Operations Research, Systems Engineering and Industrial Engineering Commons^™

Scheduling, Complexity, And Solution Methods For Space Robot On-Orbit Servicing, Susan E. Sorenson

Graduate Theses and Dissertations

This research proposes problems, models, and solutions for the scheduling of space robot on-orbit servicing. We present the Multi-Orbit Routing and Scheduling of Refuellable On-Orbit Servicing Space Robots problem which considers on-orbit servicing across multiple orbits with moving tasks and moving refuelling depots. We formulate a mixed integer linear program model to optimize the routing and scheduling of robot servicers to accomplish on-orbit servicing tasks. We develop and demonstrate flexible algorithms for the creation of the model parameters and associated data sets. Our first algorithm creates the network arcs using orbital mechanics. We have also created a novel way to …

Deep Learning Applications In Industrial And Systems Engineering, Winthrop Harvey

Graduate Theses and Dissertations

Deep learning - the use of large neural networks to perform machine learning - has transformed the world. As the capabilities of deep models continue to grow, deep learning is becoming an increasingly valuable and practical tool for industrial engineering. With its wide applicability, deep learning can be turned to many industrial engineering tasks, including optimization, heuristic search, and functional approximation. In this dissertation, the major concepts and paradigms of deep learning are reviewed, and three industrial engineering projects applying these methods are described. The first applies a deep convolutional network to the task of absolute aerial geolocalization - the …

Supervised Representation Learning For Improving Prediction Performance In Medical Decision Support Applications, Phawis Thammasorn

Graduate Theses and Dissertations

Machine learning approaches for prediction play an integral role in modern-day decision supports system. An integral part of the process is extracting interest variables or features to describe the input data. Then, the variables are utilized for training machine-learning algorithms to map from the variables to the target output. After the training, the model is validated with either validation or testing data before making predictions with a new dataset. Despite the straightforward workflow, the process relies heavily on good feature representation of data. Engineering suitable representation eases the subsequent actions and copes with many practical issues that potentially prevent the …

Implementing The Cms+ Sports Rankings Algorithm In A Javafx Environment, Luke Welch

Industrial Engineering Undergraduate Honors Theses

Every year, sports teams and athletes get cut from championship opportunities because of their rank. While this reality is easier to swallow if a team or athlete is distant from the cut, it is much harder when they are right on the edge. Many times, it leaves fans and athletes wondering, “Why wasn’t I ranked higher? What factors when into the ranking? Are the rankings based on opinion alone?” These are fair questions that deserve an answer. Many times, sports rankings are derived from opinion polls. Other times, they are derived from a combination of opinion polls and measured performance. …

A Machine Learning Approach To Understanding Emerging Markets, Namita Balani

Graduate Theses and Dissertations

Logistic providers have learned to efficiently serve their existing customer bases with optimized routes and transportation resource allocation. The problem arises when there is potential for logistics growth in an emerging market with no previous data. The purpose of this work is to use industry data for previously known and well-documented markets to apply data analytic techniques such as machine learning to investigate the uncertainty in a new market. The thesis looks into machine learning techniques to predict miles per stop given historical data. It mainly focuses on Random Forest Regression Analysis, but concludes that additional techniques, such as Polynomial …

Scheduling Allocation And Inventory Replenishment Problems Under Uncertainty: Applications In Managing Electric Vehicle And Drone Battery Swap Stations, Amin Asadi

Graduate Theses and Dissertations

In this dissertation, motivated by electric vehicle (EV) and drone application growth, we propose novel optimization problems and solution techniques for managing the operations at EV and drone battery swap stations. In Chapter 2, we introduce a novel class of stochastic scheduling allocation and inventory replenishment problems (SAIRP), which determines the recharging, discharging, and replacement decisions at a swap station over time to maximize the expected total profit. We use Markov Decision Process (MDP) to model SAIRPs facing uncertain demands, varying costs, and battery degradation. Considering battery degradation is crucial as it relaxes the assumption that charging/discharging batteries do not …

Towards A Cyber-Physical Manufacturing Cloud Through Operable Digital Twins And Virtual Production Lines, Md Rakib Shahriar

Graduate Theses and Dissertations

In last decade, the paradigm of Cyber-Physical Systems (CPS) has integrated industrial manufacturing systems with Cloud Computing technologies for Cloud Manufacturing. Up to 2015, there were many CPS-based manufacturing systems that collected real-time machining data to perform remote monitoring, prognostics and health management, and predictive maintenance. However, these CPS-integrated and network ready machines were not directly connected to the elements of Cloud Manufacturing and required human-in-the-loop. Addressing this gap, we introduced a new paradigm of Cyber-Physical Manufacturing Cloud (CPMC) that bridges a gap between physical machines and virtual space in 2017. CPMC virtualizes machine tools in cloud through web services …

Automatic Methods To Enhance The Quality Of Colonoscopy Video, Nidhal Kareem Shukur Azawi

Graduate Theses and Dissertations

Colonoscopy is a form of endoscopy because it uses colonoscopy device to help the doctor to understand a colon patient. Enhancing the quality of Colonoscopy images is a challenge because of the wet and dynamic environment inside the colon causes many problems even the colonoscope devise has a good quality. Some of these problems are blurriness, specular highlights shiny areas.

In this work, different kinds of techniques have been investigated in order to improve the quality of colonoscopy images. Also, variety of preprocessing approaches (removing bad images, resizing images, median filtration with and without image resizing) have been conducted to …

Fault Adaptive Workload Allocation For Complex Manufacturing Systems, Charlie B. Destefano

Graduate Theses and Dissertations

This research proposes novel fault adaptive workload allocation (FAWA) strategies for the health management of complex manufacturing systems. The primary goal of these strategies is to minimize maintenance costs and maximize production by strategically controlling when and where failures occur through condition-based workload allocation.

For complex systems that are capable of performing tasks a variety of different ways, such as an industrial robot arm that can move between locations using different joint angle configurations and path trajectories, each option, i.e. mission plan, will result in different degradation rates and life-expectancies. Consequently, this can make it difficult to predict when a …

Collaborative Robotic Path Planning For Industrial Spraying Operations On Complex Geometries, Steven Brown

Graduate Theses and Dissertations

Implementation of automated robotic solutions for complex tasks currently faces a few major hurdles. For instance, lack of effective sensing and task variability – especially in high-mix/low-volume processes – creates too much uncertainty to reliably hard-code a robotic work cell. Current collaborative frameworks generally focus on integrating the sensing required for a physically collaborative implementation. While this paradigm has proven effective for mitigating uncertainty by mixing human cognitive function and fine motor skills with robotic strength and repeatability, there are many instances where physical interaction is impractical but human reasoning and task knowledge is still needed. The proposed framework consists …

Locating And Protecting Facilities Subject To Random Disruptions And Attacks, Hugh Medal

Graduate Theses and Dissertations

Recent events such as the 2011 Tohoku earthquake and tsunami in Japan have revealed the vulnerability of networks such as supply chains to disruptive events. In particular, it has become apparent that the failure of a few elements of an infrastructure system can cause a system-wide disruption. Thus, it is important to learn more about which elements of infrastructure systems are most critical and how to protect an infrastructure system from the effects of a disruption. This dissertation seeks to enhance the understanding of how to design and protect networked infrastructure systems from disruptions by developing new mathematical models and …