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Articles 1 - 12 of 12
Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
Analysis Of The Psychological And Production Effects Of The Use Of Gamification For Manufacturing Assembly, Makenzie Dolly
Analysis Of The Psychological And Production Effects Of The Use Of Gamification For Manufacturing Assembly, Makenzie Dolly
Graduate Theses, Dissertations, and Problem Reports
In this dissertation, the applications of gamification for manufacturing with a focus on effects to workers and productivity were studied. Gamification is a relatively new research area, with the term being officially defined in 2010. Since then, several fields (education, health, and marketing) have benefitted from its application. Despite exhibiting strong potential, the application of gamification had remained rather unexplored in the manufacturing domain. To explore this further, by employing a comprehensive literature review, four research gaps were identified: the need for i) the use and acceptance of Deterding’s definition of gamification, ii) a clearer definition for various game element …
Accelerating Manufacturing Decisions Using Bayesian Optimization: An Optimization And Prediction Perspective, Taofeeq Olajire
Accelerating Manufacturing Decisions Using Bayesian Optimization: An Optimization And Prediction Perspective, Taofeeq Olajire
Graduate Theses, Dissertations, and Problem Reports
Manufacturing is a promising technique for producing complex and custom-made parts with a high degree of precision. It can also provide us with desired materials and products with specified properties. To achieve that, it is crucial to find out the optimum point of process parameters that have a significant impact on the properties and quality of the final product. Unfortunately, optimizing these parameters can be challenging due to the complex and nonlinear nature of the underlying process, which becomes more complicated when there are conflicting objectives, sometimes with multiple goals. Furthermore, experiments are usually costly, time-consuming, and require expensive materials, …
A Comparative Analysis Of Coastdown Testing Methods From An Electric Drive Unit Engagement Perspective Using A Student-Designed Parallel Hybrid Electric Vehicle, Dawson Everett Dunnuck
A Comparative Analysis Of Coastdown Testing Methods From An Electric Drive Unit Engagement Perspective Using A Student-Designed Parallel Hybrid Electric Vehicle, Dawson Everett Dunnuck
Graduate Theses, Dissertations, and Problem Reports
Coastdown testing and road load determination are pivotal parts of the automotive design process. Vehicle manufacturers and independent companies perform and analyze road loads determined through a coastdown or similar method to determine a vehicle’s road load for modeling and EPA certification. For a traditional coastdown, the vehicle’s drivetrain must be disconnected through a clutch between the engine and the transmission while traveling at a high rate of speed to place the vehicle in neutral. This changes for hybrid and electric vehicles. Some hybrid, and most electric, vehicles delivered to customers do not have this clutch action to grant the …
Framework For Data Acquisition And Fusion Of Camera And Radar For Autonomous Vehicle Systems, Clay Edward Vincent
Framework For Data Acquisition And Fusion Of Camera And Radar For Autonomous Vehicle Systems, Clay Edward Vincent
Graduate Theses, Dissertations, and Problem Reports
The primary contribution is the development of the data collection testing methodology for autonomous driving systems of a hybrid electric passenger vehicle. As automotive manufacturers begin to develop adaptive cruise control technology in vehicles, progress is being made toward the development of fully-autonomous vehicles. Adaptive cruise control capability is classified into five levels defined by the Society of Automotive Engineering. Some vehicles under development have attained higher levels of autonomy, but the focus of most commercial development is Level 2 autonomy. As the level of autonomy increases, the sensor technology becomes more advanced with a sensor suite which includes radar, …
Dynamic Modeling, Data Reconciliation, Parameter Estimation, And Health Monitoring Of A Supercritical Power Plant, Katherine Grace Hedrick
Dynamic Modeling, Data Reconciliation, Parameter Estimation, And Health Monitoring Of A Supercritical Power Plant, Katherine Grace Hedrick
Graduate Theses, Dissertations, and Problem Reports
With the introduction of a larger portion of renewable sources of power coming onto the U.S. power grid in recent decades, the operational strategy of coal-fired power plants has changed significantly to focus more on flexibility in response to the changing energy market. This has naturally led to different operational challenges. Many of these challenges are focused on the boilers within these plants, as they are producing more emissions and experiencing increased damage during load-following, which in turn leads to increased costs from penalties for not achieving emission standards or maintenance costs as boilers accumulate damage from the cycling behavior. …
Spatio-Temporal Deep Learning Approaches For Addressing Track Association Problem Using Automatic Identification System (Ais) Data, Md Asif Bin Syed
Spatio-Temporal Deep Learning Approaches For Addressing Track Association Problem Using Automatic Identification System (Ais) Data, Md Asif Bin Syed
Graduate Theses, Dissertations, and Problem Reports
In the realm of marine surveillance, track association constitutes a pivotal yet challenging task, involving the identification and tracking of unlabelled vessel trajectories. The need for accurate data association algorithms stems from the urge to spot unusual vessel movements or threat detection. These algorithms link sequential observations containing location and motion information to specific moving objects, helping to build their real-time trajectories. These threat detection algorithms will be useful when a vessel attempts to conceal its identity. The algorithm can then identify and track the specific vessel from its incoming signal. The data for this study is sourced from the …
Improving The Health And Safety Of Manufacturing Workers By Detecting And Addressing Personal Protective Equipment (Ppe) Violations In Real-Time With The Use Of Automated Ppe Detection Technology, Joseph Olufemi Fasinu
Improving The Health And Safety Of Manufacturing Workers By Detecting And Addressing Personal Protective Equipment (Ppe) Violations In Real-Time With The Use Of Automated Ppe Detection Technology, Joseph Olufemi Fasinu
Graduate Theses, Dissertations, and Problem Reports
The Centers for Disease Control and Prevention (CDC) emphasized that Personal Protective Equipment (PPE) can significantly reduce the risk of occupational injuries and illnesses. However, improper use, failure to use, and other PPE-related violations can still result in injuries and fatalities. Eye and face protection violation has been one of the top 10 most frequently violated OSHA standards in fiscal years 2018, 2019, 2020, 2021 and 2022 consecutively. A common practice among safety professionals to ensure PPE compliance has been to physically inspect or monitor PPE usage among workers, which has been found to be unsustainable on a continuous real-time …
Techno-Economic Analysis And Optimization Of Hydrogen And Mechanical Energy Storage Systems, Pavitra Senthamilselvan Sengalani
Techno-Economic Analysis And Optimization Of Hydrogen And Mechanical Energy Storage Systems, Pavitra Senthamilselvan Sengalani
Graduate Theses, Dissertations, and Problem Reports
The increasing significance of renewable energy sources is thrusting the load cycling of fossil-fueled power plants (FFPP), designed to operate under nominal-load conditions. Integration of energy storage systems (ESS) with the FFPPs such as hydrogen energy storage (HES) and mechanical energy storage facility such as compressed air energy storage (CAES) shows the potential to minimize the levelized cost of electricity during high demand scenarios and also minimize the negative impacts of off-design FFPP operation. The deployment of energy storage facilities at the FFPP level have considerable potential advantages as they can be exploited within the existing equipment items and facilities …
Physics Infused Lstm Network For Track Association Based On Marine Vessel Automatic Identification System Data, Tasmiah Haque
Physics Infused Lstm Network For Track Association Based On Marine Vessel Automatic Identification System Data, Tasmiah Haque
Graduate Theses, Dissertations, and Problem Reports
In marine surveillance, a crucial task is distinguishing between normal and abnormal vessel movements to timely identify potential threats. Subsequently, the vessels need to be monitored and tracked until necessary action can be taken. To achieve this, a track association problem is formulated where multiple vessels' unlabeled geographic and motion parameters are associated with their true labels. These parameters are typically obtained from the Automatic Identification System (AIS) database, which enables real-time tracking of marine vessels equipped with AIS. The parameters are time-stamped and collected over a long period, and therefore, modeling the inherent temporal patterns in the data is …
A Machine Learning Approach For Early Diagnosis Of Transthyretin Amyloid Cardiomyopathy Among Heart Failure Patients, Tanjim Ahmed
A Machine Learning Approach For Early Diagnosis Of Transthyretin Amyloid Cardiomyopathy Among Heart Failure Patients, Tanjim Ahmed
Graduate Theses, Dissertations, and Problem Reports
Transthyretin Amyloid Cardiomyopathy (ATTR-CM) is a rare, progressive, and fatal disease. Prevalence of ATTR-CM ranges from 4 to 17 per 100000 cases where the mean survival time is less than 4 years. It has a history of being underdiagnosed and misdiagnosed. The diagnosis delay has a weighted mean of 6.1 years for wild-type ATTR-CM. Low awareness, the necessity of invasive procedures, and lack of treatment are the key reasons for delayed diagnosis. But, with the introduction of non-invasive tests like nuclear scintigraphy with 99mTC-PYP and the disease modifying drug Tafamidis, the diagnosis delay signifies a missed opportunity to increase …
Evaluating Electrification Of Fossil Fuel-Fired Boilers For Decarbonization Using Discrete Event Simulation, Nahian Ismail Chowdhury
Evaluating Electrification Of Fossil Fuel-Fired Boilers For Decarbonization Using Discrete Event Simulation, Nahian Ismail Chowdhury
Graduate Theses, Dissertations, and Problem Reports
Decarbonizing fossil fuel usage is crucial in mitigating the impacts of climate change. CO2, which comprises the major portion of greenhouse gas, is emitted from burning fossil fuels. One of the significant sources of fossil fuel user is industrial process heating, and most of the heating in industrial processes is achieved through boilers. Electrification is a promising solution for decarbonizing these boilers, as it enables renewable energy sources to generate electricity, which can then be used to power the electric boilers. The electrification of boilers can reduce greenhouse gas emissions, improve air quality, and increase energy efficiency. However, it requires …
Energy Digital Twins In Smart Manufacturing Systems, Anna Billey
Energy Digital Twins In Smart Manufacturing Systems, Anna Billey
Graduate Theses, Dissertations, and Problem Reports
In this thesis, an Energy Digital Twin for smart manufacturing systems was developed and evaluated. In particular, the study focused on bidirectional parameter communication between the physical and the virtual part with the aim of optimizing the energy used in the manufacturing process. Rising costs and the environmental impacts related to energy consumption have grown in importance worldwide. There are elevated concerns in sectors like manufacturing, leading to an urgent quest to reduce energy consumption. A recent advancement in Industry 4.0 technology, the Digital Twin, represents a promising smart technology and tool that researchers are investigating to help reduce energy …