Scholarly Works, Industrial and Systems Engineering

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  • Human-AI Collaborative Innovation in Design
    Song, Binyang; Zhu, Qihao; Luo, Jianxi (2024)
    Human-AI collaboration (HAIC) is a promising strategy to transform engineering design and innovation, yet how to design artificial intelligence (AI) to boost HAIC remains unclear. Accordingly, this paper provides a new, unified, and comprehensive scheme for classifying AI roles. On this basis, we develop an AI design framework that outlines expected AI capabilities, interactive attributes, and trust enablers across various HAIC scenarios, offering guidance for integrating AI into human teams effectively. We also discuss current advancements, challenges, and prospects for future research.
  • Data-driven Car Drag Coefficient Prediction with Depth and Normal Renderings
    Song, Binyang; Yuan, Chenyang; Permenter, Frank; Arechiga, Nikos; Ahmed, Faez (American Society of Mechanical Engineers, 2024)
    Generative AI models have made significant progress in automating the creation of 3D shapes, which has the potential to transform car design. In engineering design and optimization, evaluating engineering metrics is crucial. To make generative models performance-aware and enable them to create high-performing designs, surrogate modeling of these metrics is necessary. However, the currently used representations of 3D shapes either require extensive computational resources to learn or suffer from significant information loss, which impairs their effectiveness in surrogate modeling. To address this issue, we propose a new 2D representation of 3D shapes. We develop a surrogate drag model based on this representation to verify its effectiveness in predicting 3D car drag. We construct a diverse dataset of 4,535 high-quality 3D car meshes labeled by drag coefficients computed from computational fluid dynamics simulations to train our model. Our experiments demonstrate that our model can accurately and efficiently evaluate drag coefficients with an R^2 value above 0.84 for various car categories. Our model is implemented using deep neural networks, making it compatible with recent AI image generation tools (such as Stable Diffusion) and a significant step towards the automatic generation of drag-optimized car designs. Moreover, we demonstrate a case study using the proposed surrogate model to guide a diffusion-based deep generative model for drag-optimized car body synthesis. We have made the dataset and code publicly available at https://decode.mit.edu/projects/dragprediction.
  • Generative Design for Manufacturing: Integrating Generation with Optimization Using a Guided Voxel Diffusion Model
    Song, 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.
  • Drag-guided Diffusion Models for Vehicle Image Generation
    Arechiga, 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.
  • Teleoperator-Robot-Human Interaction in Manufacturing: Perspectives from Industry, Robot Manufacturers, and Researchers
    Kim, Sunwook; Hernandez, Ivan; Nussbaum, Maury A.; Lim, Sol (Informa, 2024-02-08)
    OCCUPATIONAL APPLICATIONS: Industrial robots have become an important aspect in modern industry. In the context of human-robot collaboration, enabling teleoperated robots to work in close proximity to local/onsite humans can provide new opportunities to improve human engagement in a distributed workplace. Interviews with industry stakeholders highlighted several potential benefits of such teleoperator-robot-human collaboration (tRHC), including the application of tRHC to tasks requiring both expertise and manual dexterity (e.g., maintenance and highly skilled tasks in sectors including construction, manufacturing, and healthcare), as well as opportunities to expand job accessibility for individuals with disabilities and older individuals. However, interviewees also indicated potential challenges of tRHC, particularly related to human perception (e.g., perceiving remote environments), safety, and trust. Given these challenges, and the current limited information on the practical value and implementation of tRHC, we propose several future research directions, with a focus on human factors and ergonomics, to help realize the potential benefits of tRHC.
  • Influences of backpack loading on recovery from anterior and posterior losses of balance: An exploratory investigation
    Pitts, Jessica; Komisar, Vicki; Elmblad, Kayley; Smith, Alyssa; Verbrigghe, Derek; Siko, Carly; Nussbaum, Maury A.; Duncan, Carolyn A. (Elsevier, 2024-05-01)
    Backpacks are common devices for carrying external posterior loads. However, relatively little is known about how these external loads affect the ability to recover from balance loss. In this exploratory investigation, 16 young adults (8 female, 8 male) performed forward and backward lean-and-release balance recovery trials, while wearing a backpack that was unloaded or loaded (at 15% of individual body weight). We quantified the effects of backpack loading on balance recovery in terms of maximum recoverable lean angles, center-of-mass kinematics, and temporal-spatial stepping characteristics. Mean values of maximum lean angles were 20° and 9° in response to forward and backward perturbations, respectively. These angles significantly decreased when wearing the additional load for only backward losses of balance. During backward losses of balance, the additional load decreased peak center-of-mass velocity and increased acceleration by ∼10 and 18% respectively, which was accompanied by ∼5% faster stepping responses and steps that were ∼9% longer, 11% higher, and had an ∼10% earlier onset. Thus, wearing a backpack decreases backward balance recovery ability and changes backward recovery stepping characteristics.
  • Trunk postural control during unstable sitting among individuals with and without low back pain: A systematic review with an individual participant data meta-analysis
    Alshehri, Mansour A.; Alzahrani, Hosam; van den Hoorn, Wolbert; Klyne, David M.; Vette, Albert H.; Hendershot, Brad D.; Roberts, Brad W. R.; Larivière, Christian; Barbado, David; Vera-Garcia, Francisco J.; van Dieen, Jaap H.; Cholewicki, Jacek; Nussbaum, Maury A.; Madigan, Michael L.; Reeves, Norman Peter; Silfies, Sheri P.; Brown, Stephen H. M.; Hodges, Paul W. (Public Library of Science (PLoS), 2024-01-24)
    Introduction Sitting on an unstable surface is a common paradigm to investigate trunk postural control among individuals with low back pain (LBP), by minimizing the influence lower extremities on balance control. Outcomes of many small studies are inconsistent (e.g., some find differences between groups while others do not), potentially due to confounding factors such as age, sex, body mass index [BMI], or clinical presentations. We conducted a systematic review with an individual participant data (IPD) meta-analysis to investigate whether trunk postural control differs between those with and without LBP, and whether the difference between groups is impacted by vision and potential confounding factors. Methods We completed this review according to PRISMA-IPD guidelines. The literature was screened (up to 7th September 2023) from five electronic databases: MEDLINE, CINAHL, Embase, Scopus, and Web of Science Core Collection. Outcome measures were extracted that describe unstable seat movements, specifically centre of pressure or seat angle. Our main analyses included: 1) a two-stage IPD meta-analysis to assess the difference between groups and their interaction with age, sex, BMI, and vision on trunk postural control; 2) and a two-stage IPD meta-regression to determine the effects of LBP clinical features (pain intensity, disability, pain catastrophizing, and fear-avoidance beliefs) on trunk postural control. Results Forty studies (1,821 participants) were included for the descriptive analysis and 24 studies (1,050 participants) were included for the IPD analysis. IPD meta-analyses revealed three main findings: (a) trunk postural control was worse (higher root mean square displacement [RMSdispl], range, and long-term diffusion; lower mean power frequency) among individuals with than without LBP; (b) trunk postural control deteriorated more (higher RMSdispl, shortand long-term diffusion) among individuals with than without LBP when vision was removed; and (c) older age and higher BMI had greater adverse impacts on trunk postural control (higher short-term diffusion; longer time and distance coordinates of the critical point) among individuals with than without LBP. IPD meta-regressions indicated no associations between the limited LBP clinical features that could be considered and trunk postural control. Conclusion Trunk postural control appears to be inferior among individuals with LBP, which was indicated by increased seat movements and some evidence of trunk stiffening. These findings are likely explained by delayed or less accurate corrective responses.
  • Why Similar Policies Resulted In Different COVID-19 Outcomes: How Responsiveness And Culture Influenced Mortality Rates
    Lim, Tse Yang; Xu, Ran; Ruktanonchai, Nick; Saucedo, Omar; Childs, Lauren M.; Jalali, Mohammad S.; Rahmandad, Hazhir; Ghaffarzadegan, Navid (Health Affairs, 2023-12)
    In the first two years of the COVID-19 pandemic, per capita mortality varied by more than a hundredfold across countries, despite most implementing similar nonpharmaceutical interventions. Factors such as policy stringency, gross domestic product, and age distribution explain only a small fraction of mortality variation. To address this puzzle, we built on a previously validated pandemic model in which perceived risk altered societal responses affecting SARS-CoV-2 transmission. Using data from more than 100 countries, we found that a key factor explaining heterogeneous death rates was not the policy responses themselves but rather variation in responsiveness. Responsiveness measures how sensitive communities are to evolving mortality risks and how readily they adopt nonpharmaceutical interventions in response, to curb transmission.We further found that responsiveness correlated with two cultural constructs across countries: uncertainty avoidance and power distance. Our findings show that more responsive adoption of similar policies saves many lives, with important implications for the design and implementation of responses to future outbreaks.
  • Identifying sensors-based parameters associated with fall risk in community-dwelling older adults: an investigation and interpretation of discriminatory parameters
    Wang, Xuan; Cao, Junjie; Zhao, Qizheng; Chen, Manting; Luo, Jiajia; Wang, Hailiang; Yu, Lisha; Tsui, Kwok-Leung; Zhao, Yang (2024-02-01)
    Background: Falls pose a severe threat to the health of older adults worldwide. Determining gait and kinematic parameters that are related to an increased risk of falls is essential for developing effective intervention and fall prevention strategies. This study aimed to investigate the discriminatory parameter, which lay an important basis for developing effective clinical screening tools for identifying high-fall-risk older adults. Methods: Forty-one individuals aged 65 years and above living in the community participated in this study. The older adults were classified as high-fall-risk and low-fall-risk individuals based on their BBS scores. The participants wore an inertial measurement unit (IMU) while conducting the Timed Up and Go (TUG) test. Simultaneously, a depth camera acquired images of the participants’ movements during the experiment. After segmenting the data according to subtasks, 142 parameters were extracted from the sensor-based data. A t-test or Mann-Whitney U test was performed on the parameters for distinguishing older adults at high risk of falling. The logistic regression was used to further quantify the role of different parameters in identifying high-fall-risk individuals. Furthermore, we conducted an ablation experiment to explore the complementary information offered by the two sensors. Results: Fifteen participants were defined as high-fall-risk individuals, while twenty-six were defined as low-fall-risk individuals. 17 parameters were tested for significance with p-values less than 0.05. Some of these parameters, such as the usage of walking assistance, maximum angular velocity around the yaw axis during turn-to-sit, and step length, exhibit the greatest discriminatory abilities in identifying high-fall-risk individuals. Additionally, combining features from both devices for fall risk assessment resulted in a higher AUC of 0.882 compared to using each device separately. Conclusions: Utilizing different types of sensors can offer more comprehensive information. Interpreting parameters to physiology provides deeper insights into the identification of high-fall-risk individuals. High-fall-risk individuals typically exhibited a cautious gait, such as larger step width and shorter step length during walking. Besides, we identified some abnormal gait patterns of high-fall-risk individuals compared to low-fall-risk individuals, such as less knee flexion and a tendency to tilt the pelvis forward during turning.
  • Interactive stories through robot musical theater for preschoolers’ STEAM education
    Choi, Koeun; Yu, Shuqi; Kim, Jisun; Dong, Jia; Lee, Yeaji; Haines, Chelsea; Newbill, Phyllis; Upthegrove, Tanner; Wyatt, Ariana; Jeon, Myonghoon (2022)
  • What Do You Want for In-Vehicle Agents? One Fits All vs. Multiple Specialized Agents
    Park, Se Hyeon; Lee, Seul Chan; Wang, Manhua; Hock, Philipp; Baumann, Martin; Jeon, Myounghoon (ACM, 2022-09-17)
    It is expected that in-vehicle intelligent agents (IVIAs) become an important user interface in automated driving, and much research on how to design IVIAs considering user needs and scenarios has been conducted. The question arising here is whether people want to have one almighty agent connecting to all user's data sources and dealing with all situations, including driving contexts. Another plausible form is multiple specialized agents that play the role only in each task context. As a first step in answering the question, we developed two plausible scenarios of interacting with IVIAs and presented the video. In both scenarios, a user of IVIAs experiences embarrassing situations because of the connectivity of IVIAs. We expect that this effort can be a starting point to understand users' needs and requirements to develop and design IVIAs in terms of connectivity.
  • The 4th Workshop on Localization vs. Internationalization: Creating an International Survey on Automotive User Interfaces
    Stojmenova, 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.
  • Asymmetries in Potential for Partisan Gerrymandering
    Goedert, Nicholas; Hildebrand, Robert; Travis, Laurel; Pierson, Matthew (2024)
    This paper investigates the effectiveness of potential partisan gerrymandering of the U.S. House of Representatives across a range of states. We use a heuristic algorithm to generate district maps that optimize for multiple objectives, including compactness, partisan benefit, and competitiveness. While partisan gerrymandering is highly effective for both sides, we find that the majority of states are moderately biased toward Republicans when optimized for either compactness or partisan benefit, meaning that Republican gerrymanders have the potential to be more effective. However, we also find that more densely populated and more heavily Hispanic states show less Republican bias or even Democratic bias. Additionally, we find that in almost all cases we can generate reasonably compact maps with very little sacrifice to partisan objectives through a mixed objective function. This suggests that there is a strong potential for stealth partisan gerrymanders that are both compact and beneficial to one party. Nationwide, partisan gerrymandering is capable of swinging over one hundred seats in the U.S. House, even when compact districts are simultaneously sought.
  • Construction inspection & monitoring with quadruped robots in future human-robot teaming: A preliminary study
    Halder, Srijeet; Afsari, Kereshmeh; Chiou, Erin; Patrick, Rafael; Hamed, Kaveh Akbari (Elsevier, 2023-04-15)
    Construction inspection and monitoring are key activities in construction projects. Automation of inspection tasks can address existing limitations and inefficiencies of the manual process to enable systematic and consistent construction inspection. However, there is a lack of an in-depth understanding of the process of construction inspection and monitoring and the tasks and sequences involved to provide the basis for task delegation in a human-technology partnership. The purpose of this research is to study the conventional process of inspection and monitoring of construction work currently implemented in construction projects and to develop an alternative process using a quadruped robot as an inspector assistant to overcome the limitations of the conventional process. This paper explores the use of quadruped robots for construction inspection and monitoring with an emphasis on a human-robot teaming approach. Technical development and testing of the robotic technology are not in the scope of this study. The results indicate how inspector assistant quadruped robots can enable a human-technology partnership in future construction inspection and monitoring tasks. The research was conducted through on-site experiments and observations of inspectors during construction inspection and monitoring followed by a semi-structured interview to develop a process map of the conventional construction inspection and monitoring process. The study also includes on-site robot training and experiments with the inspectors to develop an alternative process map to depict future construction inspection and monitoring work with the use of an inspector assistant quadruped robot. Both the conventional and alternative process maps were validated through interview surveys with industry experts against four criteria including, completeness, accuracy, generalizability, and comprehensibility. The findings suggest that the developed process maps reflect existing and future construction inspection and monitoring work.
  • Taxonomy and definition of audio augmented reality (AAR): A grounded theory study
    Dam, Abhraneil; Siddiqui, Arsh; Leclercq, Charles; Jeon, Myounghoon (Academic Press - Elsevier, 2024-02)
    AR applications have mostly considered visual augmentations while excluding other modalities. Recent developments in audio augmented reality (AAR) applications have been based on the definitions of visual AR or mixed reality (MR), and thus, AAR technology development has lacked systematic efforts. We investigated the concept of augmented reality through audio to provide a systematic understanding and generate a taxonomy and a definition for AAR. A conference workshop (N = 28), focus groups (N = 18), and expert interviews (N = 6) generated qualitative data regarding the concept of AAR. Grounded Theory (GT) was used to analyze the data and produce a new taxonomy and a definition. The AAR taxonomy consists of three categories – Environment Connected, Goal Directed, and Context Adapted, with three subcategories respectively. The need for a separate taxonomy for AAR is highlighted to aid in the development of AAR applications in a systematic manner. The taxonomy is expected to be used as a heuristic tool that can guide developers to build AAR applications and can be used in evaluating user experience with AAR applications.
  • Generative Agent-Based Modeling: Unveiling Social System Dynamics through Coupling Mechanistic Models with Generative Artificial Intelligence
    Ghaffarzadegan, Navid; Majumdar, Aritra; Williams, Ross; Hosseinichimeh, Niyousha (2024-01)
    We discuss the emerging new opportunity for building feedback-rich computational models of social systems using generative artificial intelligence. Referred to as Generative Agent-Based Models (GABMs), such individual-level models utilize large language models to represent human decision-making in social settings. We provide a GABM case in which human behavior can be incorporated in simulation models by coupling a mechanistic model of human interactions with a pre-trained large language model. This is achieved by introducing a simple GABM of social norm diffusion in an organization. For educational purposes, the model is intentionally kept simple. We examine a wide range of scenarios and the sensitivity of the results to several changes in the prompt. We hope the article and the model serve as a guide for building useful dynamic models of various social systems that include realistic human reasoning and decision-making.
  • Effects of using passive back- and arm-support exoskeletons for cart pushing and pulling
    Park, Hanjun; Noll, Alex; Kim, Sunwook; Nussbaum, Maury A. (SAGE Publications, 2023-10-20)
    Though studies have shown both BSEs and ASEs are effective in reducing physical demands for various manual material handling tasks, limited evidence is currently available on their effects in pushing and pulling tasks. We evaluated the impacts of using a passive back-support (BSE) and an arm-support exoskeleton (ASE) on trunk kinematics, and the back and arm musculature for pushing and pulling of a moderately loaded (100 kg) cart. Fourteen volunteers performed cart the tasks, each of whom was randomly assigned one of the exoskeletons (BSE or ASE). Wearing the BSE substantially reduced lumbar muscle activity during both pushing (up to ~39%) and pulling (up to ~35%) compared to not wearing EXOs, while wearing an ASE had no significant impacts. For the anterior deltoid muscle, neither BSE nor ASE had beneficial impacts. Findings from the current study help to understand the effects of BSEs and ASEs in pushing and pulling tasks.
  • Effects of Back-support Exoskeletons on Task Performance and Perceived Exertion During Construction-related Tasks: Differences related to Experience
    Ojelade, Aanuoluwapo; Kim, Sunwook; Morris, Wallace; Harris-Adamson, Carisa; Barr, Alan; Nussbaum, Maury A. (SAGE Publications, 2023-10-24)
    The effects of three Back-support Exoskeletons (BSEs) on task performance (completion time) and perceived exertion were examined during simulated construction tasks. Forty participants (20 novices) completed the tasks using no BSE and three BSEs, each with two support settings (On and Off). There were significant main and interaction effects of Experience level on both outcome measures. Using BSEs negatively affected task performance for some tasks, though these effects were smaller among experienced participants. Interestingly, using BSEs inconsistently affected perceived physical effort, possibly due to the characteristics of the tasks, BSE designs, and experience levels. These results indicate that the effects of BSE on task performance and perceived physical effort are specific to experience level, BSE designs, and task demands. Further study is needed to better understand how to generalize these results to the actual work population.
  • A data-driven approach to understand factors contributing to exoskeleton use-intention in construction
    Kim, Sunwook; Moore, Albert; Ojelade, Aanuoluwapo; Gutierrez, Nancy; Harris-Adamson, Carisa; Barr, Alan; Srinivasan, Divya; Nussbaum, Maury A. (SAGE Publications, 2023-10-25)
    Work-related musculoskeletal disorders (WMSDs) remain an important heath concern for construction workers. Occupational exoskeletons (EXOs) are a new ergonomic intervention to control WMSD risk, yet their adoption has been low in construction. We explored contributing factors to EXO use-intention, by building a decision tree to predict the intention to try an exoskeleton using responses to an online survey. Variable selection and hyperparameter tuning were used respectively to reduce the number of potential predictors, and for a better prediction performance. Performance was assessed using four common metrics. The importance of variables in the final tree was calculated to understand which variable had a greater influence. The final tree had moderate prediction performance. Important variables identified were associated with opinions on EXO use, demographics, job demands, and perceived potential risks. The key influential variables were EXOs becoming standard equipment and fatigue reduction with EXO use. Practical implications of the findings are discussed.
  • Generating synthetic as-built additive manufacturing surface topography using progressive growing generative adversarial networks
    Seo, Junhyeon; Rao, Prahalada; Raeymaekers, Bart (2023-12-04)
    Numerically generating synthetic surface topography that closely resembles the features and characteristics of experimental surface topography measurements reduces the need to perform these intricate and costly measurements. However, existing algorithms to numerically generated surface topography are not well-suited to create the specific characteristics and geometric features of as-built surfaces that result from laser powder bed fusion (LPBF), such as partially melted metal particles, porosity, laser scan lines, and balling. Thus, we present a method to generate synthetic as-built LPBF surface topography maps using a progressively growing generative adversarial network. We qualitatively and quantitatively demonstrate good agreement between synthetic and experimental as-built LPBF surface topography maps using areal and deterministic surface topography parameters, radially averaged power spectral density, and material ratio curves. The ability to accurately generate synthetic as-built LPBF surface topography maps reduces the experimental burden of performing a large number of surface topography measurements. Furthermore, it facilitates combining experimental measurements with synthetic surface topography maps to create large data-sets that facilitate, e.g. relating as-built surface topography to LPBF process parameters, or implementing digital surface twins to monitor complex end-use LPBF parts, amongst other applications.