The conceptual design phase of launch vehicle design is subject to significant uncertainty. This uncertainty needs to be quantified and reflected in multidisciplinary design and optimization. However, a primary problem in conducting risk analysis in conceptual launch vehicle design is the lack of historical data and the lack of a technique to quantify input parameter uncertainty. Under those circumstances, asking disciplinary experts for their best judgment is sometimes the only option. This paper describes an expert judgement methodology developed at NASA, Langley Research Center to quantify input distributions for executing launch vehicle weight-risk analysis. The methodology borrowed features from the fields of psychology, knowledge engineering and computer science in determining the uncertainty associated with weight estimating relationships for a launch vehicle design study. A set of questionnaires was developed to qualify and quantify uncertainty associated with design parameters as a set of probability distributions. This approach developed has proved to be a practical way of collecting and documenting expert judgement data. Once parameter uncertainty is quantified in terms of a probability distribution, risk can then be propagated throughout the multidisciplinary system design using simulation or analytical methods to determine overall design risk and for probabilistic multidisciplinary optimization.

According to Everett M. Rogers, innovation is "an idea perceived as new by the individual," and diffusion is "the process by which innovation spreads" (16; 10). According to the book Diffusion of Innovations written by Rogers (16): "The essence of the diffusion process is the human interaction in which one person communicates a new idea to another person. Thus, at the most elemental level of conceptualization, the diffusion process consists of (1) a new idea, (2) individual A who knows about the innovation, and (3) individual B who does not yet know about the innovation." Online learning or distance education among individuals has been a topic of discussion for quite some time. There have been many different thoughts and theories as to what distance education should consist of; how people perceive distance education; and what should be included in a distance education course. In order to understand the confusion behind the acceptance of new technologies and ideas, many turn to the Diffusion of Innovation model. The Diffusion of Innovations model is based on the process of understanding how new ideas and products spread. It also discusses why some great ideas do not make it or take a long time to catch on. It analyzes and helps explain the adaptation of a new innovation. It helps us understand the process of social change.

Simulation is the most common tool to introduce basic concepts of lean manufacturing. The vast deployment of simulation in industry to train workers and at universities to educate students attests to this fact. However, as companies with employees scattered in different states, or universities with students logging in from several countries try to teach principles of lean manufacturing using conventional simulation, the results are less than expected. This is due to the fact that the involvement of distance students in such simulations is limited to merely viewing the action being conducted by others physically present in the classroom setting. Being restricted to the sidelines, distance students are not enthused by the potential of lean manufacturing to eliminate waste and reduce lead-time for manufacturing and nonmanufacturing processes.In this paper a method is presented which is being proposed to be implemented to create a virtual simulation to involve distance students in a hand-on manner in learning lean manufacturing principles. As this virtual simulation is conducted entirely on the computer, it can also be a good tool to train non-manufacturing process operators in optimizing their processes where the product that flows through is merely information. Lean concepts like Takt time, elimination of non-value added functions, quality-at-source, reduction of processing time, point-of-use-storage, teamwork, and kanbans, can be introduced to distance students using this virtual simulation. The tool is also ideal to introduce the concept of virtual cells in non-manufacturing processes like those found in healthcare, banking, insurance, business office functions, etc.

Author's Summary.— Why should not language instruction make use of the unlimited opportunities offered by the radio. Experiments at Ohio State University.

No abstract