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The purpose of this paper is to analyze conditional failure rates, and prioritize water pipelines for replacement based on their expected failure rate where pipes are grouped based on age and pipe type. Thus, predictions can be made on the expected number of breaks in future years.

The time to failure of a pipe can be characterized by the stochastic properties of the population as a whole, from which the likelihood of component failure is derived. When the corresponding failure rate is plotted against time, a bathtub‐shaped curve results. The bathtub curve assists in determining maintenance schedules depending on the age of the pipe. Failure rates help determine whether the rates are more than an acceptable best practice threshold to signal replacement.

Ductile iron pipes had the highest failure rates, followed by asbestos cement pipes; PVC and concrete cylinder pipes had the lowest failure rates, but because concrete cylinder pipes are very time‐consuming to repair and very expensive to install, only PVC pipes are recommended on the basis of this study. Cast iron pipes fit the bathtub shape; ductile iron and asbestos concrete were somewhat bathtub shaped, though the early phase period was not apparent; the bathtub curve for concrete cylinder was fully inverted; while PVC pipes showed zero probability of failure during the middle period. The shapes of bathtub curves drawn on conditional failure rates were similar to those for the failure rates. The bathtub curves indicate that the general failure performance of pipe materials is somewhat contrary to general principles in manufacturing.

Analysis of failure serves a practical purpose for water utilities to allocate funds for pipe maintenance and prepare a schedule for pipe replacement, so as to provide the best quality services and safe drinking water to users of the utility.

The proper prioritization of water supply pipes for repair and replacement is of great social importance to the public at large, which expends considerable funds to maintain their drinking water supply.

The study of bathtub curves has not been seen before in the analysis of water supply pipes. A unique discovery is that the traditional shape of the bathtub curve is not always applicable for water supply pipes.

The purpose of this paper is to analyze mathematical aspects of the q‐Weibull model and explore the influence of the parameter q.

The paper uses analytical developments with graph illustrations and an application to a practical example.

The q‐Weibull distribution function is able to reproduce the bathtub shape curve for the failure rate function with a single set of parameters. Moments of the distribution are also presented.

The generalized q‐Weibull distribution unifies various possible descriptions for the failure rate function: monotonically decreasing, monotonically increasing, unimodal and U‐shaped (bathtub) curves. It recovers the usual Weibull distribution as a particular case. It represents a unification of models usually found in reliability analysis. Q‐Weibull model has its inspiration in nonextensive statistics, used to describe complex systems with long‐range interactions and/or long‐term memory. This theoretical background may help the understanding of the underlying mechanisms for failure events in engineering problems.

Q‐Weibull model has already been introduced in the literature, but it was not realized that it is able to reproduce a bathtub curve using a unique set of parameters. The paper brings a mapping of the parameters, showing the range of the parameters that should be used for each type of curve.

This paper aims to determine the stage of the life cycle where the trucks of a waste collection fleet from a Colombian city are located through a reliability approach. The reliability analysis and the evaluation of curve of operational costs allow to know the moment in which it is necessary to make decisions regarding an asset, its maintenance or possible replacement.

For a dataset presented as maintenance work orders, the time to failures (TTFs) for each vehicle in the fleet were calculated. Then, a probability density function for those TTFs was fitted to locate each vehicle in a region of the bathtub curve and to calculate the reliability of the whole fleet. A general functional analysis was also developed to understand the function of the vehicles.

It was possible to determine that the largest proportion of the fleet was in the final stage of the life cycle, in this sense, the entire fleet represent critical assets which in most of cases could be worth replacement or overhaul.

In this study, an address is exposed for the identification of critical equipment by reliability and statistical analysis. This analysis is also integrated with the maintenance management process. This is a broadly interested topic since it allows to support the maintenance and operational decision-making process, indicating the focus of resource allocation all over the entire asset life cycle.

To prevent malpractices, medical staff has adopted inventory time-outs and/or checklists. Accurate inventory and maintenance of surgical instruments decreases the risk of operating room miscounting and malfunction. In our previous study, an individual management of surgical instruments was accomplished using Radio Frequency Identification (RFID) tags. The purpose of this paper is to evaluate a new management method of RFID-tagged instruments.

The management system of RFID-tagged surgical instruments was used for 27 months in clinical areas. In total, 13 study participants assembled surgical trays in the central sterile supply department.

While using the management system, trays were assembled 94 times. During this period, no assembly errors occurred. An instrument malfunction had occurred after the 19th, 56th, and 73th uses, no malfunction caused by the RFID tags, and usage history had been recorded. Additionally, the time it took to assemble surgical trays was recorded, and the long-term usability of the management system was evaluated.

The system could record the number of uses and the defective history of each surgical instrument. In addition, the history of the frequency of instruments being transferred from one tray to another was recorded. The results suggest that our system can be used to manage instruments safely. Additionally, the management system was acquired of the learning effect and the usability on daily maintenance. This finding suggests that the management system examined here ensures surgical instrument and tray assembly quality.

Quality audits are prominent and proven management tools for assessing compliance and effectiveness of quality systems. They are commonly used in the effort to improve overall business performance. However, similarly to any other physical or conceptual system, they may fail to achieve objectives set forth, raising concerns among auditees and clients alike. Argues for the provision of adequate confidence to various interested parties in the quality of auditing services. A quality audit is conceptualized using the systems approach. Subsequently, a quality assurance framework based on the application of the 1994 and 2000 versions of the ISO 9001 standard in auditing is presented. Audit system effectiveness is modeled using the concepts of audit reliability, availability and suitability. Audit failures, risks and maintainability are addressed in detail. It is concluded that audit managers must ensure appropriate levels of quality and effectiveness of quality audit systems.

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.

The purpose of this paper is to compare four life data models, namely the exponential and the Weibull models, and their corresponding generalized versions, q-exponential and q-Weibull models, by means of one practical application.

Application of the models to a practical example (a welding station), with estimation of parameters by the use of the least squares method, and the Akaike Information Criterion (AIC).

The data of the example considered in this paper is divided into three regimes, decreasing, constant and increasing failure rate, and the q-Weibull model describes the bathtub curve displayed by the data with a single set of parameters.

The simplicity and flexibility of the q-Weibull model may be very useful for practitioners of reliability analysis, and its benefits surpasses the inconvenience of the additional parameter, as AIC shows.

The q-Weibull model is compared in detail with other three models, through the analysis of one example that clearly exhibits a bathtub curve, and it is shown that it can describe the whole time range with a single set of parameters.

Provides examples of duty variability based on field tests conducted during ordinary operating conditions. A severity‐based maintenance approach is introduced as complementary to the reliability‐centred maintenance initiatives currently being introduced in various mining companies. The essential component of this approach is a series of equipment monitors (called “dutymeters”) that continuously monitor and log the real duty on the machine as well as some machine parameters that can be used for machine health diagnostics. Describes application of this concept to a range of machinery including draglines, shovels, haul trucks and longwall equipment.

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.