A paired comparison experiment for gathering expert judgment for an aircraft wiring risk assessment

Wire failure in aircraft can be attributed to several factors and the assessment of the risk of wire failure is becoming an increasingly important task. This paper will discuss the results of an actual experiment to use the paired-comparison technique for expert judgment to develop a relationship for the probability of wire failure as a function of influencing factors in an aircraft environment. The reasons for using this technique are two-fold. First, the failure probability depends on many variables including wire gauge, vibration, environmental condition, etc. In addition, the wire failure data are sparse and fitting these data to a complex failure function is a nontrivial task that may involve a host of assumptions that may not be provable.We describe a method for using actual failure data and the results from a paired comparison to populate the model parameters. In the approach, paired comparison data from select environments is used to obtain failure rate estimates for the candidate environments. Next, a functional relationship for wire failure as a function of the environments is constructed using a proportional hazards model. A regression model is fit from the failure rate estimates to the environmental variables and is used as an estimate of the failure response surface. This technique is being investigated as a means to generate failure rates for an electrical wiring interconnection system (EWIS) risk assessment software tool currently being developed for the FAA Tech Center.     

A general Bayes weibull inference model for accelerated life testing

This article presents the development of a general Bayes inference model for accelerated life testing. The failure times at a constant stress level are assumed to belong to a Weibull distribution, but the specification of strict adherence to a parametric time-transformation function is not required. Rather, prior information is used to indirectly define a multivariate prior distribution for the scale parameters at the various stress levels and the common shape parameter. Using the approach, Bayes point estimates as well as probability statements for use-stress (and accelerated) life parameters may be inferred from a host of testing scenarios. The inference procedure accommodates both the interval data sampling strategy and type I censored sampling strategy for the collection of ALT test data. The inference procedure uses the well-known MCMC (Markov Chain Monte Carlo) methods to derive posterior approximations. The approach is illustrated with an example.     

Planning for Success: A Scenariobased Approach to Contingency Planning Using Expert Judgment

This paper proposes an innovative alternative approach to contingency planning using the techniques of gaming, decision analysis and risk analysis. A hindcasting scenario exercise conducted with over 60 oil spill experts is described. The exercise identifies the critical success factors that must be achieved and the problems that must be resolved in order to accomplish a successful oil spill response. The experts' ratings of the relative criticality and difficulty in achieving the critical success factors and solving the critical problems are presented and discussed. The use of influence-diagramming techniques to structure the results of the hindcasting exercise is described. Experts may use this model to assess the response readiness of their area of responsibility, to identify critical problems or to assess the status of an emergency response.     

A Bayes method for assessing product-reliability during developmenttesting

A fully Bayes approach is presented for analyzing product reliability during the development phase. Based on a Bayes version of the Barlow-Scheuer reliability-growth model, it is assumed that the product goes through a series of test/modification stages, where each product test yields attribute (pass-fail) data, and failure types are classified as fixable or nonfixable. Relevant information on both the failure probabilities and the reliability-growth process is used to motivate the prior joint distribution for the probability of each failure type over the specified range of testing. Results at a particular test-stage can be used to update the knowledge about the probability of each failure type (and thus product reliability) at the current test-stage as well as at subsequent test-stages, and at the end of the development phase. A relative ease of incorporation of prior information and a tractability of the posterior analysis are accomplished by using a Dirichlet distribution as the prior distribution for a transformation of the failure probabilities     

Runout analysis in fatigue investigation

Those individual tests in a series of experiments that are not completed or must be suspended are known as “censored points,” or “runouts”. Inclusion of runouts in data analysis can be problematic, and such ad hoc approaches as ignoring the runout observation or treating it as a failure can significantly affect estimation. The methodology offered here alleviates the handling of runouts and censored data by using the maximum likelihood estimation (MLE) method to incorporate the censored data properly. The methodology is illustrated with an example problem using actual data and the affects of ad hoc approaches are illustrated.     

A quantitative comparison of the effects of modeling approaches on system verification using a controlled challenge problem

Requirements Engineering - To reduce program risks, engineering methods capitalizing on modeling and machine assistance have been extensively investigated within systems engineering (and more...     

1994 ASEM Conference Information and Registration Form

Abstract:

Complex investment decisions by corporate executives often require the comparison of dissimilar attributes and competing technologies. A technique to evaluate qualitative input from experts using a multi-criteria decision making (MCDM) method is described to select a new reactor technology for a merchant nuclear generator. The capital cost, risks from design, licensing and construction, reactor safety, and security considerations are some of the diverse considerations when choosing a reactor design. The uncertainty inherent in experts' opinions for the attribute weighting in the MCDM is modeled through the use of probabilistic inversion. After creating a distribution, random samples from the distribution are used to analyze the “strength” of the results. The decision results for the pool of experts identified the U.S. EPR as their optimal choice.     

Bayesian Computations for a Class of Reliability Growth Models

In this article, we consider the development and analysis of both attribute- and variable-data reliability growth models from a Bayesian perspective. We begin with an overview of a Bayesian attribute-data reliability growth model and illustrate how this model can be extended to cover the variable-data growth models as well. Bayesian analysis of these models requires inference over ordered regions, and even though closed-form results for posterior quantities can be obtained in the attribute-data case, variable-data models prove difficult. In general, when the number of test stages gets large, computations become burdensome and, more importantly, the results may become inaccurate due to computational difficulties. We illustrate how the difficulties in the posterior and predictive analyses can be overcome using Markov-chain Monte Carlo methods. We illustrate the implementation of the proposed models by using examples from both attribute and variable reliability growth data.     

A traffic density analysis of proposed ferry service expansion in San Francisco Bay using a maritime simulation model

A proposal has been made to the California legislature to dramatically increase the frequency and coverage of ferry service in the San Francisco Bay area. A major question in the approval process is the effect of this expansion on the level of congestion on the waterway and the effect this will have on the safety of vessels in the area. A simulation model was created to estimate the number of vessel interactions in the current system and their increases caused by three alternative expansion plans. The output of the simulation model is a geographic profile showing the frequency of vessel interactions across the study area, thus representing the level of congestion under each alternative. Comparing these geographic interaction profiles to a similar one generated for the current ferry service in the San Francisco Bay allows evaluation of the increase in exposure of ferries to adverse conditions, such as, for example, the interaction of high-speed ferries in restricted visibility conditions. This analysis has been submitted to the legislature as part of the overall assessment of the proposal and will be used in the expansion decision.     

A Bayesian perspective on some replacement strategies

In this paper we present a Bayesian decision theoretic approach for determining optimal replacement strategies. This approach enables us to formally incorporate, express, and update our uncertainty when determining optimal replacement strategies. We develop relevant expressions for both the block replacement protocol with minimal repair and the age replacement protocol and illustrate the use of our approach with real data.