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The purpose of this study is to highlight special characteristics of building services systems and investigate how practitioners view reliability and maintenance. These characteristics include energy‐hungry services systems, operating modes, maintenance types, the relationship between procurement costs and maintenance costs.

The practitioners' viewpoints on reliability and maintenance are explored through a workshop. The authors wish to draw the attention of researchers in the reliability and maintenance community and furthermore emphasise the difference between building services systems and systems in industries other than construction.

It is shown that a lack of failure data and maintenance data is the main problem from both academic researchers' and industrial practitioner's points of view. The paper suggests that there exists no fixed cost ratio available to apply to building services systems; the analysis of RAMS (Reliability, Availability, Maintainability and Safety) should include duty cycles and the environment; and clients of the construction industry would benefit from mandating a LCC to be applied to the build.

The gap between academia and practitioners should be bridged through better understanding each other's needs. Accurately estimating the ratio between procurement and maintenance costs is needed from a whole life costing perspective.

This paper is a good reference for building designers, facility managers and maintenance staff of building services systems. It also offers reliability researchers references on special characteristics of building services systems.

The purpose of this paper is to formulate a model which not only determines minimum level of maintenance requirements but also satisfies expected reliability level.

A multi‐objective decision making (MODM) model has been developed by viewpoint of decreasing wastes and increasing system reliability. Wastes that have been minimized are maintenance requirements (i.e. labor, spare parts, reserve system and productive maintenance activities) and maintenance system reliability that has been maximized is a function of maintenance requirements. This paper proposed goal programming model for decision‐making aid and a real case in an existing Iranian automobile manufacturing company was studied.

Output of the proposed model was optimum level of maintenance requirements which satisfies the expected reliability level. For example, outputs of model for man hour approximately are the same as available maximum level and inspection, service and test and adjustment activities are not necessary 12 times a year for all the machineries.

This model is useful for managers because they could use that in any maintenance systems and it would ensure them in achieving minimum level of maintenance requirements and the expected reliability level.

Since lean concept has appeared, many works have been done on decreasing or even eliminating of waste such as extra inventory. Although these studies have not taken into account expected reliability seriously, this paper considers these two issues together.

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 modern helicopters are designed with maximum serviceability and long life expectancy to ensure minimum life cycle cost. The purpose of this paper is to present a framework to incorporate the customer requirements on reliability and maintainability (R&M) parameters into the design and development phase of a contemporary helicopter, and to discuss the way to capture operational data to establish and improve the R&M parameters to reduce life cycle cost.

From the analysis, it is established that the reliability and maintainability cost is the major contributor to the life cost. The significant reliability and maintainability parameters which influence R&M cost are identified from analysis. The operational and design data of a contemporary helicopter are collected, compiled and analyzed to establish and improve the reliability and maintainability parameters.

The process depicted in the paper is followed for a contemporary helicopter and substantial amount of life cycle cost reduction is observed with improvement of R&M parameters.

The benefits of this methodology not only reduce life cycle cost but also improve the availability/serviceability through less failure and less time for scheduled maintenance. The methodologies also provide the reliability trends indicating potential area for design improvement.

The proposed approach assists asset managers to reduce the life cycle costs through improvement of R&M parameters.

In many industrial environments, systems are required to perform a sequence of operations (or missions) with finite breaks between each operation. During these breaks, it may be advantageous to perform repair on some of the system’s components. However, it may be impossible to perform all desirable maintenance activities prior to the beginning of the next mission due to limitations on maintenance resources. In this paper, a mathematical programming framework is established for assisting decision‐makers in determining the optimal subset of maintenance activities to perform prior to beginning the next mission. This decision‐making process is referred to as selective maintenance. The selective maintenance models presented allow the decision‐maker to consider limitations on maintenance time and budget, as well as the reliability of the system. Selective maintenance is an open research area that is consistent with the modern industrial objective of performing more intelligent and efficient maintenance.

The demand of cement in India is expected to increase rapidly as the government has been giving immense boost to various housing facilities, infrastructure projects, road networks and railway corridors. One of the ways to meet this rise in the demand of cement is to increase the capacity utilization of the existing cement plants by improving their availability. The availability of a cement plant can be improved by avoiding failures and reducing maintenance time through reliability, availability and maintainability (RAM) analysis of its subsystems. The paper aims to discuss this issue.

The data related to time between failure (TBF) and time to repair (TTR) of all the critical subsystems of a cement plant were collected over a period of two years for carrying out RAM analysis. Trend test and serial correlation test were performed on TBF and TTR data to verify whether these data are independent and identically distributed or not. Afterwards, the authors use EasyFit 5.6 professional software to find best-fit distribution of TBF and TTR data and their parameters. The effectiveness of a preventive maintenance policy was evaluated by simulating the real and proposed systems.

The results of the analysis show that the raw mill and the coal mill are critical subsystems of a cement plant from a reliability point of view, whereas the kiln is a critical subsystem from an availability point of view. The analysis shows that the repair time of the cement mill should be reduced for improving the availability of the cement plant. The RAM analysis showed that the capacity of the case study company is 17 percent underutilized due to maintenance-related problems and 15 percent underutilized because of management-related problems.

The study exhibits the usage of RAM analysis in deciding preventive maintenance programs of several cement plant subsystems. Thus, it would serve as a reference for reliability and maintenance managers in deciding maintenance strategies of cement plants as well as in improving their capacity utilization.

The study exhibits the usage of RAM analysis in deciding preventive maintenance programs of several cement plant subsystems. Even more, using a simulation study, the authors show that preventive maintenance of the cement plant beyond a certain level can be disadvantageous as it leads to an increase in downtime and decrease in availability.

The purpose of this paper is to focus on finding the optimal maintenance interval and the minimum maintenance cost for redundant system, considering environment factors.

The authors propose a decision model with environment-based preventive maintenance for the repairable redundant system. Referring to the k-out-of-n model and Proportional Hazard Model, the reliability analysis is completed for the redundant system affected by internal and external issues. Meanwhile, the maintenance cost for the redundant system is divided into two categories: the fixed maintenance cost involving whole system replacement at the time of system failure, and the cost to replace failure components when the system still functions.

Upon the required reliability analysis, an optimal maintenance interval that minimizes the average maintenance cost per unit time is identified. The simulation results indicate that the optimal maintenance interval with consideration of environmental factors is significantly shorter than that without consideration of these factors, with the maintenance cost increase within 10 percent.

The redundant systems have widely been used in industries including the aero craft control system and warship power system. The model could be applied in the more real case considering the types of components and the operation environment, and help production managers better maintain machines by increasing the safety and reliability of the redundant model with the more frequent inspection.

Previous research of redundant system always focuses on internal degradation, while ignoring the reliability analysis for a redundant system with various multiple components under the influence of environment. However, this work could fill the theoretical gap, i.e. simultaneously consider both environmental and internal factors for a redundant system with non-homogeneous components. Meanwhile, the proposed superior model increases the reliability and safety of the k-out-of-n model with reasonable cost. Production managers could benefit a lot from this as well.

This study focuses on the application of reliability-centered maintenance (RCM) to a textile industry steam boiler. The study aims to demonstrate the development and application of RCM to a steam boiler used in the textile industry.

RCM is a structured process that develops maintenance activities needed on physical resources in their operational environment to realize their inherent reliability by logically incorporating an appropriate mixture of reactive, preventive, condition-based and proactive maintenance methods. A detailed analysis of the RCM approach is presented to develop preventive maintenance (PM) program and improve the reliability and availability of the steam boiler system.

The research reveals that the identification of PM tasks is a good indicator of the PM program's efficiency and can serve as an important maintenance-related downtime source. It is also discovered that the majority of maintenance programs that claim to be proactive are, in fact, reactive. This article also shows how RCM may be successfully implemented to any system, resulting in increased system reliability.

The paper focuses on a pilot study of the development and implementation of the RCM technique to a textile industry steam boiler. It is suggested that the developed RCM model can be applied to the entire plant.

The paper presents a comprehensive RCM model framework as well as an RCM decision framework, providing maintenance managers and engineers with a step-by-step approach to RCM implementation. The proposed framework is significant in that it may be utilized for both qualitative and quantitative analysis at the same time.

The purpose of this research is to calculate and enhance the cheese cheddar manufacturing plant efficiency under actual workplace conditions by measuring reliability, availability and maintainability (RAM) indices. The authors highlight how RAM analysis is important in determining periodic maintenance and in scheduling and managing the appropriate maintenance policy.

The current work is conducted using statistical approaches to evaluate failure and repair statistics. The RAM estimation was calculated on the basis of quantitative data obtained over a span of 32 months. Descriptive statistics, Pareto analysis, as well as the presumption of independence were ensured through trend and serial correlation tests. In addition, the reliability and maintainability of the cheddar cheese processing plant and its machines were calculated at various mission periods.

The primary goal of the implementation approach is to understand the fault patterns and the accurate quantitative assessment of the reliability and maintainability of the cheddar production plant. The findings revealed the essential aspects of the line, which need improvement by an appropriate maintenance program.

This study is intended to serve to highlight the RAM assessment and its impact on the performance of the real-time system. The benefit of the technique is the continual control of the manufacturing process by means of acceptable indexes, whose use corresponds to a continuous improvement process.

The paper seeks to ease the implementation of predictive maintenance policy in industry using the root cause analysis technique, and to compare the reliability and cost effectiveness of root cause based maintenance (RCBM) relative to conventional corrective maintenance (CM).

The system is modularized into its components and maintenance schedules are developed based on each component's individual degradation trends. The effectiveness of RCBM over CM is studied by analyzing system reliability patterns and total maintenance cost functions obtained through empirical cost models, accounting for yield and production loss, maintenance, replacement and catastrophic failure costs. Cost variations for various possible failure distribution parameter values (β, η) under the CM and RCBM policies are also obtained. The proposed methodology is tested in a real aircraft failures case study.

RCBM is generally more effective over CM in achieving timely maintenance at optimal cost (savings up to 65 percent) while keeping high system reliability, for a wide range of (β, η) values. However, CM could still be beneficial for a restricted range of large (β, η).

Industry should consider shifting from CM to adopt the proposed RCBM policy, which is proved to be more efficient in most cases. The implementation is not necessarily complex.

The effectiveness of RCBM over CM in terms of reliability and cost considerations is clearly illustrated. This paper justifies the need to shift from CM to RCBM, which brings us closer to a practical implementation of predictive maintenance. This work also serves as a simple and valuable guide to implementation for maintenance and operational managers in production industries.