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The purpose of this analysis was to attempt to improve the reliability of a rotor support system of a modern aircraft engine.

The process used for carrying out FMEA is specified by MIL‐STD‐1629A procedure for carrying out failure mode, effects and criticality analysis.

In increasing demand in the avionics sector, particularly in modern defence and civil aircraft, safety and reliability are the prime concerns to complete the mission successfully. Technocrats are made to rethink the safety of complete systems by adding redundancy to the critical activities. A rotor support system (RSS) is an integral part of a gas turbine engine used in any aircraft. As its name implies, the rotor support system shares the load of the rotating component of an engine, hence the rotor support system plays a vital role in any aircraft engine. It shares the load of compressor rotor and stator, turbine rotor and stator, inter‐casing, and exhaust system of a gas turbine engine. Any failure in such a system may make the entire aircraft fail. Therefore it is worth carrying out Failure Modes and Effects Analysis (FMEA) on such a critical system. FMEA is one of the effective reliability assessment tools, which evaluate systematically and document the potential failure modes of a system or equipment and their causes. It helps in grading the severity of all potential failure modes and is useful in carrying out the changes in the early phase of design. The analysis starts with the potential failure of the smallest component at the final indenture and goes up to the initial indenture level.

The paper adds insight into the reliability improvement of the rotor support system of modern aircraft.

Repairable system reliability analysis is very important to industry and, for complex systems, replacing a failed component is the most commonly used corrective maintenance action as it is an inexpensive way to restore the system to its functional state. However, failure data analysis for repairable system is not an easy task and usually a number of assumptions which are difficult to validate have to be made. Despite the fact that time series models have the advantage of few such assumptions and they have been successfully applied in areas such as chemical processes, manufacturing and economics forecasting, its use in the field of reliability prediction has not been that widespread. In this paper, we examine the usefulness of this powerful technique in predicting system failures. Time series models are statistically and theoretically sound in their foundation and no postulation of models is required when analysing failure data. Illustrative examples using actual data are presented. Comparison with the traditional Duane model, which is commonly used for repairable system, is also discussed. The time series method gives satisfactory results in terms of its predictive performance and hence can be a viable alternative to the Duane model.

The purpose of this paper is to develop novel preventive maintenance (PM) modeling methods for a cold standby system subject to two types of failures: random failure and deterioration failure.

The system consists of two components and a single repair shop, assuming that the repair shop can only service for one component at a time. Based on semi-Markov theory, transition probabilities between all possible system states are discussed. With the transition probabilities, Markov renewal equations are established at regenerative points. By solving the Markov regenerative equations, the mean time from the initial state to system failure (MTSF) and the steady state availability (SSA) are formulated as two reliability measures for different reliability requirements of systems. The optimal PM policies are obtained when MTSF and SSA are maximized.

The result of simulation experiments verifies that the derived maintenance models are effective. Sensitivity analysis revealed the significant influencing factors for optimal PM policy for cold standby systems when different system reliability indexes (i.e. MTSF and SSA) are considered. Furthermore, the results show that the repair for random failure has a tremendous impact on prolonging the MTSF of cold standby system and PM plays a greater role in promoting the system availability of a cold standby system than it does in prolonging the MTSF of system.

In practical situations, system not only suffers normal deterioration caused by internal factors, but also undergoes random failures influenced by random shocks. Therefore, multiple failure types are needed to be considered in maintenance modeling. The result of the sensitivity analysis has an instructional role in making maintenance decisions by different system reliability indexes (i.e. MTSF and SSA).

This paper presents novel PM modeling methods for a cold standby system subject to two types of failures: random failure and deterioration failure. The sensitivity analysis identifies the significant influencing factors for optimal maintenance policy by different system reliability indexes which are useful for the managers for further decision making.

Defines the concept of “organisational failure” in information systems (IS) development, and proposes a diagnostic model drawn from research done into IS consultancy firms that develop systems using a variety of methodologies. The research involved a qualitative study aimed at the nature of the development process and the role of organisational issues in this process. The model’s elements and relationships were determined by the research findings. Presents two cases of failure that show how IS failure is rooted in organisational pathology and examine existing failure concepts. The concept and model proposed can be used by practitioners and management before and during a project for diagnosing organisational failure before it interferes with IS development and afterwards for extracting deeper rooted organisational learning from failure.

The internet of things and just-in-time are the embryonic model of innovation for the state-of-the-art design of the service system. This paper aims to develop a fault-tolerant machining system with active and standby redundancy. The availability of the fault-tolerant redundant repairable system is a key concern in the successful deployment of the service system.

In this paper, the authors cogitate a fault-tolerant redundant repairable system of finite working units along with warm standby unit provisioning. Working unit and standby unit are susceptible to random failures, which interrupt the quality-of-service. The system is also prone to common cause failure, which tends its catastrophe. The instantaneous repair of failed unit guarantees the increase in the availability of the unit/system. The time-to-repair by the single service facility for the failed unit follows the arbitrary distribution. For increasing the practicability of the studied model, the authors have also incorporated real-time machining practices such as imperfect coverage of the failure of units, switching failure of standby unit, common cause failure, reboot delay, switch over delay, etc.

For deriving the explicit expression for steady-state probabilities of the system, the authors use a supplementary variable technique for which the only required input is the Laplace–Stieltjes transform (LST) of the repair time distribution.

For complex and multi-parameters distribution of repair time, derivation of performance measures is not possible. The authors prefer numerical simulation because of its importance in the application for real-time uses.

The stepwise recursive procedure, illustrative examples, and numerical results have been presented for the diverse category of repair time distribution: exponential (M), n-stage Erlang (Ern), deterministic (D), uniform (U(a,b)), n-stage generalized Erlang (GE_[n]) and hyperexponential (HE_[n]).

Concluding remarks and future scopes have also been included. The studied fault-tolerant redundant repairable system is suitable for reliability analysis of a computer system, communication system, manufacturing system, software reliability, service system, etc.

As per the survey in literature, no previous published paper is presented with so wide range of repair time distribution in the machine repair problem. This paper is valuable for system design for reliability analysis of the fault-tolerant redundant repairable.

The main goal of this paper is to develop novel Tω(weakest t-norm)-based fuzzy arithmetic operations to analyze the intuitionistic fuzzy reliability of Printed Circuit Board Assembly (PCBA) using fault tree.

The paper proposes a fuzzy fault tree analysis (FFTA) method for evaluating the intuitionistic fuzzy reliability of any nonrepairable system with uncertain information about failures of system components. This method uses a fault tree for modeling the failure phenomenon of the system, triangular intuitionistic fuzzy numbers (TIFNs) to determine data uncertainty, while novel arithmetic operations are adopted to determine the intuitionistic fuzzy reliability of a system under consideration. The proposed arithmetic operations employ Tω(weakest t-norm) to minimize the accumulating phenomenon of fuzziness, whereas the weighted arithmetic mean is employed to determine the membership as well as nonmembership degrees of the intuitionistic fuzzy failure possibility of the nonrepairable system. The usefulness of the proposed method has been illustrated by inspecting the intuitionistic fuzzy failure possibility of the PCBA and comparing the results with five other existing FFTA methods.

The results show that the proposed FFTA method effectively reduces the accumulating phenomenon of fuzziness and provides optimized degrees of membership and nonmembership for computed intuitionistic fuzzy reliability of a nonrepairable system.

The paper introduces Tω(weakest t-norm) and weighted arithmetic mean based operations for evaluating the intuitionistic fuzzy failure possibility of any nonrepairable system in an uncertain environment using a fault tree.

Unmanned aircraft applications are quickly expanded in different fields. These systems are complex that include several subsystems with different types of technologies. Maintenance and inspection planning is necessary to obtain optimal performance and effectiveness. The failure rate in these systems is more than commercial and manned aircraft since they are usually cheaper. But maintenance and operation planning are difficult because we deal with a system that has multi-components, multi-failure models, and different dependencies between subsystems without any advanced health monitoring system. In this paper, this matter is considered and a framework to determine optimal maintenance and inspection plan for this type of system is proposed to improve system reliability and availability. The new criteria according to this field are proposed.

Maintenance of unmanned systems influences their readiness; also, according to the complexity of the system and different types of components, maintenance programming is a vital requirement. The plan should consider several criteria and disciplines; thus, multicriteria decision approaches may be useful. On another side, the reliability and safety of unmanned aircraft are the most important requirements in the design and operation phases. The authors consider these parameters and develop a framework based on risk-based maintenance to overcome the problems for unmanned systems. This framework consists of two stages: at the first stage, the critical components and failure modes are determined by FMEA, and in the second stage, the priority of maintenance tasks is determined by a fuzzy multicriteria weighted decision system. In this study, fourteen criteria with different levels of importance are developed and proposed to find the best plan for maintenance and inspection intervals. These criteria have been extracted from the literature review, the author's experience, and expert opinions.

A novel framework for risk-based maintenance has been proposed. Risk determination and risk criteria are the most important factors in this framework. Risks are determined by FMEA, and new criteria are proposed that are used for decision-making. These criteria are proposed based on practical experience and experts' opinions for the maintenance process in the aeronautic industry. These are evaluated by industrial cases, and this framework capability has been demonstrated.

The proposed framework and criteria for small unmanned aircraft have been developed based on a practical point of view and expert opinion. Thus for implementation in other aeronautic industries, the framework may need a minor modification.

Two important subsystems of an unmanned aircraft have been studied, and the capabilities of this method have been presented.

This research is original work to determine a maintenance program for unmanned aircraft that their application has rapidly grown up. Practical and design parameters have been considered in this work.

Failures represent an important source of variability in service operations and a major performance challenge. As a consequence, the effective management of failures is a prerequisite to achieve lean services. The purpose of this paper is to focus on the operational perspective of failures; that is attempt to quantify the impact of critical failure parameters on key system performance measures, such as cycle time and work‐in‐process. The authors also analyze various operational concepts, or management practices, that service organizations use to address the effects of failures.

Discrete event simulation was used to model the behavior of a typical two‐stage service system (front‐office, back‐office), and design of experiments to estimate the impact of significant parameters that characterize service failures, on key system performance measures. In a final experiment, three of the most common practices used by management to address failures, and the impact of these practices on system performance under different conditions were analyzed. The findings are validated through a case study in the financial services.

The results of this study suggest that failures and rework degrade the performance of service systems. This adverse impact is reinforced, if specific inputs of the system deteriorate, such as the ability of the service organization to deliver appropriate quality, to detect failures early and to be capable enough to recover timely and efficiently from failures. In addition, the results show that typical management practices used to address the impact of failures have strengths and weaknesses depending on the characteristics of both the service system and the failures. If this is not taken into consideration, the above managerial practices may lead only to short‐term improvements, while the main causes of failures will remain unsolved.

Analyzing the impact of failures in a service environment is a challenging task. This paper complements the existing literature on service failures by focusing on the related effects on operations. With the use of simulation, the authors quantify the impact of failures on key aspects of operations of the service system and also provide useful insight into the parameters that determine the effectiveness of various management practices used in practice to address failures. Finally, the authors use a case study in financial services to validate the results.

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.