzzy logic offers visual aid, adaptive and flexible operation to investigate the inputs and outputs relationships.

Future research direction would be to embed such a model into a user‐friendly software. A further development would be to investigate means of generating the rule‐based directly from the data without the need for eliciting knowledge from experts.

This paper provided a practical applications that can help solving the problem of lack of real‐time control and monitoring of a failure prone manufacturing system in an intelligent an optimum way. This paper also helped in bridging the existing gap between maintenance systems and production systems.

The results of the performance comparisons show that in most studied cases, the performance of the developed system is better than the classical analytic approach.

The purpose of this paper is to develop an attractiveness index-based warranty cost model considering decision variables as design alternatives, warranty duration and support level.

A warranty optimization approach is illustrated using a real life example of an automobile engine with Mean Time Between Failures and Warranty Attractiveness Index as constraints.

It will help to improve the customer satisfaction by giving a more attractive warranty compared to that being offered by the competitors.

Approaches that consider the effect of decision variables on attractiveness of a warranty policy in a quantitative manner have received relatively less attention. The paper attempts to capture the attractiveness of warranty from the manufacturer as well as customer point of view.

The proposed approach will help manufacturers to take appropriate decisions related to warranty parameters and component selection at the design stage.