Theses and dissertations

This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students. 

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Co-Bot Integration For High-Volume Manufacturing of Aerospace Components

Description

Over the years, American manufacturing has been offshored due to the competitive labor conditions in other countries. In addition, the COVID-19 pandemic exposed the fragility of the international supply chain, highlighting the importance of reshoring manufacturing and industry. However, reshoring alone cannot solve the underlying issues that caused offshoring in…

Over the years, American manufacturing has been offshored due to the competitive labor conditions in other countries. In addition, the COVID-19 pandemic exposed the fragility of the international supply chain, highlighting the importance of reshoring manufacturing and industry. However, reshoring alone cannot solve the underlying issues that caused offshoring in the first place, such as shortages of skilled labor and extensive regulation. To address these issues, the implementation and scaling of automation and Industry 4.0 technologies are necessary. The aerospace industry is a prime example of the need for skilled labor. Abiding by rigorous specifications and achieving the tight tolerances required by aerospace specifications is a highly specialized skill that requires experience and training. The shortage of skilled labor puts those working in aerospace at a disadvantage, often leading to long strenuous work hours to meet demand. To address this, a collaboration with two ASU manufacturing student research teams aided the development of two co-bot solutions that can work alongside technicians and operators to reduce downtime, increase efficiency, and free up human operators to focus on more complex tasks. While many automated solutions are available on the market, co-bots are not often used to their full capability. The proposed solutions demonstrate the possibilities of implementing co-bots in the aerospace industry by using them in machine tending and blending processes for aerospace parts. In traditional manufacturing processes, human operators are still responsible for performing repetitive and often mundane tasks, such as loading and removing workpieces from a CNC workstation and starting a CNC machine for repetitive parts. The current blending process requires a technician to manually sand damaged areas for Depot, Repair, and Overhaul (DRO), which is time-consuming and strenuous. By using a co-bot for this process, the technician's workload is significantly reduced, decreasing lead times and increasing quality control. Inspiration for this thesis came from observing the demands of companies like SpaceX, which require mass manufacturing of rocket engines to meet testing and launch schedules. The SpaceX Raptor engine is a complex, precise system that is aimed at being produced in high volume, which is a prime target for co-bot integration to help meet production targets. Implementing more co-bots into manufacturing has been shown to increase efficiency, reduce cost, and relieve stress on human operators. The integration of co-bots into the manufacturing process for the Raptor engine has the potential to improve efficiency and productivity, making high-volume manufacturing a possibility. Overall, the implementation of co-bots in the aerospace industry can offer a competitive advantage by increasing productivity and efficiency while reducing costs and relieving stress on human operators. This thesis provides proof of the possibilities of implementing co-bots in a versatile industry like aerospace and demonstrates the potential benefits of integrating co-bots into the manufacturing process for rocket engines like the Raptor. By doing so, the aerospace industry can move towards a more automated and efficient future, helping to address the challenges faced by American manufacturing today.
ContributorsMorse, Connor (Author) / Gintz, Jerry (Thesis director) / Hillary, Scott (Committee member) / Barrett, The Honors College (Contributor) / School of Manufacturing Systems and Networks (Contributor)
Created2023-05

Thesis CoBot Integration for High Volume Manufacturing.pdf

ContributorsMorse, Connor (Author) / Gintz, Jerry (Thesis director) / Hillary, Scott (Committee member) / Barrett, The Honors College (Contributor) / School of Manufacturing Systems and Networks (Contributor)
Created2023-05

Thesis Defense.pdf

ContributorsMorse, Connor (Author) / Gintz, Jerry (Thesis director) / Hillary, Scott (Committee member) / Barrett, The Honors College (Contributor) / School of Manufacturing Systems and Networks (Contributor)
Created2023-05
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Towards Energy­-efficient Visual Navigation: Sensor Quantization and Event­-based Vision Pipelines

Description
Visual navigation is a useful and important task for a variety of applications. As the preva­lence of robots increase, there is an increasing need for energy-­efficient navigation methods as well. Many aspects of efficient visual navigation algorithms have been implemented in the lit­erature, but there is a lack of work…

Visual navigation is a useful and important task for a variety of applications. As the preva­lence of robots increase, there is an increasing need for energy-­efficient navigation methods as well. Many aspects of efficient visual navigation algorithms have been implemented in the lit­erature, but there is a lack of work on evaluation of the efficiency of the image sensors. In this thesis, two methods are evaluated: adaptive image sensor quantization for traditional camera pipelines as well as new event­-based sensors for low­-power computer vision.The first contribution in this thesis is an evaluation of performing varying levels of sen­sor linear and logarithmic quantization with the task of visual simultaneous localization and mapping (SLAM). This unconventional method can provide efficiency benefits with a trade­ off between accuracy of the task and energy-­efficiency. A new sensor quantization method, gradient­-based quantization, is introduced to improve the accuracy of the task. This method only lowers the bit level of parts of the image that are less likely to be important in the SLAM algorithm since lower bit levels signify better energy­-efficiency, but worse task accuracy. The third contribution is an evaluation of the efficiency and accuracy of event­-based camera inten­sity representations for the task of optical flow. The results of performing a learning based optical flow are provided for each of five different reconstruction methods along with ablation studies. Lastly, the challenges of an event feature­-based SLAM system are presented with re­sults demonstrating the necessity for high quality and high­ resolution event data. The work in this thesis provides studies useful for examining trade­offs for an efficient visual navigation system with traditional and event vision sensors. The results of this thesis also provide multiple directions for future work.
ContributorsChristie, Olivia Catherine (Author) / Jayasuriya, Suren (Thesis advisor) / Chakrabarti, Chaitali (Committee member) / Yang, Yezhou (Committee member) / Arizona State University (Publisher)
Created2022
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Risk Management of Industrial Robot Systems

Description
As industries advance and automation becomes more prevalent, it is vital that safety remains at the forefront of discussions. To support this, Risk Management standards have been developed and adopted for both North American and International markets. Additionally, technical documents have been published to streamline risk management processes. Part of…

As industries advance and automation becomes more prevalent, it is vital that safety remains at the forefront of discussions. To support this, Risk Management standards have been developed and adopted for both North American and International markets. Additionally, technical documents have been published to streamline risk management processes. Part of these emerging technologies includes Collaborative robots, each with specific methods tailored to their capabilities. These standards offer guidance not only to end-users but also to Robot manufacturers, ensuring adherence to safety standards and providing methods for risk mitigation. The risk levels and categories are organized in a hierarchical structure, ranging from the most severe to negligible. Under these standards, the process involves identifying risks, mitigating them, validating the mitigation through verification, and solidifying the results. As technologies continue to evolve, it is essential for standards to evolve accordingly to ensure optimal safety levels when implemented correctly. Having effective risk management in place for all Industrial Robot Systems is paramount to reduce liability and protect both operators and assets. Detail key standards are that govern the realm of industrial robot systems for both north America and the rest if the world as well as highlight robot manufacturers adherence to the standards, response to safety, and how risk management can be applied.
ContributorsHall, Ammon (Author) / Gintz, Jerry (Thesis advisor) / Sugar, Thomas (Committee member) / Dehghan-Niri, Ehsan (Committee member) / Arizona State University (Publisher)
Created2024
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From SLAM to Spatial AI: Using Implicit 3D Latent Space Landmark Reconstruction for Robot Localization and Mapping

Description
Simultaneous localization and mapping (SLAM) has traditionally relied on low-level geometric or optical features. However, these features-based SLAM methods often struggle with feature-less or repetitive scenes. Additionally, low-level features may not provide sufficient information for robot navigation and manipulation, leaving robots without a complete understanding of the 3D spatial world.…

Simultaneous localization and mapping (SLAM) has traditionally relied on low-level geometric or optical features. However, these features-based SLAM methods often struggle with feature-less or repetitive scenes. Additionally, low-level features may not provide sufficient information for robot navigation and manipulation, leaving robots without a complete understanding of the 3D spatial world. Advanced information is necessary to address these limitations. Fortunately, recent developments in learning-based 3D reconstruction allow robots to not only detect semantic meanings, but also recognize the 3D structure of objects from a few images. By combining this 3D structural information, SLAM can be improved from a low-level approach to a structure-aware approach. This work propose a novel approach for multi-view 3D reconstruction using recurrent transformer. This approach allows robots to accumulate information from multiple views and encode them into a compact latent space. The resulting latent representations are then decoded to produce 3D structural landmarks, which can be used to improve robot localization and mapping.
ContributorsHuang, Chi-Yao (Author) / Yang, Yezhou (Thesis advisor) / Turaga, Pavan (Committee member) / Jayasuriya, Suren (Committee member) / Arizona State University (Publisher)
Created2023
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A Study on the Analysis of Treadmill Perturbation Data for the Design of Active Ankle Foot Orthosis to Prevent Falls and Gait Rehabilitation

Description
According to the Center for Disease Control and Prevention report around 29,668 United States residents aged greater than 65 years had died as a result of a fall in 2016. Other injuries like wrist fractures, hip fractures, and head injuries occur as a result of a fall. Certain groups of…

According to the Center for Disease Control and Prevention report around 29,668 United States residents aged greater than 65 years had died as a result of a fall in 2016. Other injuries like wrist fractures, hip fractures, and head injuries occur as a result of a fall. Certain groups of people are more prone to experience falls than others, one of which being individuals with stroke. The two most common issues with individuals with strokes are ankle weakness and foot drop, both of which contribute to falls. To mitigate this issue, the most popular clinical remedy given to these users is thermoplastic Ankle Foot Orthosis. These AFO's help improving gait velocity, stride length, and cadence. However, studies have shown that a continuous restraint on the ankle harms the compensatory stepping response and forward propulsion. It has been shown in previous studies that compensatory stepping and forward propulsion are crucial for the user's ability to recover from postural perturbations. Hence, there is a need for active devices that can supply a plantarflexion during the push-off and dorsiflexion during the swing phase of gait. Although advancements in the orthotic research have shown major improvements in supporting the ankle joint for rehabilitation, there is a lack of available active devices that can help impaired users in daily activities. In this study, our primary focus is to build an unobtrusive, cost-effective, and easy to wear active device for gait rehabilitation and fall prevention in individuals who are at risk. The device will be using a double-acting cylinder that can be easily incorporated into the user's footwear using a novel custom-designed powered ankle brace. The device will use Inertial Measurement Units to measure kinematic parameters of the lower body and a custom control algorithm to actuate the device based on the measurements. The study can be used to advance the field of gait assistance, rehabilitation, and potentially fall prevention of individuals with lower-limb impairments through the use of Active Ankle Foot Orthosis.
ContributorsRay, Sambarta (Author) / Honeycutt, Claire (Thesis advisor) / Dasarathy, Gautam (Thesis advisor) / Redkar, Sangram (Committee member) / Jayasuriya, Suren (Committee member) / Arizona State University (Publisher)
Created2020