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Fully automated variable-polarity plasma arc VPPA welding system developed at Marshall Space Flight Center. System eliminates defects caused by human error. Integrates many sensors with mathematical model of the weld and computer-controlled welding equipment. Sensors provide real-time information on geometry of weld bead, location of weld joint, and wire-feed entry. Mathematical model relates geometry of weld to critical parameters of welding process.
The calculation of reliability measures using Markov models is required for life-critical processor-memory-switch structures that have standby redundancy or that are subject to transient or intermittent faults or repair. The task of specifying these models is tedious and prone to human error because of the large number of states and transitions required in any reasonable system. Therefore, model specification is a major analysis bottleneck, and model verification is a major validation problem. The general unfamiliarity of computer architects with Markov modeling techniques further increases the necessity of automating the model specification. Automation requires a general system description language (SDL). For practicality, this SDL should also provide a high level of abstraction and be easy to learn and use. The first attempt to define and implement an SDL with those characteristics is presented. A program named Automated Reliability Modeling (ARM) was constructed as a research vehicle. The ARM program uses a graphical interface as its SDL, and it outputs a Markov reliability model specification formulated for direct use by programs that generate and evaluate the model.
A fully automated welding system, which can operate totally independent of human intervention, is currently unavailable in the welding industry. Development of the Marshall Automated Weld System (MAWS) has been undertaken to fill this void. The system will enable application of statistical process control practices to assure weld quality prior to post weld nondestructive testing. The Variable Polarity Plasma Arc (VPPA) welding process has been baselined for MAWS because it has eliminated process related defects in the welding of the Space Shuttle External Tank. The few remaining weld defects occurring on the tank can be associated with human error. The system integrates multiple sensors (providing real time information on weld bead geometry, weld joint location, wirefeed entry, and inert gas quality) with a weld model (describing weld geometry in relation to critical parameters) and computer-controlled VPPA weld equipment. This system is designed to provide real-time, closed-loop control of the weld as it is being made.
A fully automated welding system, which can operate totally independent of human intervention, is currently unavailable in the welding industry. Development of the Marshall Automated Weld System (MAWS) has been undertaken to fill this void. The system will enable application of statistical process control practices to assure weld quality prior to post weld nondestructive testing. The Variable Polarity Plasma Arc (VPPA) welding process has been baselined for MAWS because it has eliminated process related defects in the welding of the Space Shuttle External Tank. The few remaining weld defects occurring on the tank can be associated with human error. The system integrates multiple sensors (providing real time information on weld bead geometry, weld joint location, wirefeed entry, and inert gas quality) with a weld model (describing weld geometry in relation to critical parameters) and computer controlled VPPA weld equipment. This system is designed to provide real-time, closed-loop control of the weld as it is being made.
This report updates a 1989-90 survey of advanced instrumentation and controls (I&C) technologies and associated human factors issues in the U.S. and Canadian nuclear industries carried out by a team from Oak Ridge National Laboratory (Carter and Uhrig 1990). The authors found that the most advanced I&C systems are in the Canadian CANDU plants, where the newest plant (Darlington) has digital systems in almost 100 percent of its control systems and in over 70 percent of its plant protection system. Increased emphasis on human factors and cognitive science in modern control rooms has resulted in a reduced workload for the operators and the elimination of many human errors. Automation implemented through digital instrumentation and control is effectively changing the role of the operator to that of a systems manager. The hypothesis that properly introducing digital systems increases safety is supported by the Canadian experience. The performance of these digital systems has been achieved using appropriate quality assurance programs for both hardware and software development. Recent regulatory authority review of the development of safety-critical software has resulted in the creation of isolated software modules with well defined interfaces and more formal structure in the software generation. The ability of digital systems to detect impending failures and initiate a fail-safe action is a significant safety issue that should be of special interest to nuclear utilities and regulatory authorities around the world.
This panel was organized by the Aerospace Human Factors Committee to illustrate behavioral research on the perceptual, cognitive, and group processes that determine crew effectiveness in modern cockpits. Crew reactions to the introduction of highly automated systems in the cockpit will be reported on. Automation can improve operational capabilities and efficiency and can reduce some types of human error, but may also introduce entirely new opportunities for error. The problem solving and decision making strategies used by crews led by captains with various personality profiles will be discussed. Also presented will be computational approaches to modeling the cognitive demands of cockpit operations and the cognitive capabilities and limitations of crew members. Factors contributing to aircrew deviations from standard operating procedures and misuse of checklist, often leading to violations, incidents, or accidents will be examined. The mechanisms of visual perception pilots use in aircraft control and the implications of these mechanisms for effective design of visual displays will be discussed.
Advances in technology have greatly impacted the appearance of the modern aircraft cockpit. Where once one would see rows upon rows. The introduction of automation has greatly altered the demands on the pilots and the dynamics of aircrew task performance. While engineers and designers continue to implement the latest technological innovations in the cockpit - claiming higher reliability and decreased workload - a large percentage of aircraft accidents are still attributed to human error. Rather than being the main instigators of accidents, operators tend to be the inheritors of system defects created by poor design, incorrect installation, faulty maintenance and bad management decisions. This paper looks at some of the variables that need to be considered if we are to eliminate at least one of these inheritances - poor design. Specifically, this paper describes the first part of a comprehensive study aimed at identifying the effects of automation on crew coordination.
Report presents survey of state of art in human factors in automation of aircraft operation. Presents examination of aircraft automation and effects on flight crews in relation to human error and aircraft accidents.
The scheduling of events on board a spacecraft is based on forecast energy levels. The real time values of energy may not coincide with the forecast values; consequently, a dynamic revising to the allocation of power is needed. The re-scheduling is also needed for other reasons on board a spacecraft like the addition of new event which must be scheduled, or a failure of an event due to many different contingencies. This need of rescheduling is very important to the survivability of the spacecraft. In this presentation, a re-scheduling tool will be presented as a part of an overall scheme for the power management on board a spacecraft from the allocation of energy point of view. The overall scheme is based on the optimal use of energy available on board a spacecraft using expert systems combined with linear optimization techniques. The system will be able to schedule maximum number of events utilizing most energy available. The outcome is more events scheduled to share the operation cost of that spacecraft. The system will also be able to re-schedule in case of a contingency with minimal time and minimal disturbance of the original schedule. The end product is a fully integrated planning system capable of producing the right decisions in short time with less human error. The overall system will be presented with the re-scheduling algorithm discussed in detail, then the tests and results will be presented for validations.
This paper describes how features from the field of Intelligent Tutoring Systems are applied to the Motor-Operated Valve (MOV) Advanced Technology Training System (ATTS). The MOV ATTS is a training system developed at Galaxy Scientific Corporation for the Central Research Institute of Electric Power Industry in Japan and the Electric Power Research Institute in the United States. The MOV ATTS combines traditional computer-based training approaches with system simulation, integrated expert systems, and student and expert modeling. The primary goal of the MOV ATTS is to reduce human errors that occur during MOV overhaul and repair. The MOV ATTS addresses this goal by providing basic operational information of the MOV, simulating MOV operation, providing troubleshooting practice of MOV failures, and tailoring this training to the needs of each individual student. The MOV ATTS integrates multiple expert models (functional and procedural) to provide advice and feedback to students. The integration also provides expert model validation support to developers. Student modeling is supported by two separate student models: one model registers and updates the student's current knowledge of basic MOV information, while another model logs the student's actions and errors during troubleshooting exercises. These two models are used to provide tailored feedback to the student during the MOV course.
Aluminum-Lithium is a modern material that NASA MSFC is evaluating as an option for the aluminum alloys and other aerospace metals presently in use. The importance of aluminum-lithium is in it's superior weight to strength characteristics. However, aluminum-lithium has produced many challenges in regards to manufacturing and maintenance. The solution to these problems are vital to the future uses of the shuttle for delivering larger payloads into earth orbit and are equally important to future commercial applications of aluminum-lithium. The Metals Processes Branch at MSFC is conducting extensive tests on aluminum-lithium which includes the collection of large amounts of data. This report discusses the automation and data acquisition for two processes: the initial weld and the repair. The new approach reduces the time required to collect the data, increases the accuracy of the data, and eliminates several types of human errors during data collection and entry. The same material properties that enhance the weight to strength characteristics of aluminum-lithium contribute to the problems with cracks occurring during welding, especially during the repair/rework process. The repairs are required to remove flaws or defects discovered in the initial weld, either discovered by x-ray, visual inspection, or some other type of nondestructive evaluation. It has been observed that cracks typically appear as a result of or beyond the second repair. MSFC scientists have determined that residual mechanical stress introduced by the welding process is a primary cause of the cracking. Two obvious solutions are to either prevent or minimize the stress introduced during the welding process, or remove or reduce the stress after the welding process and MSFC is investigating both of these.
Human Factors Engineering (HFE) is a discipline whose goal is to engineer a safer, more efficient interface between humans and machines. HFE makes use of a wide range of tools and techniques to fulfill this goal. One of these tools is known as motion and time study, a technique used to develop time standards for given tasks. During the summer of 1995, a human factors motion and time study was initiated with the goals of developing a database of EVA task times and developing a method of utilizing the database to predict how long an EVA should take. Initial development relied on the EVA activities performed during the STS-61 (Hubble) mission. The first step of the study was to become familiar with EVA's, the previous task-time studies, and documents produced on EVA's. After reviewing these documents, an initial set of task primitives and task-time modifiers was developed. Data was collected from videotaped footage of two entire STS-61 EVA missions and portions of several others, each with two EVA astronauts. Feedback from the analysis of the data was used to further refine the primitives and modifiers used. The project was continued during the summer of 1996, during which data on human errors was also collected and analyzed. Additional data from the STS-71 mission was also collected. Analysis of variance techniques for categorical data was used to determine which factors may affect the primitive times and how much of an effect they have. Probability distributions for the various task were also generated. Further analysis of the modifiers and interactions is planned.
Session TP2 includes short reports concerning: (1) Human Factors Engineering of the International space Station Human Research Facility; (2) Structured Methods for Identifying and Correcting Potential Human Errors in Space operation; (3) An Improved Procedure for Selecting Astronauts for Extended Space Missions; (4) The NASA Performance Assessment Workstation: Cognitive Performance During Head-Down Bedrest; (5) Cognitive Performance Aboard the Life and Microgravity Spacelab; and (6) Psychophysiological Reactivity Under MIR-Simulation and Real Micro-G.
Automatic contrail detection is of major importance in the study of the atmospheric effects of aviation. Due to the large volume of satellite imagery, selecting contrail images for study by hand is impractical and highly subject to human error. It is far better to have a system in place that will automatically evaluate an image to determine 1) whether it contains contrails and 2) where the contrails are located. Preliminary studies indicate that it is possible to automatically detect and locate contrails in Advanced Very High Resolution Radiometer (AVHRR) imagery with a high degree of confidence. Once contrails have been identified and localized in a satellite image, it is useful to segment the image into contrail versus noncontrail pixels. The ability to partition image pixels makes it possible to determine the optical properties of contrails, including optical thickness and particle size. In this paper, we describe a new technique for segmenting satellite images containing contrails. This method has good potential for creating a contrail climatology in an automated fashion. The majority of contrails are detected, rejecting clutter in the image, even cirrus streaks. Long, thin contrails are most easily detected. However, some contrails may be missed because they are curved, diffused over a large area, or present in short segments. Contrails average 2-3 km in width for the cases studied.
Propulsion system quality is defined in this paper as having high reliability, that is, quality is a high probability of within-tolerance performance or operation. Since failures are out-of-tolerance performance, the probability of failures and their occurrence is the difference between high and low quality systems. Failures can be described at 3 levels: the system failure (which is the detectable end of a failure), the failure mode (which is the failure process), and the failure cause (which is the start). Failure causes can be evaluated & classified by type. The results of typing flight history failures shows that most failures are in unrecognized modes and result from human error or noise, i.e. failures are when engineers learn how things really work. Although the study based on US launch vehicles, a sampling of failures from other countries indicates the finding has broad application. The parameters of the design of a propulsion system are not single valued, but have dispersions associated with the manufacturing of parts. Many tests are needed to find failures, if the dispersions are large relative to tolerances, which could contribute to the large number of failures in unrecognized modes.
Increased automation in complex systems has led to changes in the human controller's role and to new types of technology-induced human error. Attempts to mitigate these errors have primarily involved giving more authority to the automation, enhancing operator training, or changing the interface. While these responses may be reasonable under many circumstances, an alternative is to redesign the automation in ways that do not reduce necessary or desirable functionality or to change functionality where the tradeoffs are judged to be acceptable. This paper describes an approach to detecting error-prone automation features early in the development process while significant changes can still be made to the conceptual design of the system. The information about such error-prone features can also be useful in the design of the operator interface, operational procedures, or operator training.
The process of designing and analyzing a multiple-reflector system has traditionally been time-intensive, requiring large amounts of both computational and human time. At many frequencies, a discrete approximation of the radiation integral may be used to model the system. The code which implements this physical optics (PO) algorithm was developed at the Jet Propulsion Laboratory. It analyzes systems of antennas in pairs, and for each pair, the analysis can be computationally time-consuming. Additionally, the antennas must be described using a local coordinate system for each antenna, which makes it difficult to integrate the design into a multi-disciplinary framework in which there is traditionally one global coordinate system, even before considering deforming the antenna as prescribed by external structural and/or thermal factors. Finally, setting up the code to correctly analyze all the antenna pairs in the system can take a fair amount of time, and introduces possible human error. The use of parallel computing to reduce the computational time required for the analysis of a given pair of antennas has been previously discussed. This paper focuses on the other problems mentioned above. It will present a methodology and examples of use of an automated tool that performs the analysis of a complete multiple-reflector system in an integrated multi-disciplinary environment (including CAD modeling, and structural and thermal analysis) at the click of a button. This tool, named MOD Tool (Millimeter-wave Optics Design Tool), has been designed and implemented as a distributed tool, with a client that runs almost identically on Unix, Mac, and Windows platforms, and a server that runs primarily on a Unix workstation and can interact with parallel supercomputers with simple instruction from the user interacting with the client.
Aging aircraft structures and composite materials are requiring rapid inspection of large areas. Removal from the aircraft for NDE at an inspection facility is not economical as compared to field inspection. Detection and characterization of defects are labor intensive, time consuming and when the process is manual the results are subjected to human error. These limitations of NDE created a need for portable, user friendly inspection systems that can rapidly scan large areas of complex structures and locate all the detrimental material conditions. Addressing this need has been an evolutionary process that followed the technology trend, and unique devices were developed to allow rapid field inspection. This development involves multi-disciplinary approaches to integrate NDE, telerobotics, neural networks, advanced materials science, imbedded computing and automated control. These efforts have led to the development of various portable inspection systems and the current trend is towards fully automatic systems that will operate autonomously.