Grado Department of Industrial and Systems Engineering
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Browsing Grado Department of Industrial and Systems Engineering by Content Type "Conference proceeding"
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- The 4th Workshop on Localization vs. Internationalization: Creating an International Survey on Automotive User InterfacesStojmenova, Kristina; Lee, Seul Chan; De Oliveira Faria, Nayara; Schroeter, Ronald; Jeon, Myounghoon (ACM, 2022-09-17)International surveys tend to collect data on attitudes, values and behaviors towards a specific topic from users from multiple countries, providing an insight on the differences and similarities across nations, cultures or geo-political structures. Consequently, international surveys provide important information about the diversity of the user's needs, values and preferences, which have to be taken into consideration when creating products and services as widely used as the personal automobile. The workshop will focus on the design and development of an international survey on automotive user interfaces on a global scale. It will try to identify the most important aspects related to automotive user interfaces, which should be addressed in the survey. It will also prepare a strategy for its international distribution and create a plan for comprehensive data collection. Lastly, it will try to outline venues and communication channels for the survey dissemination, with the goal of achieving wide visibility.
- 5G Opportunities in WarehousingAs capabilities of fifth generation wireless technology (5G) improve, adoption will go beyond current urban cellular networks into industrial settings enabling the IoT landscape. 5G primarily delivers value by enhancing mobile broadband through ultra-reliable, low-latency signals and massive machine-type communications. With the concurrent development of 5G and industrial automation, replacing Wi-Fi and LTE services with 5G networks offers an opportunity to enhance scheduling, latency, jitters, and redundancy in demanding applications. Additionally, the equipment redesigns and upgrades to operate in 5G will pave the way for innovation in operational strategies previously constrained by network capabilities. In this paper, we consider the warehouse operations and functions that are most likely to benefit from 5G adoption. The areas 5G will impact in warehousing are robotic operations, such as AGVs/AMRs; augmented reality devices for picking, training, and maintenance; inventory management through real time asset tracking; equipment battery life from network slicing; and data security. In general, the capacity and low-latency available through 5G will support continuous data transfer that is sufficient to support real-time analytics and decision-making. Knowing which functions will benefit most from 5G will provide strategic guidance for upgrading equipment and operations and aid in developing the factory of the future.
- Automating context dependent gaze metrics for evaluation of laparoscopic surgery manual skillsDeng, Shiyu; Kulkarni, Chaitanya; Parker, Sarah J.; Barnes, Laura E.; Wang, Tianzi; Hartman-Kenzler, Jacob; Safford, Shawn; Lau, Nathan (2022-03)
- Beyond Finding Change: multitemporal Landsat for forest monitoring and managementWynne, Randolph H.; Thomas, Valerie A.; Brooks, Evan B.; Coulston, J. O.; Derwin, Jill M.; Liknes, Greg C.; Yang, Z.; Fox, Thomas R.; Ghannam, S.; Abbott, A. Lynn; House, M. N.; Saxena, R.; Watson, Layne T.; Gopalakrishnan, Ranjith (2017-07)Take homes
- Tobler’s Law still in effect with time series – spatial autocorrelation in temporal coherence can help in both preprocessing and estimation
- Continual process improvement in extant algorithms needed
- Need additional means by which variations within (parameterization) and across algorithms addressed (the Reverend…)
- Time series improving higher order products (example with NLCD TCC) enabling near continuous monitoring
- Big Data, Smart Buildings, Post-Covid Office Real Estate Decision Making, and Multi-Disciplinary Undergraduate Learning: A Case Study in Discovery ThinkingKretser, Michael; Cherbaka, Natalie (2024-02-22)
- Changes in kinematics and muscle activity when learning to use a whole-body powered exoskeleton for stationary load handlingPark, Hanjun; Kim, Sunwook; Nussbaum, Maury A.; Srinivasan, Divya (SAGE, 2022-10-11)
- Changes in lower-limb joint torques when using a passive back-support exoskeleton for level walkingPark, Jang-Ho; Kim, Sunwook; Nussbaum, Maury A.; Srinivasan, Divya (SAGE, 2021-09)
- Cognitive Workload of Novice Forklift Truck Drivers in VR-based TrainingJamshid Nezhad Zahabi, Saman; Shafiqul Islam, Md; Kim, Sunwook; Lau, Nathan; Nussbaum, Maury A.; Lim, Sol (SAGE, 2023-10-19)There is increasing use of Virtual Reality (VR) to train forklift truck operators but a lack of sufficient understanding of how cognitive workload changes with respect to different task demands in VR-based training. In this study, 19 novice participants completed three forklift driving lessons with varying difficulty levels (low, medium, and high) using a VR simulator. To examine the effect of repeated training on cognitive workload, two sessions were repeated by participants using the same procedures. Cognitive workload was assessed with objective (electroencephalogram [EEG] activity) and subjective (NASA-TLX) measurements. EEG theta power and NASA-TLX (mental workload) scores were significantly higher for high than low difficulty levels. However, both EEG and NASA-TLX responses were reduced with repeated training in the second session. These findings highlight the effectiveness of EEG in continuous monitoring of workload variation caused by task difficulty and implementing training programs to moderate cognitive workload for forklift operators.
- Collaborative Multi-Robot Multi-Human Teams in Search and RescueWilliams, Ryan K.; Abaid, Nicole; McClure, James; Lau, Nathan; Heintzman, Larkin; Hashimoto, Amanda; Wang, Tianzi; Patnayak, Chinmaya; Kumar, Akshay (2022-04-30)Robots such as unmanned aerial vehicles (UAVs) deployed for search and rescue (SAR) can explore areas where human searchers cannot easily go and gather information on scales that can transform SAR strategy. Multi-UAV teams therefore have the potential to transform SAR by augmenting the capabilities of human teams and providing information that would otherwise be inaccessible. Our research aims to develop new theory and technologies for field deploying autonomous UAVs and managing multi-UAV teams working in concert with multi-human teams for SAR. Specifically, in this paper we summarize our work in progress towards these goals, including: (1) a multi-UAV search path planner that adapts to human behavior; (2) an in-field distributed computing prototype that supports multi-UAV computation and communication; (3) behavioral modeling that yields spatially localized predictions of lost person location; and (4) an interface between human searchers and UAVs that facilitates human-UAV interaction over a wide range of autonomy.
- Conversational Voice Agents are Preferred and Lead to Better Driving Performance in Conditionally Automated VehiclesWang, M.; Lee, S. C.; Montavon, G.; Qin, J.; Jeon, Myounghoon (ACM, 2022-09-17)In-vehicle intelligent agents (IVIAs) can provide versatile information on vehicle status and road events and further promote user perceptions such as trust. However, IVIAs need to be constructed carefully to reduce distraction and prevent unintended consequences like overreliance, especially when driver intervention is still required in conditional automation. To investigate the effects of speech style (informative vs. conversational) and embodiment (voice-only vs. robot) of IVIAs on driver perception and performance in conditionally automated vehicles, we recruited 24 young drivers to experience four driving scenarios in a simulator. Results indicated that although robot agents received higher system response accuracy and trust scores, they were not preferred due to great visual distraction. Conversational agents were generally favored and led to better takeover quality in terms of lower speed and smaller standard deviation of lane position. Our findings provide a valuable perspective on balancing user preference and subsequent user performance when designing IVIAs.
- Design of Gaze-Based Alarm Acknowledgement by Parameter CharacteristicsHerdt, Katherine; Lau, Nathan; Hilderbrant, Michael; Le, Tai; LeBlanc, Katya (Springer, 2022-06-16)Alarms in industrial control rooms are defined by their ability to alert an operator of abnormal events that require prompt response. However, when vigilant, operators may anticipate upcoming alarms, rendering those alarms less informative if not a nuisance. Three gaze-based alarm acknowledgement methods were designed by estimating operator awareness based on their eye fixations on the parameter/area of interest and parameter behavior shortly before the alarm. The three designs differed in acknowledging the types of parameter behaviors, which could be: a) near the alarm threshold, b) fluctuating drastically, or c) trending towards an alarm threshold. These three parameter behaviors correlate with increased visual sampling, which suggests higher operator awareness or expectation of alarms. In a simulator study comparing the three gaze-based acknowledgement methods against no gaze acknowledgement, 24 participants completed 24 trials of alarm monitoring task while maintaining a single parameter within a predefined range. Analysis of variance revealed that usability ratings were higher for conditions with than without gaze acknowledgements, demonstrating promise for this alarm management approach.
- Discussion Panel: Examining the perpetual issue of musculoskeletal disorders (MSDs) – Challenges, gaps, and opportunitiesBrooks, Lisa; Maikala, Rammohan V.; Reid, Christopher R.; Gallagher, Sean; Allread, Gary; McGowan, Blake; Fox, Robert R.; Nussbaum, Maury A. (SAGE, 2022-10-11)According to Injury Facts® data reported annually by the National Safety Council (NSC), overexertion (e.g., lifting, pushing, pulling, holding, or carrying objects) and bodily reactions have consistently been the leading cause of nonfatal injury or illness events involving days away from work. Likewise, overexertion topped the list of injury causes in the 2021 Liberty Mutual Workplace Safety Index, costing $13.3 billion in direct costs for businesses. Data from NSC, the Bureau of Labor Statistics, Liberty Mutual sources, and peer-reviewed research clearly emphasize the gravity of risk factors related to the worker, work, and workplace on MSD development. The NSC began a major initiative last year with a goal to examine the factors influence MSDs systematically. With the support of a major industry partner, it formed an international advisory council consisting of stakeholders from industry, academic, and research communities. The invited panel of experts, all members of this advisory council, will exchange their views on challenges, gaps, and opportunities to mitigate MSDs. These panelists will discuss various issues regarding research, translation, and work practice related to MSDs. Also emphasized will be knowledge gaps (e.g., causal mechanisms, pathophysiology, and MSD theories), opportunities for enhancing risk reduction through new assessment tools (e.g., mathematical models to predict the risk of injury), emerging technologies (e.g., wearable sensors and exoskeletons), and perspectives on future research/practice priorities.
- Drag-guided Diffusion Models for Vehicle Image GenerationArechiga, Nikos; Permenter, Frank; Song, Binyang; Yuan, Chenyang (2023-12-15)Denoising diffusion models trained at web-scale have revolutionized image generation. The application of these tools to engineering design holds promising potential but is currently limited by their inability to understand and adhere to concrete engineering constraints. In this paper, we take a step toward the goal of incorporating quantitative constraints into diffusion models by proposing physics-based guidance, which enables the optimization of a performance metric (as predicted by a surrogate model) during the generation process. As a proof-of-concept, we add drag guidance to Stable Diffusion, which allows this tool to generate images of novel vehicles while simultaneously minimizing their predicted drag coefficients.
- Effects of Arm-Support Exoskeletons on Kinematics and Subjective Assessments During a Static TaskOjelade, Aanuoluwapo; Kelson, Denean D.; Srinivasan, Divya D.; Kim, Sunwook S.; Smets, Marty; Nussbaum, Maury A. (Human Factors and Ergonomics Society, 2021-09)
- Effects of Back-support Exoskeletons on Task Performance and Usability During Simulated Construction-relevant TasksOjelade, Aanuoluwapo; Morris, Wallace; Kim, Sunwook; Harris-Adamson, Carisa; Barr, Alan; Nussbaum, Maury A. (SAGE, 2022-10-11)
- Examining senior drivers’ acceptance to advanced driver assistance systemsLiang, Dan; Antin, Jonathan F.; Lau, Nathan (2019-09-10)Advanced driver assistance systems (ADAS) can help maintain seniors’ safety and mobility with their decline in cognitive and physical capabilities. An early step of investigating the adoption and merits of ADAS for senior drivers is examining the factors that influence senior drivers’ acceptance of the technology. This paper presents our modeling effort on the acceptance of 18 senior drivers towards adaptive cruise control (ACC) and lane control features after six weeks of naturalistic driving with study vehicles. Adapting the Technology Acceptance Model (TAM), our model is built on questionnaire data on perceived usefulness (PU), perceived ease of use (PEoU), usebased trust (T) and perceived satisfaction (PS) in predicting behavioral intention to use (BIU) ADAS. Two major findings in our modeling effort are that (i) perceived ease of use has significant influence on trust and (ii) perceived satisfaction has significant influence on behavioral intention to use.
- Forklift Driving Performance of Novices with Repeated VR-based TrainingIslam, Md Shafiqul; Jamshid Nezhad Zahabi, Saman; Kim, Sunwook; Lau, Nathan; Nussbaum, Maury A.; Lim, Sol (SAGE, 2023-10-19)Virtual reality (VR) has emerged as a promising tool for training novice forklift drivers, but temporal patterns of such improvements are largely unknown. We trained 19 novice participants using an order-picker VR simulator on a selected driving lesson. In two sessions, participant driving performance was assessed using task completion time and kinematics of the head, shoulder, and lumbar spine via inertial measurement units (IMUs). Completion time and head flexion/movement decreased significantly (up to 22.4% and 31.5%, respectively). The observed changes in head motion (flexion/extension) indicate an initial adjustment period to prepare a mental model of the driving task and the control panel, which was also adapted over repeated trials. One implication of our results is that reduced head flexion/extension could be used as an indication of a novice driver’s improved skill during the early stages of training, in terms of familiarizing themselves with vehicle control and the vehicle control panel.
- Gait kinematics when learning to use a whole-body powered exoskeletonPark, Hanjun; Lee, Youngjae; Kim, Sunwook; Nussbaum, Maury A.; Srinivasan, Divya (SAGE, 2021-09)
- Generative Design for Manufacturing: Integrating Generation with Optimization Using a Guided Voxel Diffusion ModelSong, Binyang; Chilukuri, Premith Kumar; Kang, Sungku; Jin, Ran (2024)In digital manufacturing, converting advanced designs into quality products is hampered by manufacturers' limited design knowledge, restricting the adoption and enhancement of innovative solutions. This paper addresses this challenge through a novel generative denoising diffusion model (DDM) trained on historical 3D design data, enabling the creation of voxel-based designs that meet manufacturing standards. By integrating a surrogate model for evaluating the manufacturability of generated designs, the proposed DDM is able to optimize manufacturability during the generative process. This paper takes a leap forward from the predominant 2D focus of existing generative models towards 3D generative design, which not only broadens manufacturers' design capabilities but also accelerates the development of practical and optimized products. We demonstrate the efficacy of this approach via a case study on Microbial Fuel Cell (MFC) anode design, illustrating how this method can significantly enhance manufacturing workflows and outcomes. Our research offers a path for manufacturers to deepen their design expertise and foster innovation in digital manufacturing.
- Group Model Building Techniques for Rapid Elicitation of Parameter Values and Effect-Size-Driven FormulationsHosseinichimeh, Niyousha; MacDonald, Rod; Hyder, Ayaz; Ebrahimvandi, Alireza; Porter, Lauren; Reno, Becky; Maurer, Julie A.; Andersen, Deborah; Richardson, George; Hawley, Josh; Andersen, David F. (2017-02)Three parts to this presentation: Group Model Building and the Ohio Infant Mortality Project More Details on Rapid Elicitation of Parameters and Size Effects Advance Look at the Resultant Model as of Feb. 2017