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The purpose of this paper is to propose a state dependent stochastic Markov model for availability analysis of process plant instead of traditional time dependent model.

The traditional concepts of system performance measurement and reliability (namely, binary; two-state concepts) are observed to be inadequate to characterize performance of complex system components. Availability analysis considering an intermediate state, such as a degraded state, provides a better alternative mechanism for system performance mapping. The availability model provides a better assessment of failure and repair characteristics for equipment in the sub-system and its overall performance. In addition to availability analysis, this paper also discusses the preventive maintenance (PM) program to achieve target availability. In this model, the degraded state is considered as a PM state. Using Markov analysis the optimum maintenance interval is determined.

Markov process provides an easier way to measure the performance of the process facility. This study also revealed that the maintenance interval has a major influence in the availability of a process facility as well as in maintaining target availability. The developed model is also applicable to the varying target availability as well as having the capability to handle even the reconfigured process systems.

Considering the degraded state as an operative state, a higher availability of the plant is predicted. The consideration of the degraded state of the system makes the availability estimation more realistic and acceptable. Availability quantification, target availability allocation and a PM model are exemplified in a sub-system of an liquefied natural gas facility.

The unique features of the present study are; Markov modeling approach integrating availability and PM; optimum PM interval determination of stochastically degrading components based on target availability; consideration of three-state systems; and consideration of increasing failure rates.

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 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 study the evolution of a system stationary availability and determine the optimal preventive maintenance period, which maximises it in a context where preventive and corrective maintenance actions are imperfect and have non‐negligible durations.

The quasi‐renewal process approach and a (p, q) rule are respectively used to model corrective and preventive maintenance. Considering the durations of the preventive and corrective maintenance actions as well as their respective efficiency extents, a mathematical model and a numerical algorithm are developed in order to compute the system stationary availability.

It has been proven that for any given situation regarding the system, the repair and preventive maintenance efficiency extents, and the downtime durations for preventive and corrective maintenance, there is necessarily a finite optimal period T* of preventive maintenance which maximises the system stationary availability. A sufficient condition for the uniqueness of the optimal solution has also been derived. Numerical examples illustrated how preventive and corrective maintenance efficiency extents affect simultaneously the system optimal availability.

The study considers a general industrial framework where preventive and corrective maintenance actions are imperfect. In fact, neither the best‐qualified technicians nor the most suitable tools or spare parts are found to carry out maintenance actions. In such a context for a large variety of technical systems, when implementing preventive maintenance policies one should take into account the efficiency extents of maintenance actions as well as their durations in order to evaluate and optimise the system availability. The paper provides maintenance managers with a decision model allowing not only the computation and optimisation of system availability, but also the investigation of how preventive and corrective maintenance efficiency extents affect simultaneously the system optimal availability. The proposed model also allows one to find to what extent corrective actions ineffectiveness should be tolerated without having an important availability loss.

The paper proposes a modified formulation of the quasi‐renewal process taking into account the non‐negligible duration of corrective maintenance actions and periodic preventive maintenance. A new numerical algorithm is also developed in this context to compute the quasi‐renewal function that it is impossible to find in closed form. This allowed the computation and optimisation of system stationary availability.

The purpose of this paper is to offer an integrated approach for understanding the relations among the theoretical and operational antecedents of consumer involvement in the context of financial products. The theoretical antecedents of involvement have been conceptualized as the consumer's personal profile, purchase situation, and target product; the operational antecedent includes the purchase availability manipulation.

The research is based on a field study among private customers of a leading financial institute and on two experimental designs within lab settings. The independent variables include the theoretical and operational antecedents and the dependent measure comprises the involvement measure.

The findings emphasize that the theoretical antecedents constitute an effective manipulation of involvement, whereas the operational antecedent has only limited effect.

Financial managers should consider the type of financial service, distribution channel, social context and advertising medium, in conjunction with the consumer's profile, to increase the overall involvement.

The research provides a new view at the way predictions of involvement are formed within the financial context. This view is enabled by including the antecedents of product involvement along with the manipulation of product availability. When these components are considered jointly, a richer set of predictions can be offered than previously conceptualized. To this end, the research calls for a more comprehensive approach for manipulating involvement that bases its activation on the theoretical antecedents.

The purpose of this paper is to present a methodology for forecasting the availability off-highway trucks used in a fleet for large transport operations of ore and sterile rock from an open pit mine.

This methodology enables the estimation of the number of hours of preventive and corrective maintenance required, which are used to predict truck availability. The authors used historical data for the maintenance strategy based on the hours of operation.

These data are statistically analyzed to obtain the key quantities and statistical models required to project availability and to develop equipment replacement plans.

A methodology for forecasting availability to assets in open pit mining industry was implemented.

The purpose of this paper is to propose a novel resource availability assessment for supply chain (SC) configuration. This approach involves understanding both local resource availability and the demand-side implications of supplying global/regional markets as part of a more holistic SC design activity that incorporates local environmental factors.

The proposed framework was derived from literature analysis, bridging relevant literature domains – natural capital theory, industrial ecology and SC configuration – in order to develop design rules for future resource-constrained industrial systems. In order to test the proposed framework, an exploratory case study, based on secondary data, was conducted.

Research findings suggest that this approach might better identify relationships and vulnerabilities between natural resource availability and the viability of regional/global SCs. The research suggests that natural resource availability depends upon three elements – local resource consumption, global resource demand and external environmental factors.

The framework has two main limitations. The current work is focussed on a single industry case study used to exemplify the approach. Second, the framework does not consider other possible industries, which might enter or leave the specific location during the company’s operation. Furthermore, no assessment was made of the migration of populations within the area.

For practitioners, such as those in the agri-food sector, the resource availability assessment framework informs SC configuration design. For policymakers, the research aims to provide policy guidelines, which can help to improve water-saving strategies for a particular region. At a broader societal level, the research raises awareness of resource scarcity amongst industrial players and the wider public.

A resource availability assessment framework has been proposed, suggesting that the dynamics of both global and local resource demand, in conjunction with changing local environmental factors, can over time significantly deteriorate a firm’s natural resource impact on the local environment. Thus, the framework seeks to deliver mechanisms to evaluate potential vulnerabilities and solutions available to firms using a more proactive SC design method and to apply reconfiguration processes that account for natural resources, based primarily on network and resource attributes.

The purpose of this paper is to explore the impact of the Kijima Type II imperfect repair model on the availability of repairable systems (RS). Since many individuals are interested in measuring the extent to which the system will be available after it has been run for a long time, the specific interest in this study is in the steady-state (limiting) availability behavior of such systems. Furthermore, the authors study the impact of age-based preventive maintenance (PM) on the RS performance.

Because of the complexity of the underlying assumptions of the Kijima Type II model, the authors use simulation modeling to estimate the system availability. Based on preliminary simulation results, the availability function achieves a steady-state value greater than zero. The system steady-state availability is then estimated from the simulation output by computing the average of the availability estimates beyond the initial transient period. Next, the authors develop a meta-model to convert the system reliability and maintainability parameters into the coefficients of the limiting availability estimate without the simulation effort. Using a circumscribed central composite experimental design, the authors confirm the accuracy of the meta-model.

The results show that the meta-model is robust, and provides good estimates of the system limiting availability. Also, the authors find that when using a Kijima Type II model for a system repair process, age-based PM can improve the steady-state availability value. Therefore, an optimal age-based PM policy that maximizes the system’s steady-state availability can be identified.

In practice, it is important to study the system steady-state availability because many individuals, i.e. engineers, are more interested in measuring the extent to which the system will be available after it has been run for a long time. Therefore, this study represents a significant addition to the body of knowledge related to virtual age modeling, in that it incorporates a Kijima type II model and considers system steady-state availability.

The purpose of this paper is to provide a basis for the construction professionals and stakeholders to understand the critical factors influencing resource availability in a post‐disaster situation. The study reported in this paper is part of ongoing research concerned with developing a methodology to improve the outcomes of resource availability for projects in post‐disaster environments. This study attempts to address the following questions: what factors impinge upon the availability of resources in a disaster recovery project and what are the common resource availability determinants across different recovery environments?

The method of analysis in this investigation is a comparative case study. The researchers took part in disaster field trips to Indonesia, China and Australia during their recovery from natural disasters. By using case studies and a triangulation method, critical factors that affected resource availability in the three examined countries were identified and compared.

A comparative analysis shows that specific cultural elements, the socio‐economic environment and the political agenda in the three countries influenced their resourcing problems and the solutions they adopted. Despite different resourcing approaches in the three cases, competence of construction professionals, and government response and intervention were identified as common determinants to resourcing disaster recovery projects.

The research findings contribute to the project management methodology to post‐disaster reconstruction.

From this research, decision makers and construction practitioners can have a clearer direction for improving their resourcing effort in a post‐disaster situation. This study provides a basis for the construction professionals and stakeholders to understand the critical factors influencing resource availability in a post‐disaster situation, with a view to enhancing their capability of managing disaster recovery projects.

A comparative analysis of three cases provides a multi‐perspective view of the resourcing issues in a post‐disaster situation. As many problems are faced in disaster recovery projects, resource availability intrinsically links to chronic conditions of vulnerability in existence in the broader social system prior to a disaster. The five aspects of resourcing discussed in the paper show the key areas of recovery planning in relation to resource availability.

In large and complex disaster recovery operations, the availability of resources is bound to be limited. Identified resourcing problems are likely to be universal and can be anticipated and pre‐planned for, irrespective of the environment when a disaster happens. The paper provides a basis for the construction professionals and stakeholders to understand the critical factors influencing resource availability in a post‐disaster situation.

The purpose of this paper is to present the technique for evaluating the performance of a condensate system of a coal-based thermal power plant situated in the northern part of India. The data which used for system availability evaluation are not precise and are uncertain and, further, collected from concerned power plant history sheets and from discussion through plant personnel.

In the proposed model, traditional Markov birth-death process using a probabilistic approach is used to analyze the performance of a complex repairable condensate system of power plant up to a desired degree of accuracy. This approach has been demonstrated by breaking the condensate system into six subsystems arranged in series with two feasible states, namely, working and failed, labeled in a transition diagram and modeled as a Markov process, using Chapman–Kolmogorov equations, which are used for development of a probabilistic stochastic model for availability analysis in a more effecting manner, considering some suitable assumptions.

This study of analysis of reliability and availability can help in increasing the plant production and performance. The analysis is done with the help of availability matrices, which are developed using different combinations of failures and repair rates of all subsystems. To achieve the goal of maximum power generation, it is required to run the various subsystem of the concerned system of plant, failure free for a long duration. Therefore, the present approach may be a more powerful analysis tool to access the performance of all subsystems of a condensate system in terms of availability level achieved in availability matrices. The results of present study are found to be highly beneficial to the plant management for making maintenance decisions.

The present paper suggests a suitable technique for stochastic modeling and availability evaluation of an industrial system using Markovian approach and drawing a transition diagram to represent the operational behavior of the system. The present methodology includes the advantage of the ability to model and develop a more complex industrial system and helps in improving the performance and handling the uncertainties and possibilities of an industrial system.