Development of a standard framework for manufacturing simulators

Discrete event simulation is now a well established modelling and experimental technique for the analysis of manufacturing systems. Since it was first employed as a technique, much of the research and commercial developments in the field have been concerned with improving the considerable task of model specification in order to improve productivity and reduce the level of modelling and programming expertise required. The main areas of research have been the development of modelling structures to bring modularity in program development, incorporating such structures in simulation software systems which would alleviate some of the programming burden, and the use of automatic programming systems to develop interfaces that would raise the model specification to a higher level of abstraction. A more recent development in the field has been the advent of a new generation of software, often referred to as manufacturing simulators, which have incorporated extensive manufacturing system domain knowledge in the model specification interface. Many manufacturing simulators are now commercially available, but their development has not been based on any common standard. This is evident in the differences that exist between their interfaces, internal data representation methods and modelling capabilities. The lack of a standard makes it impossible to reuse any part of a model when a user finds it necessary to move from one simulator to another. In such cases, not only a new modelling language has to be learnt but also the complete model has to be developed again requiring considerable time and effort. The motivation for the research was the need for the development of a standard that is necessary to improve reusability of models and is the first step towards interchangability of such models. A standard framework for manufacturing simulators has been developed. It consists of a data model that is independent of any simulator, and a translation module for converting model specification data into the internal data representation of manufacturing simulators; the translators are application specific, but the methodology is common and illustrated for three popular simulators. The data model provides for a minimum common model data specification which is based on an extensive analysis of existing simulators. It uses dialogues for interface and the frame knowledge representation method for modular storage of data. The translation methodology uses production rules for data mapping

The Role Of Simulation In The SY2000 Initiative

Report on how simulation can be used in education because it approximates, replicates or emulates the features of some task, setting, or context

Training high performance skills using above real-time training

The Above Real-Time Training (ARTT) concept is a unique approach to training high performance skills. ARTT refers to a training paradigm that places the operator in a simulated environment that functions at faster than normal time. Such a training paradigm represents a departure from the intuitive, but not often supported, feeling that the best practice is determined by the training environment with the highest fidelity. This approach is hypothesized to provide greater 'transfer value' per simulation trial, by incorporating training techniques and instructional features into the simulator. These techniques allow individuals to acquire these critical skills faster and with greater retention. ARTT also allows an individual trained in 'fast time' to operate at what appears to be a more confident state, when the same task is performed in a real-time environment. Two related experiments are discussed. The findings appear to be consistent with previous findings that show positive effects of task variation during training. Moreover, ARTT has merit in improving or maintaining transfer with sharp reductions in training time. There are indications that the effectiveness of ARTT varies as a function of task content and possibly task difficulty. Other implications for ARTT are discussed along with future research directions

Payload training methodology study

The results of the Payload Training Methodology Study (PTMS) are documented. Methods and procedures are defined for the development of payload training programs to be conducted at the Marshall Space Flight Center Payload Training Complex (PCT) for the Space Station Freedom program. The study outlines the overall training program concept as well as the six methodologies associated with the program implementation. The program concept outlines the entire payload training program from initial identification of training requirements to the development of detailed design specifications for simulators and instructional material. The following six methodologies are defined: (1) The Training and Simulation Needs Assessment Methodology; (2) The Simulation Approach Methodology; (3) The Simulation Definition Analysis Methodology; (4) The Simulator Requirements Standardization Methodology; (5) The Simulator Development Verification Methodology; and (6) The Simulator Validation Methodology

Exploring the relationship between perceptual-cognitive function and driver safety : prediction and transfer

La conduite automobile continue d'être le mode de transport dominant dans le monde et le nombre de véhicules sur la route ne devrait qu’augmenter au cours des prochaines décennies. Dans un même temps, l'évolution démographique qui se produit actuellement dans le monde industrialisé implique que la proportion de conducteurs âgés sur la route devrait augmenter considérablement. L'âge s'accompagne de changements de grande envergure dans les systèmes physiques, sensoriels et cognitifs, entraînant des changements fonctionnels qui peuvent être subtils ou profonds. Nous commençons seulement à comprendre comment la variabilité normale et pathologique de ces mesures fonctionnelles affecte les performances de conduite et la sécurité. Le développement d'un outil fiable et fondé sur des données probantes pour distinguer les conducteurs prudents des conducteurs dangereux continue d'être une préoccupation majeure pour les chercheurs en gérontologie, en accidentologie et en clinique. L'accumulation de preuves suggère maintenant qu'il existe un lien important entre des capacités cognitives spécifiques telles que la vitesse de traitement de l’information et l'attention, et les performances de conduite. Continuer à explorer cette relation pour peut-être un jour développer un tel outil est une entreprise importante. Une autre implication de la relation entre les capacités cognitives et les performances de conduite est que les interventions conçues pour les améliorer ou les maintenir pourraient éventuellement améliorer ou maintenir la sécurité et le confort de conduite des individus à court et à long terme. L'objectif de cette thèse est triple. Premièrement, il développe et valide une nouvelle méthodologie pour évaluer les performances de conduite des jeunes adultes et des adultes plus âgés à l'aide de scénarios de simulation de conduite personnalisés. Deuxièmement, elle pousse l'état de nos connaissances sur la façon dont les capacités cognitives sont liées à la performance de conduite en démontrant que la performance sur un test intégratif d'attention dynamique et de vitesse de traitement - c'est-à-dire le suivi d'objets multiples en 3D (3D-MOT) - prédit les performances des conducteurs de différents groupes d'âge. Enfin, elle offre des preuves suggérant que la formation 3D-MOT améliore réellement la fonction attentionnelle et la vitesse de traitement en transférant la performance sur un test indépendant de ces capacités et, finalement, que cette amélioration pourrait se traduire par une amélioration des performances de conduite.Driving continues to be the world’s dominant form of transportation and the number of vehicles on the road is only projected to increase in the coming decades. At the same time, the demographic shift currently occurring in the industrialized world implies that the proportion of older adult drivers on the road is set to increase substantially. With age comes wide-ranging changes in physical, sensory and cognitive systems resulting in functional changes that can be subtle or profound. We are only beginning to understand how both normal and pathological variability in these functional measures affect driving performance and safety. Developing a reliable, evidence-based tool to distinguish safe from unsafe drivers continues to be a major preoccupation for gerontology, accidentology, and clinical researchers alike. Accumulating evidence now suggests that there is an important link between specific cognitive abilities such as speed-of-processing, attention, and driving performance. Continuing to explore this relationship in order to perhaps one day develop such a tool is an important endeavour. Another implication of the relationship between cognitive abilities and driving performance is that interventions designed to improve or sustain these might conceivably enhance or maintain individuals’ driving safety and comfort in the short- and long-term. The purpose of this thesis is threefold. First, it develops and validates a novel methodology for assessing both young adult and older adult driving performance using custom driving simulator scenarios. Second, it pushes the state of our knowledge of how cognitive abilities relate to driving performance by demonstrating that performance on an integrative test of dynamic attention and speed-of-processing—i.e., 3-dimensional multiple object tracking (3D-MOT)— predicts how drivers of different age groups perform. Finally, it offers evidence to suggest that training 3D-MOT actually enhances attentional function and speed-of-processing by transferring to performance on an unrelated test of these abilities and, ultimately, that this improvement might translate to improved driving performance

Determinants of Aviation Students’ Intentions to Use Virtual Reality for Flight Training

Immersive simulation technology has been incorporated into numerous training environments, including medicine, engineering, and marketing. The aviation industry, in particular, has a history of embracing technology to enhance training and has especially regulated the requirements of devices for flight training. Virtual reality (VR) is the newest technology being adapted for training purposes. Many educational institutions training providers are incorporating virtual environments (VE) and VR systems into curricula and training programs to expand educational opportunities, enhance learning, promote deep cognitive learning, and leverage the abilities of a generation of students who have adopted technology from an early age. As VR is adopted for educational purposes, researchers are conducting experiments to learning with the VE occurs at an equal or greater level than in the real world. However, research surrounding students’ perceptions of the technology and intentions to use it for training has been neglected. This is especially true in the realm of aviation and flight training. The goal of this research was to determine the factors that influence aviation students’ intention to use VR for flight training. An extended Technology Acceptance Model (TAM) was developed that incorporates elements of the Theory of Planned Behavior (TPB); factors derived from relevant, validated extended TAMs; and new factors that are theorized to impact use intention. These factors are related to aviation education, the use of VR technology in training environments, and using VR for flight training. The new model may explain flight students’ acceptance of VR for flight training as well as their intent to use the technology. A quantitative research method with a cross-sectional survey design was utilized. Descriptive statistical analysis, a confirmatory factor analysis (CFA), and a structural equation modeling (SEM) process were employed. Data were collected from aviation students enrolled in FAA-approved Part 141 pilot schools in early 2020 using a survey design. Results indicated a good model fit to answer the three research questions of the study. There were 14 hypotheses in the original model. Although one was removed, an additional relationship was discovered, validated, and added to the model. Nine of the hypotheses were supported. Eight of the nine predictor factors of the model were determined to directly or indirectly impact behavioral intention (BI). The original TAM factors had the strongest relationships. Relationships between factors particularly relevant to VR technology and aviation training were also supported. The results of the study fill a gap in the research surrounding the use of VR for flight training and the influencing factors of behavioral intention. The model may also be modified for other educational and training environments as well as other forms of immersive simulation technology

Report of the committee on a commercially developed space facility

Major facilities that could support significant microgravity research and applications activity are discussed. The ground-based facilities include drop towers, aircraft flying parabolic trajectories, and sounding rockets. Facilities that are intrinsically tied to the Space Shuttle range from Get-Away-Special canisters to Spacelab long modules. There are also orbital facilities which include recoverable capsules launched on expendable launch vehicles, free-flying spacecraft, and space stations. Some of these existing, planned, and proposed facilities are non-U.S. in origin, but potentially available to U.S. investigators. In addition, some are governmentally developed and operated whereas others are planned to be privately developed and/or operated. Tables are provided to show the facility, developer, duration, estimated gravity level, crew interaction, flight frequency, year available, power to payload, payload volume, and maximum payload mass. The potential of direct and indirect benefits of manufacturing in space are presented

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 288)

This bibliography lists 190 reports, articles and other documents introduced into the NASA scientific and technical information system in August 1986

Acquisition, retention and transfer of heavy equipment operator skills through simulator training

Initiatives and collaborations among heavy construction equipment manufacturing companies and training technology firms to develop and employ simulators for varied training purposes are becoming commonplace. However, human factors research on simulator training for operators of construction equipment is still sparse. For simulator training to be effective, it is necessary to understand how skills are learned using the simulator, how those skills are transferred to other tasks, devices, and real scenarios, and how well skills are retained after simulator training. ^ This research is on skill development, specifically as it applies to operator training for two specific types of heavy construction equipment: excavator and wheel loader. It aims at decomposing the complexity of equipment operation and distinguishing the skills to be acquired for each machine. It consists of five studies, three conducted with students at Purdue and two with expert operators at John Deere. ^ Study 1 investigated whether operation of a simulated hydraulic excavator is influenced by an intervening task performed between initial practice on the excavator and a subsequent retention test using a controls familiarization task (which involves just knowing the control functions). Two intervening tasks were inserted: practicing on a simulated loader, and reading an unrelated text intended to distract the participants. Performance on the simulator was compared against that of a group of participants who practiced on the simulated excavator throughout. The results showed no performance cost attributable to inserting practice on the simulated loader while learning the controls on the simulated excavator. The learning trends, however, prompted the question of whether the same results would bear true for learning a more complex perceptual-motor task. ^ Study 2 was intended to verify whether the alternating equipment sequence yields the same outcome for a more complex truck loading task that involves multiple operations. Besides the two experimental groups (control and loader groups) in Study 1, an additional group which was given practice on the two machines (but with a different practice schedule from the original loader group) was added to address the question of whether the duration of practice on an alternative machine affects performance on the previously learned machine. The number of sessions was also increased, from three to five, to examine the possible influence when participants continue to switch between the machines. Those participants who engaged in intervening practice on the simulated loader showed a smaller performance improvement on learning the truck loading task on the simulated excavator than did the control group who practiced on the simulated excavator for all five sessions. This outcome confirms that the controls familiarization tasks on both machines studied in the preliminary study may have been too simple for the full effects of switching between the machines to be evident. This finding of continued skill improvement upon return to the previously practiced machine inspires consideration of concurrent simulator-based training rather than the practice of learning to operate only one machine at a time. ^ Study 3 analyzed skill transfer using hierarchical task analysis (HTA) to investigate the degree of overlap in specific task components by studying the similarity and dissimilarity of the truck loading task performed in Study 2 on excavator and wheel loader simulators. After the modification and verification by operators of the initial HTAs, the finalized HTAs revealed that the lack of positive transfer found in performing the truck loading task alternately with the excavator and loader was likely due to the differences between loader and excavator in terms of the controls, physical constraints, and the explicit goals and subgoals of the task. In addition, comparing the number of levels of subgoals of HTAs did not evidence any level-of-difficulty differences between tasks. ^ Studies 4 and 5 investigated whether there is a cost when switching between different types of training modules within the same machine. Study 4 was conducted with experienced operators, who provided information on how the four selected tasks on the loader should be performed and classified the perceived difficulty level of each. Verbal protocol analysis was used to decompose the tasks of the four training modules on the loader simulator: 1) Simple Bucket Loading (B1), Filling a Trench (B2), Truck Loading (B3), and Fork Lifting (F). A nine phase, systematic method for deriving the HTAs from the think-aloud protocols was also developed in this study, which successfully generated the four HTAs. The findings show that 1) the HTA of the Fork Lifting module is significantly different than those of the three bucket loading tasks, and 2) although all three bucket loading tasks shared a similar mechanism, the operators ranked B1 as the easiest, followed by B2 and then B3 due to the corresponding accessibility of the dump targets, and fork lifting was ranked as the most difficult task. The results were used to justify the hypotheses for Study 5. ^ Study 5 sought to verify whether an alternating practice sequence within the same machine, i.e. training with an alternative tool (a wide fork) and returning to the original learned tool (a bucket) on a loader simulator, yields better skill transfer and retention (after a one-week interval). Four groups of undergraduate students were tested. Two groups were given two tasks involving bucket loading to practice in the first two sessions, whereas the other two groups were given a bucket loading task in the first session and the fork lifting task in the second session. The transfer and retention tasks both involved a bucket loading task that had not been performed in Sessions 1 and 2. The results showed that the groups who were assigned to practice on two tasks involving the manipulation of buckets performed better in the skill transfer test when the new task was introduced that also involved manipulation of the bucket. The results support thespecificity of training principle (for which the practice conditions match the test conditions and thus facilitate retention or transfer) but not the progressive difficulty training principle (for which difficulty impedes performance in the learning stage but facilitates retention). It is suggested that, when training perceptual-motor tasks, tasks practiced during the learning phase should match the transfer task. Manipulation of task difficulty may play a role only if the tasks share task-relevant cognitive processes and mental models. ^ The overall findings of this research provide: 1) better understanding of skill development for the operation of construction equipment, and 2) evidence as to how the trainees can better utilize their time when training on a single machine and concurrently on multiple machines. The findings add to the general body of knowledge on perceptual-motor skill acquisition and to that on training in a specific domain via a specific technology. The findings are expected to generalize to heavy equipment training in related domains, such as forestry and mining, and domains requiring instrument handling skills and robotic arms, such as surgery and orbital space vessel external operations