Optimal design procedures for two-level fractional factorial experiments given partial prior information about parameters
Design optimization for fractional factorial experiments by finite decision problem based on prior information
SEARCH · Search NASA
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Design optimization for fractional factorial experiments by finite decision problem based on prior information
Skylab as orbital factory, worksite and observatory for experiments in science, technology, materials science and manufacturing
NAMER is used to find Bayes procedure for designing two level, fractional factorial experiments when given partial prior information. Program is written in FORTRAN 4 for IBM 7094 computer.
Under certain specified conditions, the Bayes procedure for designing two-level fractional factorial experiments is that which maximizes the expected utility over all possible choices of parameter-estimator matchings, physical-design variable matchings, defining parameter groups, and sequences of telescoping groups. NAMER computes the utility of all possible matchings of physical variables to design variables and parameters to estimators for a specified choice of defining parameter group or groups. The matching yielding the maximum expected utility is indicated, and detailed information is provided about the optimal matchings and utilities. Complete documentation is given; and an example illustrates input, output, and usage.
An algorithm and computer program are presented for generating all the distinct 2(p-q) fractional factorial designs. Some applications of this algorithm to the construction of tables of designs and of designs for nonstandard situations and its use in Bayesian design are discussed. An appendix includes a discussion of an actual experiment whose design was facilitated by the algorithm.
As many as three iterated statistical model deletion procedures are considered for an experiment. Population model coefficients were chosen to simulate a saturated factorial experiment having an unfavorable distribution of parameter values. Using random number studies, three model selection strategies were developed, namely, (1) a strategy to be used in anticipation of large coefficients of variation (neighborhood of 65 percent), (2) strategy to be used in anticipation of small coefficients of variation (4 percent or less), and (3) a security regret strategy to be used in the absence of such prior knowledge.
Population model coefficients were chosen to simulate a saturated 2 to the 4th fixed-effects experiment having an unfavorable distribution of relative values. Using random number studies, deletion strategies were compared that were based on the F-distribution, on an order statistics distribution of Cochran's, and on a combination of the two. The strategies were compared under the criterion of minimizing the maximum prediction error, wherever it occurred, among the two-level factorial points. The strategies were evaluated for each of the conditions of 0, 1, 2, 3, 4, 5, or 6 center points. Three classes of strategies were identified as being appropriate, depending on the extent of the experimenter's prior knowledge. In almost every case the best strategy was found to be unique according to the number of center points. Among the three classes of strategies, a security regret class of strategy was demonstrated as being widely useful in that over a range of coefficients of variation from 4 to 65%, the maximum predictive error was never increased by more than 12% over what it would have been if the best strategy had been used for the particular coefficient of variation. The relative efficiency of the experiment, when using the security regret strategy, was examined as a function of the number of center points, and was found to be best when the design used one center point.
Automation of lunar mining and manufacturing facility maintenance and repair is addressed. Designing the factory as an automated, multiproduct, remotely controlled, reprogrammable Lunar Manufacturing Facility capable of constructing duplicates of itself which would themselves be capable of further replication is proposed.
In a continued effort to design a surface based factory on Mars for the production of oxygen and water, a preliminary study was made of the surface and atmospheric composition on Mars and determined the mass densities of the various gases in the Martian atmosphere. Based on the initial studies, oxygen and water were determined to be the two products that could be produced economically under the Martian conditions. Studies were also made on present production techniques to obtain water and oxygen. Analyses were made to evaluate the current methods of production that were adaptable to the Martian conditions. Even though the initial effort was the production of oxygen and water, it was found necessary to produce some diluted gases that can be mixed with the oxygen produced to constitute 'breathable' air. The conceptual design of a breathable air manufacturing system, a means of drilling for underground water, and storage of water for future use were completed. The design objective was the conceptual design of an integrated system for the supply of quality water for biological consumption, farming, residential and industrial use.
For 15 years, the Software Engineering Laboratory (SEL) has been carrying out studies and experiments for the purpose of understanding, assessing, and improving software and software processes within a production software development environment at NASA/GSFC. The SEL comprises three major organizations: (1) NASA/GSFC, Flight Dynamics Division; (2) University of Maryland, Department of Computer Science; and (3) Computer Sciences Corporation, Flight Dynamics Technology Group. These organizations have jointly carried out several hundred software studies, producing hundreds of reports, papers, and documents, all of which describe some aspect of the software engineering technology that was analyzed in the flight dynamics environment at NASA. The studies range from small, controlled experiments (such as analyzing the effectiveness of code reading versus that of functional testing) to large, multiple project studies (such as assessing the impacts of Ada on a production environment). The organization's driving goal is to improve the software process continually, so that sustained improvement may be observed in the resulting products. This paper discusses the SEL as a functioning example of an operational software experience factory and summarizes the characteristics of and major lessons learned from 15 years of SEL operations.
In a continued effort to design a surface-based factory on Mars for the production of oxygen and water, the Design Group at Prairie View A&M University made a preliminary study of the surface and atmospheric composition on Mars and determined the mass densities of the various gases in the martian atmosphere. Based on the initial studies, the design group determined oxygen and water to be the two products that could be produced economically under the martian conditions. Studies were also made on present production techniques to obtain water and oxygen. Analyses were made to evaluate the current methods of production that were adaptable to the martian conditions. The detailed report was contained in an Interim Report submitted to NASA/USRA in Aug. of 1986. Even though the initial effort was the production of oxygen and water, we found it necessary to produce some diluted gases that can be mixed with oxygen to constitute 'breathable' air. In Phase 2--Task 1A, the Prairie View A&M University team completed the conceptual design of a breathable-air manufacturing system, a means of drilling for underground water, and storage of water for future use. The design objective of the team for the 1987-1988 academic year was the conceptual design of an integrated system for the supply of quality water for biological consumption, farming, and residential and industrial use. The design has also been completed. Phase 2--Task 1C is the present task for the Prairie View Design Team. This is a continuation of the previous task, and the continuation of this effort is the investigation into the extraction of water from beneath the surface and an alternative method of extraction from ice formations on the surface of Mars if accessible. In addition to investigation of water extraction, a system for computer control of extraction and treatment was developed with emphasis on fully automated control with robotic repair and maintenance. It is expected that oxygen- and water-producing plants on Mars will be limited in the amount of human control that will be available to operate large and/or isolated plants. Therefore, it is imperative that computers be integrated into plant operation with the capability to maintain life support systems and analyze and replace defective parts or systems with no human interface.
The AIAA/NASA Conference on Intelligent Robotics in Field, Factory, Service, and Space (CIRFFSS '94) was originally proposed because of the strong belief that America's problems of global economic competitiveness and job creation and preservation can partly be solved by the use of intelligent robotics, which are also required for human space exploration missions. Individual sessions addressed nuclear industry, agile manufacturing, security/building monitoring, on-orbit applications, vision and sensing technologies, situated control and low-level control, robotic systems architecture, environmental restoration and waste management, robotic remanufacturing, and healthcare applications.
The factory of the future will require an operating methodology which effectively utilizes all of the elements of product design, manufacturing and delivery. The process must respond rapidly to changes in product demand, product mix, design changes or changes in the raw materials. To achieve agility in a manufacturing operation, the design and development of the manufacturing processes must focus on customer satisfaction. Achieving greatest results requires that the manufacturing process be considered from product concept through sales. This provides the best opportunity to build a quality product for the customer at a reasonable rate. The primary elements of a manufacturing system include people, equipment, materials, methods and the environment. The most significant and most agile element in any process is the human resource. Only with a highly trained, knowledgeable work force can the proper methods be applied to efficiently process materials with machinery which is predictable, reliable and flexible. This paper discusses the affect of each element on the development of agile manufacturing systems.
The AIAA/NASA Conference on Intelligent Robotics in Field, Factory, Service, and Space (CIRFFSS '94) was originally proposed because of the strong belief that America's problems of global economic competitiveness and job creation and preservations can partly be solved by the use of intelligent robotics, which are also required for human space exploration missions. Individual sessions addressed the following topics: (1) vision systems integration and architecture; (2) selective perception and human robot interaction; (3) robotic systems technology; (4) military and other field applications; (5) dual-use precommercial robotic technology; (6) building operations; (7) planetary exploration applications; (8) planning; (9) new directions in robotics; and (10) commercialization.
It is argued that the next wave of software process improvement (SPI) activities will be based on a people-centered paradigm. The most promising such paradigm, Watts Humphrey's personal software process (PSP), is summarized and its advantages are listed. The concepts of the PSP are shown also to fit a down-scaled version of Basili's experience factory. The author's data and lessons learned while practicing the PSP are presented along with personal experience, observations, and advice from the perspective of a consultant and teacher for the personal software process.
The goal of this paper is to present the analysis of the multi-factor experiment (factorial design) conducted in EG490, Junior Design at Loyola College in Maryland. The discussion of this paper concludes the experimental analysis and ties the individual class papers together.
According to biological data recorded by the Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) satellite, the ocean contains nearly half of all the Earth's photosynthesis activity. Through photosynthesis, plant life forms use carbon from the atmosphere, and in return, plants produce the oxygen that life requires. In effect, ocean chlorophyll works like a factory, taking carbon and "manufacturing" the air we breathe. Most ocean-bound photosynthesis is performed by single-celled plants called phytoplankton. "These things are so small," according to Michael Behrenfeld, a researcher at NASA Goddard Space Flight Center, "that if you take hundreds of them and stack them end-to-end, the length of that stack is only the thickness of a penny". The humble phytoplankton species plays a vital role in balancing the amounts of oxygen and carbon dioxide in the atmosphere. Therefore, understanding exactly how phytoplankton growth works is important.
A 1/4 - scale model of the Naval Aircraft Factory float-wing convoy interceptor was tested in the Langley 7-by 10-foot tunnel to determine the longitudinal and lateral stability characteristics. The model was tested in the presence of a ground board to determine the effect of simulating the ground on the longitudinal characteristics.