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Degraded failures and sudden critical failures are quite prevalent in industries. Degradation processes commonly belong to Weibull family and critical failures are found to follow exponential distribution. Therefore, it becomes important to carry out reliability and availability analysis of such systems. From the reported literature, it is learnt that models are available for the situations where the degraded failures as well as critical failures follow exponential distribution. The purpose of this paper is to present models suitable for reliability and availability analysis of systems where the degradation process follows Weibull distribution and critical failures follow exponential distribution.

The research uses Semi-Markov modeling using the approach of method of stages which is suitable when the failure processes follow Weibull distribution. The paper considers various states of the system and uses state transition diagram to present the transition of the system among good state, degraded state and failed state. Method of stages is used to convert the semi-Markov model to Markov model. The number of stages calculated in Method of stages is usually not an integer value which needs to be round off. Method of stages thus suffers from the rounding off error. A unique approach is proposed to arrive at failure rates to reduce the error in method of stages. Periodic inspection and repairs of systems are commonly followed in industries to take care of system degradation. This paper presents models to carry out reliability and availability analysis of the systems including the case where degraded failures can be arrested by appropriate inspection and repair.

The proposed method for estimating the degraded failure rate can be used to reduce the error in method of stages. The models and the methodology are suitable for reliability and availability analysis of systems involving degradation which is very common in systems involving moving parts. These models are very suitable in accurately estimating the system reliability and availability which is very important in industry. The models conveniently cover the cases of degraded systems for which the model proposed by Hokstad and Frovig is not suitable.

The models developed consider the systems where the repair phenomenon follows exponential and the failure mechanism follows Weibull with shape parameter greater than 1.

These models can be suitably used to deal with reliability and availability analysis of systems where the degradation process is non-exponential. Thus, the models can be practically used to meet the industrial requirement of accurately estimating the reliability and availability of degradable systems.

A unique approach is presented in this paper for estimating degraded failure rate in the method of stages which reduces the rounding error. The models presented for reliability and availability analyses can deal with degradable systems where the degradation process follows Weibull distribution, which is not possible with the model presented by Hokstad and Frovig.

The purpose of this paper is to propose a novel hybrid approach called as Markov System Dynamics (MSD) approach which combines the Markov approach with system dynamics (SD) simulation approach for availability modeling and to study the dynamic behavior of repairable systems.

In the proposed approach the identification of the single unit repairable system all possible states has been performed by using the Markov approach. The remaining stages of traditional Markov analysis are highly mathematically intensive. The present work proposes a hybrid approach called as MSD approach which combines the Markov approach with SD simulation approach to overcome some of the limitations of Markov process in a simple and efficient way for availability modeling and to study the dynamic behavior of this system.

The proposed framework is illustrated for a single unit repairable system. The worked out example shows the steady state point and also it gives the point, interval and steady state availabilities and also the dynamic behavior of the system. However this methodology can be extended easily for more complex multi-state maintainable systems. The results of the simulation when compared with that obtained by traditional Markov analysis clearly validate the proposed approach as an alternative approach for availability modeling of repairable systems.

In many practical situations we require to find the time at which our system reaches steady state conditions for planning maintenance activities. The proposed MSD method in this paper is capable of finding this steady state point very easily.

The proposed approach clearly indicates the time at which the system reaches its steady state and calculates the point, interval availabilities for planning maintenance activities. The different parties, i.e., engineers and machine operators, can jointly work with this model in order to understand the dynamic behavior of repairable systems.

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.

Urinary incontinence (UI) is a common chronic health condition, a problem specifically among elderly women that impacts quality of life negatively. However, UI is usually viewed as likely result of old age, and as such is generally not evaluated or even managed appropriately. Many treatments are available to manage incontinence, such as bladder training and numerous surgical procedures such as Burch colposuspension and Sling for UI which have high success rates. The purpose of this paper is to analyze which of these popular surgical procedures for UI is effective.

This research employs randomized, prospective studies to obtain robust cost and utility data used in the Markov chain decision model for examining which of these surgical interventions is more effective in treating women with stress UI based on two measures: number of quality adjusted life years (QALY) and cost per QALY. Treeage Pro Healthcare software was employed in Markov decision analysis.

Results showed the Sling procedure is a more effective surgical intervention than the Burch. However, if a utility greater than certain utility value, for which both procedures are equally effective, is assigned to persistent incontinence, the Burch procedure is more effective than the Sling procedure.

This paper demonstrates the efficacy of a Markov chain decision modeling approach to study the comparative effectiveness analysis of available treatments for patients with UI, an important public health issue, widely prevalent among elderly women in developed and developing countries. This research also improves upon other analyses using a Markov chain decision modeling process to analyze various strategies for treating UI.

Gives the background to human resource planning (HRP) and argues that HRP tools are still an essential management requirement. Looks, therefore, to HRP tools that are not so mathematically complex as to be of little use to the average practitioner. Provides an approach which harnesses modern spreadsheet technology to implement the previously esoteric tools of analysis ‐ “holonic modelling”. Holonic modelling recognizes that computer power and the flexibility of software packages allow problems to be structured in a flexible manner. Goes on to demonstrate the use of holonic modelling in the context of HRP.

The purpose of this paper is to present an original model, and one of practical use, for a contractor's internal analysis of the likelihood of late and incomplete payments, in an uncertain payment environment. Payments typically dominate the thinking of a contractor and the way a contractor operates. The model applies equally to subcontractors, suppliers and consultants.

The model is based on Markov chains, specially adapted to the problem, where the states are defined as the period of time by which the payment is overdue. In addition, there are special states corresponding to claims that have been paid, and those that need resolution. Transitions between states reflect the payment characteristics on the project (which itself depends on the type of project and the owner‐contractor relationship).

Real project data confirm the validity of the model. Output from the model can be shown to agree with actual contractor payment data. The output is in terms of probability of payment by a certain date, and mean time to payment for amounts owing. Such information assists the contractor in its financial management practices.

The paper gives a summary approach for contractors. A strength and paradox of the model is its simplicity in usage, yet it overlies hidden more extensive mathematics, which might generally not be known or is necessary to be known to contractors. The model analysis feeds into the contractor's cash flow calculations, overall project risk analysis and accounting procedures.

The paper represents an original contribution to the modelling and analysis of contractor payments.

With every passing day, the center of gravity for air traffic for the Middle East and Turkey is shifting toward becoming a center for airway transport, maintenance, repair, overhaul (MRO) and transfer. The MRO sector is gaining importance because of this increase in Turkey. The purpose of this study is to examine the future employability of the graduates receiving civil aviation maintenance training in Turkey.

The paper uses past seven years’ data about maintenance personnel of Turkey. It includes all-level students, recently working personnel and retired personnel of each year. Regression analysis and Markov analysis were used to show the prediction of aviation maintenance personnel.

The paper provides quantitative results about employability of maintenance personnel under the real numbers of alumni and working and retired personnel in Turkey. The results show that the number of graduates will be greater than the number of staff members in certifying categories in 2018. Presently, Turkey meets the employment expected, but in the future, aviation maintenance personnel number is rising, and there will be an excess number of graduates left over in Turkey.

Because of the chosen region, Turkey, the research results may lack generalizability. Therefore, researchers are encouraged to conduct analysis for other countries which have an important role in aviation.

The paper includes implications for the government maintenance personnel policy and educational policy for managing all types of maintenance personnel in Turkey.

This kind of personnel needs analysis has not been done before, and this is the originality of this paper. It will in turn lead to an analysis of planning for allocation of maintenance staff and alumni. The authors collected all official numbers about maintenance personnel from Turkish Student Selection and Placement Center of Turkey, Turkish Technic and Turkish Civil Aviation Reports.

This paper seeks to propose a methodology based on Petri nets to evaluate the reliability parameters of a screening system in paper industry. The effects of failures and courses of action on the system performance have also been investigated.

Generalized stochastic Petri nets (GSPN), a class of Petri nets, has been used to model the interactions amongst the active/standby units of the system; and Markovian approach has been used to evaluate the reliability parameters. The data related to equipments' operational behavior were collected, processed and quantified. Using the data, reliability analysis of system in the long run conditions has been carried out. The sensitivity analysis has been performed to study the effect of failure/repair rates of each unit of the system on system performance.

The methodology adopted in this paper provides a better understanding on the behavior of the system through its graphical representation. The reachability graph generated with Petri net model helps to identify the state space evolution of the system.

Reliability analysis of a screening system of the paper industry presented in this paper will help management in deciding upon the maintenance strategy to be adopted with the objective of improving the performance of the system and consequently reducing the operational and maintenance costs.

The purpose of the study is to use web serer logs in analyzing the changes of user behavior in reading online news, in terms of desktop and mobile users. Advances in mobile technology and social media have paved the way for online news consumption to evolve. There is an absence of research into the changes of user behavior in terms of desktop versus mobile users, particularly by analyzing the server logs.

In this paper, the authors investigate the evolution of user behavior using logs from the Malaysian newspaper Berita Harian Online in April 2012 and April 2017. Web usage mining techniques were used for pre-processing the logs and identifying user sessions. A Markov model is used to analyze navigation flows, and association rule mining is used to analyze user behavior within sessions.

It was found that page accesses have increased tremendously, particularly from Android phones, and about half of the requests in 2017 are referred from Facebook. Navigation flow between the main page, articles and section pages has changed from 2012 to 2017; while most users started navigation with the main page in 2012, readers often started with an article in 2017. Based on association rules, National and Sports are the most frequent section pages in 2012 and 2017 for desktop and mobile. However, based on the lift and conviction, these two sections are not read together in the same session as frequently as might be expected. Other less popular items have higher probability of being read together in a session.

The localized data set is from Berita Harian Online; although unique to this particular newspaper, the findings and the methodology for investigating user behavior can be applied to other online news. On another note, the data set could be extended to be more than a month. Although initially data for the year 2012 was collected, unfortunately only the data for April 2012 is complete. Other months have missing days. Therefore, to make an impartial comparison for the evolution of user behavior in five years, the Web server logs for April 2017 were used.

The user behavior in 2012 and 2017 was compared using association rules and Markov flow. Different from existing studies analyzing online newspaper Web server logs, this paper uniquely investigates changes in user behavior as a result of mobile phones becoming a mainstream technology for accessing the Web.

The reliability and maintainability of tunnel infrastructure and systems is an important factor in assuring normal operation of a tunnel. Evaluating availability of a large‐scale tunnel that includes civil, electrical, mechanical and electronic systems is a difficult task. The purpose of this paper is to present a methodology for performing such assessments, featuring the use of the Markov model.

The methodology involves application of failure mode, effect and criticality analysis (FMECA), state space diagram construction, formulation of state space equations, and development of transitional matrices. It also involves transformation of multi‐state models into two‐state models (each comprises of an “up” state and a “down” state) through the use of the frequency and duration method for determining the failure and repair rates, as well as the mean‐time‐between‐failures (MTBF) of the entire tunnel. By using the proposed bottom‐up approach, a MTBF tree linking the availability measures of individual equipment with those of sub‐systems, and ultimately the whole tunnel can be developed.

The tunnel availability measures obtained by this analysis can be used in making comparisons between different tunnel designs so as to determine the value for money of various options. Furthermore, weaknesses in a tunnel design can be identified in the analysis. The information obtained from this method can also be used to evaluate adequacy, security and maintainability of a tunnel.

The reliability and maintainability of tunnel infrastructure and systems are crucial factors for ensuring safety of tunnel operation. Unsafe conditions will cause closure of a tunnel. Efforts to improve availability of a tunnel often increase the tunnel's construction cost. Due to the complexity of tunnel systems, it is difficult to compare different tunnel designs, and trade‐off analyses to strike a balance between target availability and construction cost of a tunnel design are seldom performed. This paper presents a systematic methodology to address these issues. This methodology allows tunnel management to evaluate the adequacy, security and maintainability of a tunnel so that design weaknesses can be identified and the value of design improvements can be determined. The methodology can also be used to evaluate designs of other complex systems such as power generation or petrochemical processing plants.

A worked example demonstrating the application of the proposed methodology is presented in this paper.