Robotic Automation for Polymer Innovation and Discovery (RAPID): Silicone Formulation Automation
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Process Development for Automated Solar Cell and Module Production. Task 4: Automated Array Assembly
A baseline sequence for the manufacture of solar cell modules was specified. Starting with silicon wafers, the process goes through damage etching, texture etching, junction formation, plasma edge etch, aluminum back surface field formation, and screen printed metallization to produce finished solar cells. The cells were then series connected on a ribbon and bonded into a finished glass tedlar module. A number of steps required additional developmental effort to verify technical and economic feasibility. These steps include texture etching, plasma edge etch, aluminum back surface field formation, array layup and interconnect, and module edge sealing and framing.
Source record↗
Methodology for automating software systems. Task 1 of the foundations for automating software systems
The early stages of a research program designed to establish an experimental research platform for software engineering are described. Major emphasis is placed on Computer Assisted Software Engineering (CASE). The Poor Man's CASE Tool is based on the Apple Macintosh system, employing available software including Focal Point II, Hypercard, XRefText, and Macproject. These programs are functional in themselves, but through advanced linking are available for operation from within the tool being developed. The research platform is intended to merge software engineering technology with artificial intelligence (AI). In the first prototype of the PMCT, however, the sections of AI are not included. CASE tools assist the software engineer in planning goals, routes to those goals, and ways to measure progress. The method described allows software to be synthesized instead of being written or built.
Moseley, Warren↗
Economics of Automation in Space: Implications of Automated Versus Manned Operations on the High Cost of On-Orbit Assembly, Control and Servicing of Spacecraft
The continued high cost and risk of placing astronauts in space has placed considerable burden on NASA to cut costs and consider other means of achieving mission goals both effectively and safely. Additionally, future science missions which might place a tremendous burden on Shuttle availability, or require extended vehicle duty cycles on the Lunar surface and Mars surface, might preclude the presence of astronauts altogether.
Mars surface↗
Towards Autonomous Aviation Operations: What Can We Learn from Other Areas of Automation?
Rapid advances in automation has disrupted and transformed several industries in the past 25 years. Automation has evolved from regulation and control of simple systems like controlling the temperature in a room to the autonomous control of complex systems involving network of systems. The reason for automation varies from industry to industry depending on the complexity and benefits resulting from increased levels of automation. Automation may be needed to either reduce costs or deal with hazardous environment or make real-time decisions without the availability of humans. Space autonomy, Internet, robotic vehicles, intelligent systems, wireless networks and power systems provide successful examples of various levels of automation. NASA is conducting research in autonomy and developing plans to increase the levels of automation in aviation operations. This paper provides a brief review of levels of automation, previous efforts to increase levels of automation in aviation operations and current level of automation in the various tasks involved in aviation operations. It develops a methodology to assess the research and development in modeling, sensing and actuation needed to advance the level of automation and the benefits associated with higher levels of automation. Section II describes provides an overview of automation and previous attempts at automation in aviation. Section III provides the role of automation and lessons learned in Space Autonomy. Section IV describes the success of automation in Intelligent Transportation Systems. Section V provides a comparison between the development of automation in other areas and the needs of aviation. Section VI provides an approach to achieve increased automation in aviation operations based on the progress in other areas. The final paper will provide a detailed analysis of the benefits of increased automation for the Traffic Flow Management (TFM) function in aviation operations.
Sridhar, Banavar↗
Launch Control System Software Development System Automation Testing
The Spaceport Command and Control System (SCCS) is the National Aeronautics and Space Administration's (NASA) launch control system for the Orion capsule and Space Launch System, the next generation manned rocket currently in development. This system requires high quality testing that will measure and test the capabilities of the system. For the past two years, the Exploration and Operations Division at Kennedy Space Center (KSC) has assigned a group including interns and full-time engineers to develop automated tests to save the project time and money. The team worked on automating the testing process for the SCCS GUI that would use streamed simulated data from the testing servers to produce data, plots, statuses, etc. to the GUI. The software used to develop automated tests included an automated testing framework and an automation library. The automated testing framework has a tabular-style syntax, which means the functionality of a line of code must have the appropriate number of tabs for the line to function as intended. The header section contains either paths to custom resources or the names of libraries being used. The automation library contains functionality to automate anything that appears on a desired screen with the use of image recognition software to detect and control GUI components. The data section contains any data values strictly created for the current testing file. The body section holds the tests that are being run. The function section can include any number of functions that may be used by the current testing file or any other file that resources it. The resources and body section are required for all test files; the data and function sections can be left empty if the data values and functions being used are from a resourced library or another file. To help equip the automation team with better tools, the Project Lead of the Automated Testing Team, Jason Kapusta, assigned the task to install and train an optical character recognition (OCR) tool to Brandon Echols, a fellow intern, and I. The purpose of the OCR tool is to analyze an image and find the coordinates of any group of text. Some issues that arose while installing the OCR tool included the absence of certain libraries needed to train the tool and an outdated software version. We eventually resolved the issues and successfully installed the OCR tool. Training the tool required many images and different fonts and sizes, but in the end the tool learned to accurately decipher the text in the images and their coordinates. The OCR tool produced a file that contained significant metadata for each section of text, but only the text and coordinates of the text was required for our purpose. The team made a script to parse the information we wanted from the OCR file to a different file that would be used by automation functions within the automated framework. Since a majority of development and testing for the automated test cases for the GUI in question has been done using live simulated data on the workstations at the Launch Control Center (LCC), a large amount of progress has been made. As of this writing, about 60% of all of automated testing has been implemented. Additionally, the OCR tool will help make our automated tests more robust due to the tool's text recognition being highly scalable to different text fonts and text sizes. Soon we will have the whole test system automated, allowing for more full-time engineers working on development projects.
Automation↗
Decision Making In A High-Tech World: Automation Bias and Countermeasures
Automated decision aids and decision support systems have become essential tools in many high-tech environments. In aviation, for example, flight management systems computers not only fly the aircraft, but also calculate fuel efficient paths, detect and diagnose system malfunctions and abnormalities, and recommend or carry out decisions. Air Traffic Controllers will soon be utilizing decision support tools to help them predict and detect potential conflicts and to generate clearances. Other fields as disparate as nuclear power plants and medical diagnostics are similarly becoming more and more automated. Ideally, the combination of human decision maker and automated decision aid should result in a high-performing team, maximizing the advantages of additional cognitive and observational power in the decision-making process. In reality, however, the presence of these aids often short-circuits the way that even very experienced decision makers have traditionally handled tasks and made decisions, and introduces opportunities for new decision heuristics and biases. Results of recent research investigating the use of automated aids have indicated the presence of automation bias, that is, errors made when decision makers rely on automated cues as a heuristic replacement for vigilant information seeking and processing. Automation commission errors, i.e., errors made when decision makers inappropriately follow an automated directive, or automation omission errors, i.e., errors made when humans fail to take action or notice a problem because an automated aid fails to inform them, can result from this tendency. Evidence of the tendency to make automation-related omission and commission errors has been found in pilot self reports, in studies using pilots in flight simulations, and in non-flight decision making contexts with student samples. Considerable research has found that increasing social accountability can successfully ameliorate a broad array of cognitive biases and resultant errors. To what extent these effects generalize to performance situations is not yet empirically established. The two studies to be presented represent concurrent efforts, with student and professional pilot samples, to determine the effects of accountability pressures on automation bias and on the verification of the accurate functioning of automated aids. Students (Experiment 1) and commercial pilots (Experiment 2) performed simulated flight tasks using automated aids. In both studies, participants who perceived themselves as accountable for their strategies of interaction with the automation were significantly more likely to verify its correctness, and committed significantly fewer automation-related errors than those who did not report this perception.
Mosier, Kathleen L.↗
Automation Bias and Countermeasures in Flight Crews
Results of recent research investigating the use of automated systems have indicated the presence of automation bias, a term describing errors made when decision makers rely on automated cues as a heuristic replacement for vigilant information seeking and processing. Automation commission errors, i.e., errors made when decision makers take inappropriate action because they over-attend to automated information or directives, and automation omission errors, i.e., errors made when decision makers do not take appropriate action because they are not informed of an imminent problem or situation by automated aids, can result from this tendency. In a series of studies, participants who perceived themselves as "accountable" for their strategies of interaction with automation were significantly more likely to verify its correct functioning, and committed significantly fewer automation-related errors than those who did not report this perception. In this study, we focus on two manipulations to encourage verification behaviors within cockpit crews. The first, an information/training manipulation, will focus on explicit information on automation bias, and training for verification of automated functioning. The second manipulation will consist of display prompts to verify automated functioning. Participants (glass-cockpit crews) will fly a series of approaches on the Mini-ACFS, a two-person pan-task flight simulator. Approach scenarios include several automation "events," that is, glitches, malfunctions, or inappropriate recommendations, that can be caught if cross-checked with other cockpit indicators. We anticipate that these manipulations will ameliorate automation bias. Final data analysis will be completed prior to the OSU symposium, and is expected to support the hypotheses that: a) reduced errors are associated with verification behaviors; b) crews will be more likely to verify under training/display conditions than when in the control condition; and c) effects will persist when subjects return for a follow-up exercise 6-9 weeks after their first session. Implications for training and automation design will be discussed.
Mosier, Kathleen, L.↗
Automation: Decision Aid or Decision Maker?
This study clarified that automation bias is something unique to automated decision making contexts, and is not the result of a general tendency toward complacency. By comparing performance on exactly the same events on the same tasks with and without an automated decision aid, we were able to determine that at least the omission error part of automation bias is due to the unique context created by having an automated decision aid, and is not a phenomena that would occur even if people were not in an automated context. However, this study also revealed that having an automated decision aid did lead to modestly improved performance across all non-error events. Participants in the non- automated condition responded with 83.68% accuracy, whereas participants in the automated condition responded with 88.67% accuracy, across all events. Automated decision aids clearly led to better overall performance when they were accurate. People performed almost exactly at the level of reliability as the automation (which across events was 88% reliable). However, also clear, is that the presence of less than 100% accurate automated decision aids creates a context in which new kinds of errors in decision making can occur. Participants in the non-automated condition responded with 97% accuracy on the six "error" events, whereas participants in the automated condition had only a 65% accuracy rate when confronted with those same six events. In short, the presence of an AMA can lead to vigilance decrements that can lead to errors in decision making.
Skitka, Linda J.↗
Cockpit Adaptive Automation and Pilot Performance
The introduction of high-level automated systems in the aircraft cockpit has provided several benefits, e.g., new capabilities, enhanced operational efficiency, and reduced crew workload. At the same time, conventional 'static' automation has sometimes degraded human operator monitoring performance, increased workload, and reduced situation awareness. Adaptive automation represents an alternative to static automation. In this approach, task allocation between human operators and computer systems is flexible and context-dependent rather than static. Adaptive automation, or adaptive task allocation, is thought to provide for regulation of operator workload and performance, while preserving the benefits of static automation. In previous research we have reported beneficial effects of adaptive automation on the performance of both pilots and non-pilots of flight-related tasks. For adaptive systems to be viable, however, such benefits need to be examined jointly in the context of a single set of tasks. The studies carried out under this project evaluated a systematic method for combining different forms of adaptive automation. A model for effective combination of different forms of adaptive automation, based on matching adaptation to operator workload was proposed and tested. The model was evaluated in studies using IFR-rated pilots flying a general-aviation simulator. Performance, subjective, and physiological (heart rate variability, eye scan-paths) measures of workload were recorded. The studies compared workload-based adaptation to to non-adaptive control conditions and found evidence for systematic benefits of adaptive automation. The research provides an empirical basis for evaluating the effectiveness of adaptive automation in the cockpit. The results contribute to the development of design principles and guidelines for the implementation of adaptive automation in the cockpit, particularly in general aviation, and in other human-machine systems. Project goals were met or exceeded. The results of the research extended knowledge of automation-related performance decrements in pilots and demonstrated the positive effects of adaptive task allocation. In addition, several practical implications for cockpit automation design were drawn from the research conducted. A total of 12 articles deriving from the project were published.
Parasuraman, Raja↗
A Comparison of a Brain-Based Adaptive System and a Manual Adaptable System for Invoking Automation
Two experiments are presented that examine alternative methods for invoking automation. In each experiment, participants were asked to perform simultaneously a monitoring task and a resource management task as well as a tracking task that changed between automatic and manual modes. The monitoring task required participants to detect failures of an automated system to correct aberrant conditions under either high or low system reliability. Performance on each task was assessed as well as situation awareness and subjective workload. In the first experiment, half of the participants worked with a brain-based system that used their EEG signals to switch the tracking task between automatic and manual modes. The remaining participants were yoked to participants from the adaptive condition and received the same schedule of mode switches, but their EEG had no effect on the automation. Within each group, half of the participants were assigned to either the low or high reliability monitoring task. In addition, within each combination of automation invocation and system reliability, participants were separated into high and low complacency potential groups. The results revealed no significant effects of automation invocation on the performance measures; however, the high complacency individuals demonstrated better situation awareness when working with the adaptive automation system. The second experiment was the same as the first with one important exception. Automation was invoked manually. Thus, half of the participants pressed a button to invoke automation for 10 s. The remaining participants were yoked to participants from the adaptable condition and received the same schedule of mode switches, but they had no control over the automation. The results showed that participants who could invoke automation performed more poorly on the resource management task and reported higher levels of subjective workload. Further, those who invoked automation more frequently performed more poorly on the tracking task and reported higher levels of subjective workload. and the adaptable condition in the second experiment revealed only one significant difference: the subjective workload was higher in the adaptable condition. Overall, the results show that a brain-based, adaptive automation system may facilitate situation awareness for those individuals who are more complacent toward automation. By contrast, requiring operators to invoke automation manually may have some detrimental impact on performance but does appear to increases subjective workload relative to an adaptive system.
Bailey, Nathan R.↗
Human-centered aircraft automation: A concept and guidelines
Aircraft automation is examined and its effects on flight crews. Generic guidelines are proposed for the design and use of automation in transport aircraft, in the hope of stimulating increased and more effective dialogue among designers of automated cockpits, purchasers of automated aircraft, and the pilots who must fly those aircraft in line operations. The goal is to explore the means whereby automation may be a maximally effective tool or resource for pilots without compromising human authority and with an increase in system safety. After definition of the domain of the aircraft pilot and brief discussion of the history of aircraft automation, a concept of human centered automation is presented and discussed. Automated devices are categorized as a control automation, information automation, and management automation. The environment and context of aircraft automation are then considered, followed by thoughts on the likely future of automation of that category.
Billings, Charles E.↗
Automation-induced monitoring inefficiency: role of display location
Operators can be poor monitors of automation if they are engaged concurrently in other tasks. However, in previous studies of this phenomenon the automated task was always presented in the periphery, away from the primary manual tasks that were centrally displayed. In this study we examined whether centrally locating an automated task would boost monitoring performance during a flight-simulation task consisting of system monitoring, tracking and fuel resource management sub-tasks. Twelve nonpilot subjects were required to perform the tracking and fuel management tasks manually while watching the automated system monitoring task for occasional failures. The automation reliability was constant at 87.5% for six subjects and variable (alternating between 87.5% and 56.25%) for the other six subjects. Each subject completed four 30 min sessions over a period of 2 days. In each automation reliability condition the automation routine was disabled for the last 20 min of the fourth session in order to simulate catastrophic automation failure (0 % reliability). Monitoring for automation failure was inefficient when automation reliability was constant but not when it varied over time, replicating previous results. Furthermore, there was no evidence of resource or speed accuracy trade-off between tasks. Thus, automation-induced failures of monitoring cannot be prevented by centrally locating the automated task.
Automation↗
Effects of adaptive task allocation on monitoring of automated systems
The effects of adaptive task allocation on monitoring for automation failure during multitask flight simulation were examined. Participants monitored an automated engine status task while simultaneously performing tracking and fuel management tasks over three 30-min sessions. Two methods of adaptive task allocation, both involving temporary return of the automated engine status task to the human operator ("human control"), were examined as a possible countermeasure to monitoring inefficiency. For the model-based adaptive group, the engine status task was allocated to all participants in the middle of the second session for 10 min, following which it was again returned to automation control. The same occurred for the performance-based adaptive group, but only if an individual participant's monitoring performance up to that point did not meet a specified criterion. For the nonadaptive control groups, the engine status task remained automated throughout the experiment. All groups had low probabilities of detection of automation failures for the first 40 min spent with automation. However, following the 10-min intervening period of human control, both adaptive groups detected significantly more automation failures during the subsequent blocks under automation control. The results show that adaptive task allocation can enhance monitoring of automated systems. Both model-based and performance-based allocation improved monitoring of automation. Implications for the design of automated systems are discussed.
Task Performance and Analysis↗
Performance consequences of automation-induced 'complacency'
The effect of variations in the reliability of an automated monitoring system on human operator detection of automation failures was examined in two experiments. For four 30-min sessions, 40 subjects performed an IBM PC-based flight simulation that included manual tracking and fuel-management tasks, as well as a system-monitoring task that was under automation control. Automation reliability - the percentage of system malfunctions detected by the automation routine - either remained constant at a low or high level over time or alternated every 10 min from low to high. Operator detection of automation failures was substantially worse for constant-reliability than for variable-reliability automation after about 20 min under automation control, indicating that the former condition induced 'complacency'. When system monitoring was the only task, detection was very efficient and was unaffected by variations in automation reliability. The results provide the first empirical evidence of the performance consequences of automation-induced 'complacency'. We relate findings to operator attitudes toward automation and discuss implications for cockpit automation design.
Parasuraman, Raja↗
Enabling Advanced Automation in Spacecraft Operations with the Spacecraft Emergency Response System
True autonomy is the Holy Grail of spacecraft mission operations. The goal of launching a satellite and letting it manage itself throughout its useful life is a worthy one. With true autonomy, the cost of mission operations would be reduced to a negligible amount. Under full autonomy, any problems (no matter the severity or type) that may arise with the spacecraft would be handled without any human intervention via some combination of smart sensors, on-board intelligence, and/or smart automated ground system. Until the day that complete autonomy is practical and affordable to deploy, incremental steps of deploying ever-increasing levels of automation (computerization of once manual tasks) on the ground and on the spacecraft are gradually decreasing the cost of mission operations. For example, NASA's Goddard Space Flight Center (NASA-GSFC) has been flying spacecraft with low cost operations for several years. NASA-GSFC's SMEX (Small Explorer) and MIDEX (Middle Explorer) missions have effectively deployed significant amounts of automation to enable the missions to fly predominately in 'light-out' mode. Under light-out operations the ground system is run without human intervention. Various tools perform many of the tasks previously performed by the human operators. One of the major issues in reducing human staff in favor of automation is the perceived increased in risk of losing data, or even losing a spacecraft, because of anomalous conditions that may occur when there is no one in the control center. When things go wrong, missions deploying advanced automation need to be sure that anomalous conditions are detected and that key personal are notified in a timely manner so that on-call team members can react to those conditions. To ensure the health and safety of its lights-out missions, NASA-GSFC's Advanced Automation and Autonomy branch (Code 588) developed the Spacecraft Emergency Response System (SERS). The SERS is a Web-based collaborative environment that enables secure distributed fault and resource management. The SERS incorporates the use of intelligent agents, threaded discussions, workflow, database connectivity, and links to a variety of communications devices (e.g., two-way paging, PDA's, and Internet phones) via commercial gateways. When the SERS detects a problem, it notifies on-call team members, who then can remotely take any necessary actions to resolve the anomalies.The SERS goes well beyond a simple '911' system that sends out an error code to everyone with a pager. Instead, SERS' software agents send detailed data (i.e., notifications) to the most appropriate team members based on the type and severity of the anomaly and the skills of the on-call team members. The SERS also allows the team members to respond to the notifications from their wireless devices. This unique capability ensures rapid response since the team members no longer have to go to a PC or the control center for every anomalous event. Most importantly, the SERS enables safe experimentation with various techniques for increasing levels of automation, leading to robust autonomy. For the MIDEX missions at NASA GSFC, the SERS is used to provide 'human-in-the-loop' automation. During lights-out operations, as greater control is given to the MIDEX automated systems, the SERS can be configured to page remote personnel and keep them informed regarding actions taking place in the control center. Remote off-duty operators can even be given the option of enabling or inhibiting a specific automated response in near real time via their two-way pagers. The SERS facilitates insertion of new technology to increase automation, while maintaining the safety and security of mission resources. This paper will focus on SERS' overall functionality and how SERS has been designed to handle the monitoring and emergency response for missions with varying levels of automation. The paper will also convey some of the key lessons learned from SERS' deployment across of variety of missions, highlighting this incremental approach to achieving 'robust autonomy'.
Breed, Julie↗
Team-Centered Perspective for Adaptive Automation Design
Automation represents a very active area of human factors research. The journal, Human Factors, published a special issue on automation in 1985. Since then, hundreds of scientific studies have been published examining the nature of automation and its interaction with human performance. However, despite a dramatic increase in research investigating human factors issues in aviation automation, there remain areas that need further exploration. This NASA Technical Memorandum describes a new area of automation design and research, called adaptive automation. It discusses the concepts and outlines the human factors issues associated with the new method of adaptive function allocation. The primary focus is on human-centered design, and specifically on ensuring that adaptive automation is from a team-centered perspective. The document shows that adaptive automation has many human factors issues common to traditional automation design. Much like the introduction of other new technologies and paradigm shifts, adaptive automation presents an opportunity to remediate current problems but poses new ones for human-automation interaction in aerospace operations. The review here is intended to communicate the philosophical perspective and direction of adaptive automation research conducted under the Aerospace Operations Systems (AOS), Physiological and Psychological Stressors and Factors (PPSF) project.
Prinzel, Lawrence J., III↗
Robotic and Human-Tended Collaborative Drilling Automation for Subsurface Exploration
Future in-situ lunar/martian resource utilization and characterization, as well as the scientific search for life on Mars, will require access to the subsurface and hence drilling. Drilling on Earth is hard - an art form more than an engineering discipline. Human operators listen and feel drill string vibrations coming from kilometers underground. Abundant mass and energy make it possible for terrestrial drilling to employ brute-force approaches to failure recovery and system performance issues. Space drilling will require intelligent and autonomous systems for robotic exploration and to support human exploration. Eventual in-situ resource utilization will require deep drilling with probable human-tended operation of large-bore drills, but initial lunar subsurface exploration and near-term ISRU will be accomplished with lightweight, rover-deployable or standalone drills capable of penetrating a few tens of meters in depth. These lightweight exploration drills have a direct counterpart in terrestrial prospecting and ore-body location, and will be designed to operate either human-tended or automated. NASA and industry now are acquiring experience in developing and building low-mass automated planetary prototype drills to design and build a pre-flight lunar prototype targeted for 2011-12 flight opportunities. A successful system will include development of drilling hardware, and automated control software to operate it safely and effectively. This includes control of the drilling hardware, state estimation of both the hardware and the lithography being drilled and state of the hole, and potentially planning and scheduling software suitable for uncertain situations such as drilling. Given that Humans on the Moon or Mars are unlikely to be able to spend protracted EVA periods at a drill site, both human-tended and robotic access to planetary subsurfaces will require some degree of standalone, autonomous drilling capability. Human-robotic coordination will be important, either between a robotic drill and humans on Earth, or a human-tended drill and its visiting crew. The Mars Analog Rio Tinto Experiment (MARTE) is a current project that studies and simulates the remote science operations between an automated drill in Spain and a distant, distributed human science team. The Drilling Automation for Mars Exploration (DAME) project, by contrast: is developing and testing standalone automation at a lunar/martian impact crater analog site in Arctic Canada. The drill hardware in both projects is a hardened, evolved version of the Advanced Deep Drill (ADD) developed by Honeybee Robotics for the Mars Subsurface Program. The current ADD is capable of 20m, and the DAME project is developing diagnostic and executive software for hands-off surface operations of the evolved version of this drill. The current drill automation architecture being developed by NASA and tested in 2004-06 at analog sites in the Arctic and Spain will add downhole diagnosis of different strata, bit wear detection, and dynamic replanning capabilities when unexpected failures or drilling conditions are discovered in conjunction with simulated mission operations and remote science planning. The most important determinant of future 1unar and martian drilling automation and staffing requirements will be the actual performance of automated prototype drilling hardware systems in field trials in simulated mission operations. It is difficult to accurately predict the level of automation and human interaction that will be needed for a lunar-deployed drill without first having extensive experience with the robotic control of prototype drill systems under realistic analog field conditions. Drill-specific failure modes and software design flaws will become most apparent at this stage. DAME will develop and test drill automation software and hardware under stressful operating conditions during several planned field campaigns. Initial results from summer 2004 tests show seven identifi distinct failure modes of the drill: cuttings-removal issues with low-power drilling into permafrost, and successful steps at executive control and initial automation.
Glass, Brian↗