Ipek Bozkurt

Human Reliability Analysis in Spaceflight Applications

Predicting and mitigating human error in manned spaceflight can be the difference between mission success and lost vehicle or crewmember. The National Aeronautics and Space Administration (NASA) has used the Cognitive Reliability Error Analysis Model analysis developed by the nuclear industry during the last 30 years of manned spaceflight to predict human error. Although the analysis has proven to be reliable, it does not take into account operations specific for long duration spaceflight such as crew training and ground support. This article first explains the principles of the Cognitive Reliability Error Analysis Model and how it is used at NASA. Then, the probability for error for an International Space Station ingress procedure is calculated using standard performance shaping factors developed for the nuclear power industry. Lastly, the environmental and operational constraints of space flight are used to develop new performance shaping factors specific to a NASA-operated spacecraft. Copyright

Human Reliability Analysis in Spaceflight Applications, Part 2: Modified CREAM for Spaceflight

Human reliability analysis is a crucial for manned spaceflight success. Cognitive Reliability Error Analysis Model (CREAM) has been developed and used by the nuclear industry in predicting human error. Previously, the authors have calculated the probability error for an International Space Station ingress procedure using performance shaping factors (PSF). In this paper, the procedural risk under both ideal and common conditions using the new spaceflight specific PSFs is calculated. The risk was found to vary from the risk calculated using standard PSFs and to vary greatly depending on the spacecraft specific conditions. Under ideal conditions, the risk was found to be 1 in 88, but under common conditions, the risk was 1 in 3. Then, the new PSFs were used to analyze the impact of the three styles of training used at NASA under common conditions. Of skill-based training, task-based training, and knowledge-based training, the CREAM analysis using the new PSFs showed that skill-based training resulted in the most significant improvement in the risk of human error, from 1 in 3 to 1 in 11. Copyright

System of systems perspective on risk: towards a unified concept

Many systems and projects that concern systems engineers, engineering managers, and business managers today can be defined as system of systems (SoS), which are described as ambiguous, uncertain and dynamic, among others. In addition to the traditional view on risk identification, analysis and management, the concept of risk should be considered with respect to these systems of systems. The purpose of this paper is to analyse both fundamental concepts and recent publications in system of systems, business and engineering management, as well as risk analysis, modelling, and management for the purpose of better describing the concept of risk with respect to system of systems. The ultimate goal is to provide engineering and business managers the necessary perspective on the concept of risk and its management for the next generation of systems – including various descriptions of risk and discussion of the relevance of properties of system of systems to sustainable management of risks in engineered systems. To achieve a truly sustainable management of risk, there has to be a change in paradigm from a traditional description of risk to that of a more holistic perspective.

Evaluating a Project Management Simulation Training Exercise

This research is an evaluation of a single-player, project management simulation training exercise. Our objective is to gain understanding about the extent to which it contributes to participants’ project management knowledge and skills. Results from pre- and post-simulation exercise questionnaires indicate that overall the simulation exercise significantly improves a participant’s conceptual knowledge about project management. It also indicates that participants with less experience achieve more knowledge improvement than those with more experience. Results further indicate that the actual performance of the exercise, which represents the educational value of the exercise, is primarily dependent on the post-project management knowledge of the participant established throughout the exercise, prior knowledge brought to the exercise, and the experience of the participant. We believe that these results indicate that the simulation training exercise is a valuable training tool, which both engineering and project managers can use.

Modeling and Simulation as a Theory Building Paradigm

This chapter makes the case that theory can be captured as a model, which can be implemented as a simulation. This allows composing and recomposing theory components to process new theory out of existing theory. While current modeling and simulation applications focus on simulation as a computational activity that algorithmically produces output data based on valid input data, therefore providing information, the proposed approach utilizes the information and combines the application thereof, which provides knowledge. Relevant work is evaluated, but existing approaches neither us the conceptualization as the central component nor are they applied to ill-defined problems, thus the proposed approach is innovative and closes existing gaps. To show the feasibility and validity, theory is represented as axiomatic structures that can be executed under bounded conditions. As such, the chapter presents a methodological approach for building theory out of existing theory using modeling and simulation.

Quantitative analysis of graduate-level engineering management programs

The purpose of this study is to analyze the curricula of Engineering Management programs awarding a graduate-level EM degree (Masters and Doctoral). The analysis is conducted using text analysis software, which brings the necessary rigor and objectivity required when dealing with qualitative data. Preliminary research using multiple sources (American Society for Engineering Management and American Society of Engineering Education) result in a list of over one-hundred universities that offer a graduate-level degree in EM. To conduct the analysis, a curriculum database will be formed that includes course names and descriptions. This data will provide the input to the conceptual and semantic analysis using a computer tool. The results of this analysis will provide an insight into different threads, commonalities and differences between EM programs.

Quantitative analysis of graduate-level systems engineering programs

Systems engineering is a discipline that has increasingly been part of both industry and academia. The number of both undergraduate and graduate programs that offer a systems engineering degree has multiplied throughout the years. The purpose of this research is to analyzed the curricula of graduate-level systems engineering programs to identify main patterns and concepts that are being taught. This analysis will lead to possible strengths and weaknesses of graduate programs with respect to topics that systems engineering, as a discipline, covers.

Rapid Sensor Technology: A Risk and System Complexity Analyses of Early Detection of Influenza-Like-Illnesses

The development of effective and reliable methods to defend the nation against biological terrorism remains an urgent challenge to researchers in the areas of risk, bio-defense, public health, and emergency medicine. The emerging threat of the avian flu pandemic also highlights the unpreparedness of our nations health care system to meet a highly contagious and infectious disease outbreak. The implementation of a rapid sensor technology for early detection of influenza-like-illness provides possible opportunities, as well as problems. Bounding and defining such a complex problem is one of the first challenges this research addresses. Approaching this problem from various perspectives such as risk management, critical infrastructures and emergency medicine proves to be a valid strategy for an efficient solution. After defining the problem and laying out a strategy, discussions on possible tools and techniques for the solution of the problem is presented in this paper, together with the compounding sources of and issues with complexity.