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Most of the existing software reliability models assume time between failures to follow an exponential distribution. Develops a reliability growth model based on non‐homogeneous Poisson process with intensity function given by the power law, to predict the reliability of a software. Several authors have suggested the use of the non‐homogeneous Poisson process to assess the reliability growth of software and to predict their failure behaviour. Inference procedures considered by these authors have been Bayesian in nature. Uses an unbiased estimate of the failure rate for prediction. Compares the performance of this model with Bayes empirical‐Bayes models and a time series model. The model developed is realistic, easy to use, and gives a better prediction of reliability of a software.

The purpose of this paper is to provide maintenance personnel with a methodology for using masked field reliability data to determine the probability of each subassembly failure.

The paper compares an iterative maximum likelihood estimation method and a Bayesian methodology for handling masked data collected from 227 identical radar power supplies. The power supply consists of several subassemblies hereafter referred to as shop replaceable assemblies (SRAs).

The study examined two approaches for dealing with masking, an iterative maximum likelihood estimate procedure, IMLEP, and a Bayesian approach implemented with the application WinBUGS. It indicates that the performances of IMLEP and WinBUGS in estimating the parameters of the SRA distribution under no masking conditions are similar. IMLEP and WinBUGS also provide similar results under masking conditions. However, the study indicates that WinBUGS may perform better than IMLEP when the competing risk responsible for a failure represents a smaller total percentage of the total failures. Future study to confirm this conclusion by expanding the number of SRAs into which the item under study is organized is required.

If an item is considered to be comprised of various subassemblies and the failure of the first subassembly causes the item to fail, then the item is referred to as a series system in the literature. If the probability of a each subassembly failure is statistically independent then the item can be represented by a competing risk model and the probability distributions of the subassemblies can be ascertained from the item's failure data. When the item's cause of failure is not known, the data are referred to in the literature as being masked. Since competing risk theory requires a cause of failure and a time of failure, any masked data must be addressed in the competing risk model.

This study indicates that competing risk theory can be applied to the equipment field failure data to determine a SRA's probability of failure and thereby provide an efficient sequence of replacing suspect failed SRAs.

The analysis of masked failure data is an important area that has had only limited study in the literature due to the availability of failure data. This paper contributes to the research by providing the complete historical equipment usage data for the item under study gathered over a time frame of approximately seven years.

This study presents a lifecycle cost model considering multi-level burn-in for operationally unrepairable systems including assembly and warranty costs. A numerical method to obtain system reliability under component replacement during burn-in is also presented with derived error bounds.

The final system reliability after component and system burn-in is obtained and warranty costs are computed. On failure during operation, the system is replaced with another that undergoes an identical burn-in procedure. Cost behaviours for a small and large system are shown in a numerical example.

There are more cost savings when system burn-in is conducted for a large system whereas a strategy focusing on component burn-in only can also result in cost savings for small systems. In addition, a minimum system burn-in duration is required before cost savings are achieved for these operationally unrepairable systems.

The operationally unrepairable system is a niche class of systems which small satellites fall under and no such study has been conducted before. The authors present a different approach towards the testing of small satellites for a constellation mission.

The purpose of this paper is to present a novel modeling approach that combines a balanced systems engineering design model with a geospatial model to explore the complex interactions between natural hazards and engineered systems.

The approach taken in this work was to assemble a combined systems engineering design/geospatial model and interface it with a physics‐based hazard model to assess how to visualize the coupling of potential hazard effects from the physical domain into the functional/requirements domain.

It was demonstrated that it is possible to combine the two models and apply them to realistic hazard cases. A number of potential benefits are described and made possible by this approach including the generation of systems‐level damage assessments, the potential reduction of geo‐information data collection requirements, the incorporation of socio‐technical elements, the generation of functional templates, and the creation of a superior mitigation framework.

This approach offers a way to better understand natural hazard impacts on built systems, systemic effects of hazards, functional interdependencies between infrastructural elements, and a practical means to reduce geo‐information collection requirements.

The work is original in that it is the first time a balanced systems engineering design model has been made spatially aware and used to explore the impact of natural disasters on human systems. This work is valuable in that it directly addresses the shortcomings of spatial‐only approaches and could be used in data‐poor regions of the world.

Several inferential procedures are advocated in the literature. The most commonly used techniques are the frequentist and the Bayesian inferential procedures. Bayesian methods afford inferences based on small data sets and are especially useful in studies with limited data availability. Bayesian approaches also help incorporate prior knowledge, especially subjective knowledge, into predictions. Considering the increasing difficulty in data acquisition, the application of Bayesian techniques can be hugely beneficial to managers, especially in analysing limited data situations like a study of expert opinion. Another factor constraining the broader application of Bayesian statistics in business was computational power requirements and the availability of appropriate analytical tools. However, with the increase in computational power, connectivity and the development of appropriate software programmes, Bayesian applications have become more attractive. This chapter attempts to unravel the applications of the Bayesian inferential procedure in marketing management.

This research aims to examine the relationship between information security strategy and organization performance, with organizational capabilities as important factors influencing successful implementation of information security strategy and organization performance.

Based on existing literature in strategic management and information security, a theoretical model was proposed and validated. A self‐administered survey instrument was developed to collect empirical data. Structural equation modeling was used to test hypotheses and to fit the theoretical model.

Evidence suggests that organizational capabilities, encompassing the ability to develop high‐quality situational awareness of the current and future threat environment, the ability to possess appropriate means, and the ability to orchestrate the means to respond to information security threats, are positively associated with effective implementation of information security strategy, which in turn positively affects organization performance. However, there is no significant relationship between decision making and information security strategy implementation success.

The study provides a starting point for further research on the role of decision‐making in information security.

Findings are expected to yield practical value for business leaders in understanding the viable predisposition of organizational capabilities in the context of information security, thus enabling firms to focus on acquiring the ones indispensable for improving organization performance.

This study provides the body of knowledge with an empirical analysis of organization's information security capabilities as an aggregation of sense making, decision‐making, asset availability, and operations management constructs.

India's textile industries play a vital role in the Indian economy. These industries consume the highest thermal energy (steam power). The demand of the steam in process industries is increasing rapidly, and this demand can be met by increasing the capacity utilization of steam boilers. The purpose of this paper is to present a new approach for reliability analysis by expert judgment method.

A lack of adequate life data is one of the biggest challenge in the reliability analysis of mechanical systems. This research provides an expert judgment approach for assessing the boiler's reliability characteristics. For this purpose, opinions of experts on time to failure and time to repair data were elicited in the form of statistical distributions. In this work, reliability analysis of the boiler system is carried out by expert judgment method and by using best-fit failure model. The system reliability along with preventive maintenance intervals of all components is also evaluated.

It is observed that the reliability analysis results obtained by expert judgment method and best-fit failure model method indicate that there are no significant differences. Therefore, in case when insufficient data are available, the expert judgment method can be effectively used. The analysis shows that the feedwater tank, feedwater pump, supply water temperature sensor, strainer, return water temperature sensor, condensate filter, mechanical dust collector, coal crusher and fusible plug are identified as critical components from a reliability perspective, and preventive maintenance strategy is suggested for these components.

In this research paper, a system reliability model by the expert judgment method is developed, and it can be effectively used where insufficient failure data are available. This paper is useful for the comparative evaluation of reliability characteristics of a boiler system by expert judgment method and best-fit failure model method.

This study aims to conduct the aircraft electrical wiring interconnection system (EWIS) safety risk assessment process abundantly and hierarchically and establish the assessment index system considering the weights and interrelationships of different levels of indices.

Due to the failure of EWIS being multifactorial, hidden and diverse, this paper divides the factors influencing the failure of EWIS into 3 primary indices, 13 secondary indices and 38 tertiary indices. Taking open circuit failure (OCF) and short circuit failure (SCF) as examples, calculate the weights of assessment indices based on the triangular fuzzy number analytic hierarchy process (TFNAHP) and triangular fuzzy number decision-making trial and evaluation laboratory (TFNDEMATEL). The cloud model (CM) divides the risk levels and obtains the safety risk assessment results. The comparative analyses of different weight calculation methods, different failure modes and different aircraft EWIS zones verify the effectiveness and practicability of the proposed method.

The results show that the proposed method aligns more with the actual situation than other methods. Also, the results identify key focus objects in EWIS safety risk assessment, such as the surrounding environmental factors among the primary indices having the most significant influence on OCF and SCF, the risk level of SCF being higher than that of OCF, etc.

This paper proposes a safety risk assessment index system for aircraft EWIS based on the cable parameters, surrounding environmental factors, installation and protection methods. The weight assignment is added to the assessment index system, and the safety risk assessment model is constructed by combining TFNAHP, TFNDEMATEL and CM.

With the merit of Bayes’ theorem, this paper proposes an integrated Bayesian approach for reliability assessment during equipment development. By considering the prior information, this approach can provide useful information to use for decision‐making. A numerical example is given to illustrate the applicability of the proposed approach. It is believed that the proposed approach would be helpful for the project manager to focus attention on the key problems to resolve them early so as to ensure the greatest probability for project success.

Although there has been an increase in the application of a variety of robust technologies and systems, the oil and gas sector relies on project managers’ soft skills for success because of their vital role. Therefore, this study aims to explore the profound influence of project managers’ soft communication skills on successful risk management within Libya’s oil and gas projects.

A review of relevant literature and a quantitative approach through the administration of a questionnaire were used to determine factors impacting risk management implementation related to managerial communication skills. A total of 246 valid responses were received from the oil and gas companies in Tripoli, Libya. Partial least squares structural equation modelling was used to examine the direct and moderating relationship drawn by the hypotheses.

The findings suggest that managerial soft skills may be used to improve continuous risk management processes and intra-project communication. It was found that the experience is strengthening the positive relationship between written communication soft skills and project risk management implementation among Libyan oil and gas construction projects.

This study defines project managers’ soft communication skills and analyzes project managers’ soft communication skills with the role of experience as a moderator. This paper presents a valuable contribution by offering original insights tailored explicitly to the Libyan context. The information presented in this paper is relevant to project managers operating within the oil and gas industry. It also offers a novel approach to risk management in the Libyan oil and gas industry that can improve project efficiency and effectiveness.