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All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Intelligent Processing Equipment Research and Development Programs of the Department of Commerce

The intelligence processing equipment (IPE) research and development (R&D) programs of the Department of Commerce are carried out within the National Institute of Standards and Technology (NIST). This institute has had work in support of industrial productivity as part of its mission since its founding in 1901. With the advent of factory automation these efforts have increasingly turned to R&D in IPE. The Manufacturing Engineering Laboratory (MEL) of NIST devotes a major fraction of its efforts to this end while other elements within the organization, notably the Material Science and Engineering Laboratory, have smaller but significant programs. An inventory of all such programs at NIST and a representative selection of projects that at least demonstrate the scope of the efforts are presented.

Simpson, J. A.↗
NASA NTRS1992

US Department of Energy's Efforts in Intelligent Processing Equipment

The Department of Energy (DOE) uses intelligent processing equipment (IPE) technologies to conduct research and development and manufacturing for energy and nuclear weapons programs. This paper highlights several significant IPE efforts underway in DOE. IPE technologies are essential to the accomplishment of DOE's missions, because of the need for small lot production, precision, and accuracy in manufacturing, hazardous waste management, and protection of the environment and the safety and health of the workforce and public. Applications of IPE technologies include environmental remediation and waste handling, advanced manufacturing, and automation of tasks carried out in hazardous areas. DOE laboratories have several key programs that integrate robotics, sensor, and control technologies. These programs embody a considerable technical capability that also may be used to enhance U.S. industrial competitiveness. DOE encourages closer cooperation with U.S. industrial partners based on mutual benefits. This paper briefly describes technology transfer mechanisms available for industrial involvement.

Peavy, Richard D.↗
NASA NTRS1992

Intelligent Processing Equipment Developments Within the Navy's Manufacturing Technology Centers of Excellence

The U.S. Navy has had an active Manufacturing Technology (MANTECH) Program aimed at developing advanced production processes and equipment since the late-1960's. During the past decade, however, the resources of the MANTECH program were concentrated in Centers of Excellence. Today, the Navy sponsors four manufacturing technology Centers of Excellence: the Automated Manufacturing Research Facility (AMRF); the Electronics Manufacturing Productivity Facility (EMPF); the National Center for Excellence in Metalworking Technology (NCEMT); and the Center of Excellence for Composites Manufacturing Technology (CECMT). This paper briefly describes each of the centers and summarizes typical Intelligent Equipment Processing (IEP) projects that were undertaken.

Nanzetta, Philip↗
NASA NTRS1992

Intelligent Processing Equipment Projects at DLA

The Defense Logistics Agency is successfully incorporating Intelligent Processing Equipment (IPE) into each of its Manufacturing Technology thrust areas. Several IPE applications are addressed in the manufacturing of two 'soldier support' items: combat rations and military apparel. In combat rations, in-line sensors for food processing are being developed or modified from other industries. In addition, many process controls are being automated to achieve better quality and to gain higher use (soldier) acceptance. IPE applications in military apparel include: in-process quality controls for identification of sewing defects, use of robots in the manufacture of shirt collars, and automated handling of garments for pressing.

Obrien, Donald F.↗
NASA NTRS1992

Intelligent Processing Equipment Research Supported by the National Science Foundation

The research in progress on processes, workstations, and systems has the goal of developing a high level of understanding of the issues involved. This will enable the incorporation of a level of intelligence that will allow the creation of autonomous manufacturing systems that operate in an optimum manner, under a wide range of conditions. The emphasis of the research has been on the development of highly productive and flexible techniques to address current and future problems in manufacturing and processing. Several of these projects have resulted in well-defined and established models that can now be implemented in the application arena in the next few years.

Rao, Suren B.↗
NASA NTRS1992

Comparison of display enhancement with intelligent decision-aiding

Currently, two main approaches exist for improving the human-machine interface component of a system in order to improve overall system performance, display enhancement and intelligent decision aiding. Each of these two approaches has its own set of advantages and disadvantages, as well as introduce its own set of additional performance problems. These characteristics should help identify which types of problem situations and domains are better aided by which type of strategy. The characteristic issues are described of these two decision aiding strategies. Then differences in expert and novice decision making are described in order to help determine whether a particular strategy may be better for a particular type of user. Finally, research is outlined to compare and contrast the two technologies, as well as to examine the interaction effects introduced by the different skill levels and the different methods for training operators.

Kirlik, Alex↗
NASA NTRS1992

Robust intelligent flight control for hypersonic vehicles

Intelligent optimization methods are applied to the problem of real-time flight control for a class of airbreathing hypersonic vehicles (AHSV). The extreme flight conditions that will be encountered by single-stage-to-orbit vehicles, such as the National Aerospace Plane, present a tremendous challenge to the entire spectrum of aerospace technologies. Flight control for these vehicles is particularly difficult due to the combination of nonlinear dynamics, complex constraints, and parametric uncertainty. An approach that utilizes all available a priori and in-flight information to perform robust, real time, short-term trajectory planning is presented.

Chamitoff, Gregory Errol↗
NASA NTRS1991

Using Intelligent Simulation to Enhance Human Performance in Aircraft Maintenance

Human factors research and development investigates the capabilities and limitations of the human within a system. Of the many variables affecting human performance in the aviation maintenance system, training is among the most important. The advent of advanced technology hardware and software has created intelligent training simulations. This paper describes one advanced technology training system under development for the Federal Aviation Administration.

Aging Aircraft↗
NASA NTRS1992

CTAS: Computer intelligence for air traffic control in the terminal area

A system for the automated management and control of arrival traffic, referred to as the Center-TRACON Automation System (CTAS), has been designed by the ATC research group at NASA Ames research center. In a cooperative program, NASA and the FAA have efforts underway to install and evaluate the system at the Denver and Dallas/Ft. Worth airports. CTAS consists of three types of integrated tools that provide computer-generated intelligence for both Center and TRACON controllers to guide them in managing and controlling arrival traffic efficiently. One tool, the Traffic Management Advisor (TMA), establishes optimized landing sequences and landing times for aircraft arriving in the center airspace several hundred miles from the airport. In TRACON, TMA frequencies missed approach aircraft and unanticipated arrivals. Another tool, the Descent Advisor (DA), generates clearances for the center controllers handling at crossing times provided by TMA. In the TRACON, the final approach spacing tool (FAST) provides heading and speed clearances that produce and accurately spaced flow of aircraft on the final approach course. A data base consisting of aircraft performance models, airline preferred operational procedures and real time wind measurements contribute to the effective operation of CTAS. Extensive simulator evaluations of CTAS have demonstrated controller acceptance, delay reductions, and fuel savings.

Erzberger, Heinz↗
NASA NTRS1992

An evaluation of training effectiveness of an intelligent tutoring system

The study evaluated the training effectiveness of an intelligent tutoring system (ITS) for the Remote Manipulator System (RMS). The study examined how well individuals learn the training content and skills from the RMS ITS and to what extent the content and skills learned using the ITS transfer to RMS task performance in the SES, a high fidelity simulator. Three astronauts completed 8 2-hour ITS sessions addressing movement in three coordinate systems, grapple, ungrapple, berth, and unberth procedures, and singularities and reach limits. Their performance was also observed in an SES training session. Performance data were collected using multiple measures: ITS task performance, transfer performance on the SES, a conceptual knowledge test, an opinion survey completed by astronauts, and comments and observations from astronauts and trainers. Results indicated the RMS ITS to be moderately effective and provided evidence of the efficacy of ITS's, in general. Comments and suggestions are provided relating to how the ITS could be improved and to enable decision makers to judge the effectiveness of the RMS ITS.

Johnson, Debra Steele↗
NASA NTRS1991

Human factors issues in the use of artificial intelligence in air traffic control. October 1990 Workshop

The objective of the workshop was to explore the role of human factors in facilitating the introduction of artificial intelligence (AI) to advanced air traffic control (ATC) automation concepts. AI is an umbrella term which is continually expanding to cover a variety of techniques where machines are performing actions taken based upon dynamic, external stimuli. AI methods can be implemented using more traditional programming languages such as LISP or PROLOG, or they can be implemented using state-of-the-art techniques such as object-oriented programming, neural nets (hardware or software), and knowledge based expert systems. As this technology advances and as increasingly powerful computing platforms become available, the use of AI to enhance ATC systems can be realized. Substantial efforts along these lines are already being undertaken at the FAA Technical Center, NASA Ames Research Center, academic institutions, industry, and elsewhere. Although it is clear that the technology is ripe for bringing computer automation to ATC systems, the proper scope and role of automation are not at all apparent. The major concern is how to combine human controllers with computer technology. A wide spectrum of options exists, ranging from using automation only to provide extra tools to augment decision making by human controllers to turning over moment-by-moment control to automated systems and using humans as supervisors and system managers. Across this spectrum, it is now obvious that the difficulties that occur when tying human and automated systems together must be resolved so that automation can be introduced safely and effectively. The focus of the workshop was to further explore the role of injecting AI into ATC systems and to identify the human factors that need to be considered for successful application of the technology to present and future ATC systems.

Hockaday, Stephen↗
NASA NTRS1990

Knowledge acquisition and representation for the Systems Test and Operations Language (STOL) Intelligent Tutoring System (ITS)

This presentation concentrates on knowledge acquisition and its application to the development of an expert module and a user interface for an Intelligent Tutoring System (ITS). The Systems Test and Operations Language (STOL) ITS is being developed to assist NASA control center personnel in learning a command and control language as it is used in mission operations rooms. The objective of the tutor is to impart knowledge and skills that will permit the trainee to solve command and control problems in the same way that the STOL expert solves those problems. The STOL ITS will achieve this object by representing the solution space in such a way that the trainee can visualize the intermediate steps, and by having the expert module production rules parallel the STOL expert's knowledge structures.

Seamster, Thomas L.↗
NASA NTRS1990

A Petri-net coordination model for an intelligent mobile robot

The authors present a Petri net model of the coordination level of an intelligent mobile robot system (IMRS). The purpose of this model is to specify the integration of the individual efforts on path planning, supervisory motion control, and vision systems that are necessary for the autonomous operation of the mobile robot in a structured dynamic environment. This is achieved by analytically modeling the various units of the system as Petri net transducers and explicitly representing the task precedence and information dependence among them. The model can also be used to simulate the task processing and to evaluate the efficiency of operations and the responsibility of decisions in the coordination level of the IMRS. Some simulation results on the task processing and learning are presented.

Wang, F.-Y.↗
NASA NTRS1991

Applications of intelligent computer-aided training

Intelligent computer-aided training (ICAT) systems simulate the behavior of an experienced instructor observing a trainee, responding to help requests, diagnosing and remedying trainee errors, and proposing challenging new training scenarios. This paper presents a generic ICAT architecture that supports the efficient development of ICAT systems for varied tasks. In addition, details of ICAT projects, built with this architecture, that deliver specific training for Space Shuttle crew members, ground support personnel, and flight controllers are presented. Concurrently with the creation of specific ICAT applications, a general-purpose software development environment for ICAT systems is being built. The widespread use of such systems for both ground-based and on-orbit training will serve to preserve task and training expertise, support the training of large numbers of personnel in a distributed manner, and ensure the uniformity and verifiability of training experiences.

Loftin, R. B.↗
NASA NTRS1990

Intelligent perturbation algorithms for space scheduling optimization

The optimization of space operations is examined in the light of optimization heuristics for computer algorithms and iterative search techniques. Specific attention is given to the search concepts known collectively as intelligent perturbation algorithms (IPAs) and their application to crew/resource allocation problems. IPAs iteratively examine successive schedules which become progressively more efficient, and the characteristics of good perturbation operators are listed. IPAs can be applied to aerospace systems to efficiently utilize crews, payloads, and resources in the context of systems such as Space-Station scheduling. A program is presented called the MFIVE Space Station Scheduling Worksheet which generates task assignments and resource usage structures. The IPAs can be used to develop flexible manifesting and scheduling for the Industrial Space Facility.

Kurtzman, Clifford R.↗
NASA NTRS1992

Identification of time-varying structural dynamic systems - An artificial intelligence approach

An application of the artificial intelligence-derived methodologies of heuristic search and object-oriented programming to the problem of identifying the form of the model and the associated parameters of a time-varying structural dynamic system is presented in this paper. Possible model variations due to changes in boundary conditions or configurations of a structure are organized into a taxonomy of models, and a variant of best-first search is used to identify the model whose simulated response best matches that of the current physical structure. Simulated model responses are verified experimentally. An output-error approach is used in a discontinuous model space, and an equation-error approach is used in the parameter space. The advantages of the AI methods used, compared with conventional programming techniques for implementing knowledge structuring and inheritance, are discussed. Convergence conditions and example problems have been discussed. In the example problem, both the time-varying model and its new parameters have been identified when changes occur.

Glass, B. J.↗
NASA NTRS1990

Intelligent adaptive structures

'Intelligent Adaptive Structures' (IAS) refers to structural systems whose geometric and intrinsic structural characteristics can be automatically changed to meet mission requirements with changing operational scenarios. An IAS is composed of actuators, sensors, and a control logic; these are integrated in a distributed fashion within the elements of the structure. The IAS concepts thus far developed for space antennas and other precision structures should be applicable to civil, marine, automotive, and aeronautical structural systems.

Wada, Ben K.↗
NASA NTRS1992

An advanced intelligent control system framework

A reusable rocket-engine intelligent control system (RREICS) framework was developed to a define a control framework for rocket-engine systems that reduces the required engine maintenance, extends the useful operating life, and maximizes the probability of mission success. The RREICS framework defines a controller that handles a rocket engine cluster as a single system rather than as a collection of individual engines. This enables the controller to alter individual engine operations in response to engine performance or integrity degradations while maintaining the propulsion subsystem external parameters at the levels required for mission success. A simplified model of a three engine cluster and the associated propulsion subsystem controller is also described.

Nemeth, ED↗