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This paper aims to examine the strategic value of reliability and maintainability management in achieving competitiveness and customer satisfaction. It looks into performance metrics for organizational performance and associates reliability and maintainability with such metrics.

The design strategy is based on using models for reliability and profitability assessment as well as total quality management models to illustrate how performance metrics for organizational performance can be enhanced.

It shows there is a need to associate models of profitability assessment to reliability and maintainability management. This will help top management to see the strategic value of reliability and maintainability management and, therefore, adopt necessary organizational transformations to support reliability and maintainability goals.

It is important that the role of reliability and maintainability as important strategic variables be recognized and considered in future research that evaluates organizational performance and successes.

The importance of organizational cultural transformation is noted and a transformation of organizational information system to link reliability management to a central information system such as in an enterprise resource planning (ERP) framework is suggested as a process of improving system availability and reliability.

The aim is to have top management perceive reliability and maintainability issues as part of their strategic initiatives. While the value of total quality management in achieving organizational success is well accepted, reliability and maintainability issues are often viewed at the operational level. Yet, they are critical to achieving quality and organizational success.

Reliability, maintainability and availability of modern complex engineered systems are significantly affected by four basic systems or elements: hardware, software, organizational and human. Computerized Numerical Control Turning Center (CNCTC) is one of the complex machine tools used in manufacturing industries. Several research studies have shown that the reliability and maintainability is greatly influenced by human and organizational factors (HOFs). The purpose of this paper is to identify critical HOFs and their effects on the reliability and maintainability of the CNCTC.

In this paper, 12 human performance influencing factors (PIFs) and 10 organizational factors (OFs) which affect the reliability and maintainability of the CNCTC are identified and prioritized according to their criticality. The opinions of experts in the fields are used for prioritizing, whereas the field failure and repair data are used for reliability and maintainability modeling.

Experience, training, and behavior are the three most critical human PIFs, and safety culture, problem solving resources, corrective action program and training program are the four most critical OFs which significantly affect the reliability and maintainability of the CNCTC. The reliability and maintainability analysis reveals that the Weibull is the best-fit distribution for time-between-failure data, whereas log-normal is the best-fit distribution for Time-To-Repair data. The failure rate of the CNCTC is nearly constant. Nearly 66 percent of the total failures and repairs are typically due to the hardware system. The percentage of failures and repairs influenced by HOFs is nearly only 16 percent; however, the failure and repair impact of HOFs is significant. The HOFs can increase the mean-time-to-repair and mean-time-between-failure of the CNCTC by nearly 65 and 33 percent, respectively.

The paper uses the field failure data and expert opinions for the analysis. The critical sub-systems of the CNCTC are identified using the judgment of the experts, and the trend of the results is verified with published results.

The study aims to perform an extensive literature review in the area of the maintenance decision analysis (MDA), especially in power generation systems. In the basis of this review, the paper proposes a new model for the MDA which involves a combination of reliability, availability, maintainability and safety (RAMS) performance with energy efficiency performance (EEP).

Starting from the opportunity in Sustainable Development Scenario (SDS) by improving the energy efficiency (EE) and using renewable energy for the power generation system, also concerning to the major challenge of maintenance optimization in order to implement maintenance strategy, the maintenance decision-making and energetic efficiency management system (EEMS) have been reviewed. In the context of power generation system's performance, the measurement is also analyzed and identified. Then, the extensive literature review has been performed to compare between RAMS and EEP. And finally, the limitation and gap, where EEP is not yet a complementary consideration during MDA being identified and a new model for the performance-based MDA is proposed.

The new model proposed for the performance-based MDA is able to be used to conduct maintenance decision by utilizing the combination of RAMS and EEP depending on the type of decision required.

There is an opportunity for a maintenance organization of power generation plant to apply this new model proposed for the MDA in order to optimize the maintenance scope and schedule.

The result of work in this paper forms the basis for combining RAMS with EEP as performance-based MDA tools in the context of maintenance of the power generation system.

The purpose of this paper is to propose a practical method of performing maintenance in the offshore industry where engineers have to manage problems such as the high cost of operations, assuring an high availability of the plant, safety on board and environmental protection. Indeed an efficient maintenance method it is necessary in order to offer methods and criteria to select the rights maintenance strategies keeping in to account the environmental, safety and production constrains.

The paper provides an overview of reliability centered maintenance (RCM) and reliability, availability, maintainability methodologies and an integration of the two methodologies in a particular case study in the oil and gas sector.

This paper suggests an improvement of the well-established RCM methodology applicable to industries with high priority level. It is proposed an integration between a reliability analysis and an availability analysis and an application on the offshore oil and gas industry.

The methodology provides an excellent tool that can be utilized in industries, where safety, regulations and the availability of the plant play a fundamental role.

The proposed methodology provides a practical method for selecting the best maintenance strategy considering the equipment redundancy and sparing, the asset’s performance over long time scales, and the system uptime, downtime and slowdowns.

The purpose of this research is to show that reliability analysis and its implementation will lead to an improved whole life performance of the building systems, and hence their life cycle costs (LCC).

This paper analyses reliability impacts on the whole life cycle of building systems, and reviews the up‐to‐date approaches adopted in UK construction, based on questionnaires designed to investigate the use of reliability within the industry.

Approaches to reliability design and maintainability design have been introduced from the operating environment level, system structural level and component level, and a scheduled maintenance logic tree is modified based on the model developed by Pride. Different stages of the whole life cycle of building services systems, reliability‐associated factors should be considered to ensure the system's whole life performance. It is suggested that data analysis should be applied in reliability design, maintainability design, and maintenance policy development.

The paper presents important factors in different stages of the whole life cycle of the systems, and reliability and maintainability design approaches which can be helpful for building services system designers. The survey from the questionnaires provides the designers with understanding of key impacting factors.

The purpose of this paper is to provide results for a complete reliability, availability, and maintainability (RAM) analysis utilizing data sets from a production system in a wine packaging line. Through the illustrated case study, the author demonstrates how RAM analysis is very useful for deciding maintenance intervals, and for planning and organizing the adequate maintenance strategy.

RAM analysis has been done for each machine by using failures data. The parameters of some common probability distributions, such as Weibull, exponential, lognormal, and normal distributions, have been estimated by using the Minitab software package. An investigation to determine which of these distributions provide the best fit for characterizing the failure pattern at machine and line level has been made. Reliability and maintainability of both wine packaging and its machines has been estimated at different mission times with their best fit distribution. High maintainability issues and potential factors with their potential failure modes were presented, through failure mode and effect analysis process.

Analysis of the total downtime, breakdown frequency, reliability, and maintainability characteristics of different machines shows that: first, the availability for the wine packaging line was 91.80 percent, and for the remaining 8.2 percent the line is under repair. Second, about two failures per shift are displayed on the line, whereas for the mean time-to-repair (TTR) a failure is 24 minutes. Third, there is no correlation between the time-between-failures and the TTRs for the wine packaging line. Fourth, the main three factors affecting the maintainability process in the production line are: resources availability, manpower management, and maintenance planning procedures.

This study is anticipated to serve as an illuminating effort in conducting a complete RAM analysis in the much advertised field of wine packaging production line which on the other hand so little has been published on operational availability and equipment effectiveness. It can also be useful to serve as a valid data source for winery product manufacturers, who wish to improve the design and operation of their production lines.

The focus of this paper is on reliability and availability design goals. It aims to provide top‐level estimates of the safety and maintainability of future spacecraft systems.

The developed design tool uses basic reliability principles to estimate the probability of a safe mission and the need for repairs/replacement during ground processing, before launch and start of mission, based on the characteristics of the vehicle's main systems: the number of subsystems, the mean time to repair, and the per subsystem average reliability.

A simple reliability, maintainability and safety model is developed to support the top‐level design process of future space transportation vehicles. It also describes how the developed design tool uses various sensitivity analysis functions to improve design decisions.

The goal of the developed tool is to provide engineers/vehicle developers during the early stages of design with a tool that demonstrates the effect on maintainability of improving component reliability and reducing the number of components.

The purpose of this paper is to implement the six sigma (SS) strategy in a bag sector under actual operating circumstances based on defining-measure-analyze-improve and control (DMAIC). During the project, several statistical tools and methods have been used efficiently to create inferences. Thus, to measure and enhance system efficiency, the author calculate reliability, availability and maintainability (RAM) indices. Based on this research, the author show how the SS method and RAM analysis are very helpful in determining maintenance intervals, as well as in planning and organizing the appropriate maintenance strategy.

This study introduces the step-by-step application of the DMAIC methodology for the identification and reduction of bag production line downtime and examines the present operations management. Thus, statistical techniques are used to analyze the failure and repair database. Pareto analysis, histograms and descriptive statistics at the machine and line-level of the historical data were conducted. Trend and serial correlation testing validated the hypothesis of independence and identical distribution of database was performed. In addition, with their best fit allocation, the RAM of both the bag production line and its machines was estimated at separate mission times.

The main goals of the applied method are to understand the nature of the downtime patterns and to accurately and quantitatively estimate the RAM characteristics of the bag production system. The assessment defines the production line's critical points, requiring further enhancement through an efficient maintenance approach. Therefore, by improving plant efficiency and safety, the author can decrease unplanned downtime and equipment failures.

This research is expected to serve as an attempt to conduct SS DMAIC methodology through RAM assessment and its impact on system efficiency under actual circumstances. The benefit of the methodology is that the manufacturing process is continuously monitored by suitable indicators, the use of which leads to a continuous improvement cycle.

The purpose of this paper is to demonstrate a tactical approach to cope with the issues related to low availability of repairable machines or systems because of their poor reliability and maintainability. It not only explores the significance of availability, but also embarks upon a step-by-step procedure to earmark a relevant replenishment plan to check the mean time between failure (MTBF) and the mean time to repair (MTTR) efficiently.

The literature review identifies the extent to which availability depends on reliability and maintainability, and highlights the diversified challenges appearing among repairable systems. Different improvement initiatives have been suggested to avoid downtime, after analyzing the failure and repair time data graphically. Relevant plots and growth curves captured the historical deviations and trends along with the time, which further helps to create more robust action plans to enrich the respective reliability and maintainability of machines. During the case study, the proposed methodology has been tested on four SPMs and successfully validated the claims after achieving around a 98 percent availability at the end.

Graphical analysis is the key to developing suitable action plans to enhance the corresponding reliability and maintainability of a machine or system. By increasing the MTBF, the reliability level can be improved and similarly quick maintenance activities can help to restore the prospect of maintainability. Both of these actions ultimately reduce the downtime or increase the associated availability exponentially.

The work revolves around the availability of SPMs. Moreover, SPMs have been divided only into series sub-systems. The testability and supportability aspects have not been considered thoroughly during the fabrication of the approach.

The work focusses on the availability of systems and proposed frameworks that helps to reduce downtime or its associated expenditure, which is generally being ignored. As a case study-based work especially on SPMs in the auto sector this paper is quite rare and will motivate affiliated engineers and practitioners to achieve future breakthroughs.

The purpose of this paper is to review, discuss and further develop the production assurance (PA) concept; and to define and describe a typical production assurance program (PAP) and its elements.

An explorative literature study covering PA and dependability concept was carried out on contemporary literature. During the course of the study, meetings and discussions with a number of experts in Sweden and Norway were performed. Different types of data and examples from the oil and gas industries are used to illustrate and support the discussions.

This paper indicates that the concept of PA helps the decision maker to estimate whether a production plant is able to meet customer requirements, as it provides information about the production plant's delivery capacity, production rate and ability to deliver according to design or customer demands. PAP can provide a basis for effective production control.

The material analysed was mainly related to the oil and gas industry. However, the findings and discussion can be transferred to other areas of application, such as mine production plants and chemical process plants.

A PAP is a valuable tool for production plant managers and engineers, not only for documenting a production plant's performance, but also for providing decision support for the development and optimization of the production plant to improve the plant's performance and reduce risk and uncertainties.

In this paper the concept of dependability is extended to include capacity performance and customer requirements or market demand, which provides a measure for delivery assurance or plant production performance in relation to customer requirements. This paper also develops a generic PAP to achieve a high level of delivery assurance.