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This paper aims to evaluate a virtual training environment for testing UK gas pipeline emergency response plans.

Interviews, observations and desk research were used to identify current methods for testing plans. A virtual training environment was developed and evaluated with industry experts by using participatory design techniques. Key themes relating to both the current methods for testing plans and for a virtual training environment were identified using thematic analysis.

Improved training performance, remote participation and evidence of decision testing are benefits a virtual training environment can bring to current practice. It is suggested that a virtual training environment can enhance, rather than replace, the current process of testing emergency response plans.

Analysis of the virtual training environment being used to test plans in a live context would give further ecological validity to the findings. A study of the prototype used to test plans for incidents involving sectors outside the gas industry would further validate the findings.

The application of a virtual training environment to facilitate testing plans and the decision-making processes for major incidents involving high-pressure gas pipelines and storage sites is yet to be documented. This paper contributes to the literature by documenting the decision-making process and evaluation of a virtual training environment for testing plans in this context.

This paper considers a series system consisting of n different components having unknown and variable failure rates, where the lifetime of components follow exponential distribution having non-constant failure rates. Moreover, the failure rates are bounded by above and are dependent on environmental factors such as temperature, pressure, through linear relationship. The purpose of this paper is to design a component reliability test plan for such a series system with an unknown variable failure rate.

The reliability of the system is estimated with the help of the unbiased estimator of failure rate. The testing procedure is stopped when a fixed number of failures occur for each component.

An optimal reliability test plan is designed and the resultant non-linear integer optimization problem is formulated satisfying the constraints of producer’s and consumer’s risks. The obtained results are compared with the results available in the literature. Some examples are considered to illustrate the approach.

It is observed that use of prior information in the form of an upper bound and incorporation of environmental factors have the advantage of savings in the total testing cost.

This paper aims to propose a methodology for planning of a truncated sequential probability ratio test (SPRT) in which two systems with exponentially distributed times between failures (TBFs) are compared. The study is concerned with tests with arbitrary probabilities of I‐ and II‐type errors.

The study methodology, based on the proposed optimality criteria for these tests, permitted comparison of different modes of truncation and obviated the drawbacks of discreteness and multidimensionality of their characteristics.

The solution permits planning of a heavily‐truncated test with an average sample number exceeding its counterpart for the optimal (non‐truncated) test by at most a specified percentage. Relationships are outlined for optimal selection of the truncated test boundaries. So are optimality estimation criteria for the constructed test. The superiority of the SPRTs, truncated by the proposed methodology, over their counterparts, processed according to current practices, is demonstrated.

The solution refers to the case where the compared systems have exponentially distributed TBFs (or times to failure (TTFs) for non‐repairable cases).

The proposed algorithm and relationships for planning the tests in question can be used by developers of tests for reliability. A planning example from the semiconductor industry is given.

This paper presents a novel approach to planning of truncated SPRTs with arbitrary probabilities of I‐ and II‐type errors. The methodology is also applicable for truncated binomial SPRTs.

While previous health-care-related hybridity research has focused on macro- and micro-level investigations, this paper aims to study hybridization at the organizational level, with a specific focus on decision-making. The authors investigate how new politico-economic expectations toward a university hospital as a hybrid organization become internalized via organizational decision-making, resulting in the establishment of a new business collaboration and innovation-oriented unit.

The authors employed a social systems theoretical framework to explore organizational decision-making processes involved in the establishment of the new hybrid hospital unit. Drawing on 15 interviews and nine organizational documents, the authors describe and analyze three decision-making cycles using the concepts of complexity, decision and justification.

The findings reveal the challenging nature of decision-making during hybridization, as decisions regarding unprecedented organizational structures and activities cannot be justified by traditional decision premises. The authors show that decision-makers use a combination of novel justification strategies, namely, justification by problems, by examples and by obligations, to legitimize decisions oriented at non-traditional activities. Further, the analysis reveals how expectations of several societal systems, i.e. health care, education, science, law, economy and politics, are considered in decision-making taking place in hybrid organizations.

The study draws attention to the complexity of decision-making in a hybrid context and highlights the role of justification strategies in partially reducing complexity by concealing the paradoxical nature of decision-making and ensuring the credibility of resulting decisions. Also, the study presents a move beyond the dualism inherent in many previous hybridity studies by illustrating the involvement of several societal systems in hybridization.

To design an optimal accelerated degradation test (ADT) plan for light emitting diodes (LEDs).

This paper presents a method for the optimum planning of ADTs. The method is applied to the design of an optimal plan for LEDs. An analytical method is developed for obtaining the optimal allocations of test units to minimize the variance of the transformed life estimation at the use stress level; a simulation method is used to help select the optimal test plan and evaluate the test plans' properties. Optimal stress levels, and optimal allocations of test units to the stress levels are determined to minimize the mean squared error (MSE) of the estimated mean life of LEDs at the use stress level.

Different test plans result in different accuracy. The optimal test plan provides the most efficient use of test resources.

This paper focuses on designing an optimal plan using two test stress levels. Future research may extend to multiple stress levels.

With increasing emphasis on reliability in industry, products are made more robust, and few failures are observed in a reasonable test period. Therefore, assessing product reliability using ADTs becomes very useful. This paper fulfills the need to scientifically design plans for these tests to provide more accurate estimates of the designed‐in and manufactured reliability for the same amount of test resources.

The methodologies developed in this paper can be used for other ADTs. This enables reliability and test engineers to get the most efficient use of their test resources.

Discusses the formulation of a business recovery plan. As a starting point, presents the business recovery timeline model. Gives a framework of components to be considered in a business continuity project planning process, i.e. a risk reduction programme.

There is a prevailing assumption in the research literature that disaster exercises produce a wide variety of benefits that promote effective emergency management. Unfortunately, there are few studies available that confirm this assumption. This paper reviews the role of exercises in disaster management and places them within the context of preparedness activities. Within this context, the links among planning, training and exercising are explicated. The potential benefits of exercises are reviewed and hypotheses generated that link exercise experiences with emergency responders’ perceptions of planning adequacy, training adequacy, teamwork, response network effectiveness, equipment adequacy and job risk. The effects of two exercises – one dealing with hazardous materials and one with medical mass casualties – are examined using a quasi‐experimental research design. The subjects were professional firefighters. Results indicated that successful exercises can enhance perceptions of teamwork, training adequacy, response network effectiveness, job risk, and equipment adequacy. The link between exercise participation and perception of planning adequacy was found to be equivocal.

Planning an accelerated life test (ALT) for a product is an important task for reliability practitioners. Traditional methods to create an optimal design of an ALT are often computationally burdensome and numerically difficult. In this paper, the authors introduce a practical method to find an optimal design of experiments for ALTs by using simulation and empirical model building.

Instead of developing the Fisher information matrix-based objective function and analytic optimization, the authors suggest “experiments for experiments” approach to create optimal planning. The authors generate simulated data to evaluate the quantity of interest, e.g. 10th percentile of failure time and apply the response surface methodology (RSM) to find an optimal solution with respect to the design parameters, e.g. test conditions and test unit allocations. The authors illustrate their approach applied to the thermal ALT with right censoring and lognormal failure time distribution.

The design found by the proposed approach shows substantially improved statistical performance in terms of the standard error of estimates of 10th percentile of failure time. In addition, the approach provides useful insights about the sensitivity of each decision variable to the objective function.

More comprehensive experiments might be needed to test its scalability of the method.

This method is practically useful to find a reasonably efficient optimal ALT design. It can be applied to any quantities of interest and objective functions as long as those quantities can be computed from a set of simulated datasets.

This is a novel approach to create an optimal ALT design by using RSM and simulated data.

The purpose of this paper is to analyze the Bayes acceptance plan of the parallel system for pre‐specified consumer's and producer's specifications regarding the system availability.

This study considers Bayesian technique to examine the acceptance plan for steady state availability of a parallel system for half‐normal failure as well as repair time.

If there is variation(s) in mean availability of the test plan, then according to their admissible risks producer and consumer may choose a suitable plan.

The methodology proposed in the paper represents Bayes acceptance plan for testing the lots of the parallel system model when failure and repair time follows half‐normal distribution.

Discusses the problems of how to structure a computerized process‐oriented test facility [TF] with particular regard to the aerospace, automotive, electronic, chemical and railway industries and the military. Covers the areas of test facility functional architecture, operation philosophy, test plan preparation, data management support, system access and security, system engineering support, the conducting of the test and system maintenance support. Concludes that the aim of a structural approach has been to focalize in an organized framework the attention of a test‐designer to the operating and supporting functions of a test facility. The general methodology proposed can be utilised as a reference in many application fields from defence to commercial systems.