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Operations Research, Systems Engineering and Industrial Engineering
- Keyword
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- Anomaly Detection (1)
- Bio-signals (1)
- Condition Monitoring (CM) (1)
- Deep Learning (DL) (1)
- Distributed Acoustic Sensing (DAS) (1)
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- Estimation Model (1)
- Finite element analysis (FEA) (1)
- Functional Data Analysis (1)
- High Tonnage Loop (HTL) (1)
- Human Driver (1)
- Mental Workload (1)
- Optimizing systems;Sensitivity analysis;Simulation of human-robot collaboration;Simulation of manual labour;Simulation of robotics automation;White button mushroom harvesting (1)
- Psycho-physiological (1)
- Railroad (1)
- Railroad Safety (1)
Articles 1 - 3 of 3
Full-Text Articles in Engineering
Development Of A High-Level Discrete Event Simulation Model For The Harvesting Of White Button Mushrooms With Human-Robot Collaboration (Hrc), Ava Recchia
Electronic Theses and Dissertations
Canada is a leading global mushroom producer, with the white button mushroom (Agaricus bisporus) being the most popular type produced. Harvesting activities are labour-intensive, and farms are currently experiencing labour shortages, which are impacting productivity, growth, and overall revenue. Robotic technologies are valid mechanisms for mushroom harvesting and demonstrate a potential to reduce this gap. Examining the performance of a harvesting system with different robotics scenarios, such as manual, robotics automation, and human robot collaboration (HRC) is crucial to realizing this potential. Simulation models are useful tools for testing and assessing systems without making any physical change to the system. …
Applying Functional Data Analysis To Estimate The Mental Workload Of The Human Driver, David Olorunfemi Eniyandunmo
Applying Functional Data Analysis To Estimate The Mental Workload Of The Human Driver, David Olorunfemi Eniyandunmo
Electronic Theses and Dissertations
Recent studies have focused on accurately estimating mental workload using machine learning algorithms and extracting features from psycho-physiological measures. However, feature extraction leads to the loss of valuable information and often results in binary classifications that lack specificity in the identification of optimum mental workload levels. This study investigates the feasibility of using raw psycho-physiological data (EEG, facial EMG, ECG, EDA, pupillometry) combined with Functional Data Analysis (FDA) to estimate mental workload of human drivers. A driving scenario with five tasks was employed, and subjective ratings were collected using the modified Bedford workload scale. Results demonstrate that the FDA applied …
Railroad Condition Monitoring Using Distributed Acoustic Sensing And Deep Learning Techniques, Md Arifur Rahman
Railroad Condition Monitoring Using Distributed Acoustic Sensing And Deep Learning Techniques, Md Arifur Rahman
Electronic Theses and Dissertations
Proper condition monitoring has been a major issue among railroad administrations since it might cause catastrophic dilemmas that lead to fatalities or damage to the infrastructure. Although various aspects of train safety have been conducted by scholars, in-motion monitoring detection of defect occurrence, cause, and severity is still a big concern. Hence extensive studies are still required to enhance the accuracy of inspection methods for railroad condition monitoring (CM). Distributed acoustic sensing (DAS) has been recognized as a promising method because of its sensing capabilities over long distances and for massive structures. As DAS produces large datasets, algorithms for precise …