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Operations Research, Systems Engineering and Industrial Engineering Commons

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Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering

An Investigation Into Applications Of Canonical Polyadic Decomposition & Ensemble Learning In Forecasting Thermal Data Streams In Direct Laser Deposition Processes, Jonathan Storey Dec 2023

An Investigation Into Applications Of Canonical Polyadic Decomposition & Ensemble Learning In Forecasting Thermal Data Streams In Direct Laser Deposition Processes, Jonathan Storey

Theses and Dissertations

Additive manufacturing (AM) is a process of creating objects from 3D model data by adding layers of material. AM technologies present several advantages compared to traditional manufacturing technologies, such as producing less material waste and being capable of producing parts with greater geometric complexity. However, deficiencies in the printing process due to high process uncertainty can affect the microstructural properties of a fabricated part leading to defects. In metal AM, previous studies have linked defects in parts with melt pool temperature fluctuations, with the size of the melt pool and the scan pattern being key factors associated with part defects. …


Ai-Enabled Modeling And Monitoring Of Data-Rich Advanced Manufacturing Systems, Abdullah Al Mamun Aug 2023

Ai-Enabled Modeling And Monitoring Of Data-Rich Advanced Manufacturing Systems, Abdullah Al Mamun

Theses and Dissertations

The infrastructure of cyber-physical systems (CPS) is based on a meta-concept of cybermanufacturing systems (CMS) that synchronizes the Industrial Internet of Things (IIoTs), Cloud Computing, Industrial Control Systems (ICSs), and Big Data analytics in manufacturing operations. Artificial Intelligence (AI) can be incorporated to make intelligent decisions in the day-to-day operations of CMS. Cyberattack spaces in AI-based cybermanufacturing operations pose significant challenges, including unauthorized modification of systems, loss of historical data, destructive malware, software malfunctioning, etc. However, a cybersecurity framework can be implemented to prevent unauthorized access, theft, damage, or other harmful attacks on electronic equipment, networks, and sensitive data. The …


Assessing And Predicting The Students’ Systems Thinking Preference: Multi-Criteria Decision Making And Machine Learning, Siham Tazzit Aug 2023

Assessing And Predicting The Students’ Systems Thinking Preference: Multi-Criteria Decision Making And Machine Learning, Siham Tazzit

Theses and Dissertations

The 21st century is marked by a technological revolution that features digital implementation and high interconnectivity between systems across different domains, such as transportation, agriculture, education, and health. Although these technological changes resulted in modern systems capable of easing individuals’ lives, these systems are increasingly complex, and that increased complexity is only expected to continue. The increased system complexity is due to the rapid exchange of information between subsystems, which creates high interconnectivity and interdependence between the subsystems and their elements. Workforce skill sets, as a result, must be modified appropriately to ensure the systems’ success. Systems Thinking is an …


Distributionally Robust Unsupervised Domain Adaptation And Its Applications In 2d And 3d Image Analysis, Yibin Wang Aug 2023

Distributionally Robust Unsupervised Domain Adaptation And Its Applications In 2d And 3d Image Analysis, Yibin Wang

Theses and Dissertations

Obtaining ground-truth label information from real-world data along with uncertainty quantification can be challenging or even infeasible. In the absence of labeled data for a certain task, unsupervised domain adaptation (UDA) techniques have shown great accomplishment by learning transferable knowledge from labeled source domain data and adapting it to unlabeled target domain data, yet uncertainties are still a big concern under domain shifts. Distributionally robust learning (DRL) is emerging as a high-potential technique for building reliable learning systems that are robust to distribution shifts. In this research, a distributionally robust unsupervised domain adaptation (DRUDA) method is proposed to enhance the …


A Generalizable Method And Case Application For Development And Use Of The Aviation Systems – Trust Survey (As-Ts)., Jamison Hicks May 2023

A Generalizable Method And Case Application For Development And Use Of The Aviation Systems – Trust Survey (As-Ts)., Jamison Hicks

Theses and Dissertations

Automated systems are integral in the development of modern aircraft, especially for complex military aircraft. Pilot Trust in Automation (TIA) in these systems is vital for optimizing the pilot-vehicle interface and ensuring pilots use the systems appropriately to complete required tasks.

The objective of this research was to develop and validate a TIA scale and survey methodology to identify and mitigate trust deficiencies with automated systems for use in Army Aviation testing. There is currently no standard TIA assessment methodology for U.S. Army aviation pilots that identifies trust deficiencies and potential mitigations.

A comprehensive literature review was conducted to identify …


Passive Vs. Active Wearable Technology Monitoring Trunk Flexion In Elementary Teachers, Bailey Jose May 2023

Passive Vs. Active Wearable Technology Monitoring Trunk Flexion In Elementary Teachers, Bailey Jose

Theses and Dissertations

The objective of this study was to assess the biomechanical and subjective measures of elementary school teachers while wearing active and/or passive wearable devices during the average workday. Five elementary school teachers wore a harness that held an Upright GO 2 posture tracking device and a Vicon Blue Trident sensor on the participant's upper back for two school days. Haptic feedback was on for one day and off for the other. Data from the Vicon wearable was analyzed to determine participants’ trunk flexion severity, frequency, and duration. Surveys were used to determine perceived exertion and perception of wearable technology. This …


Adaptive Large Neighborhood Search Algorithm – Performance Evaluation Under Parallel Schemes & Applications, Sandip Kumar May 2023

Adaptive Large Neighborhood Search Algorithm – Performance Evaluation Under Parallel Schemes & Applications, Sandip Kumar

Theses and Dissertations

Adaptive Large Neighborhood Search (ALNS) is a fairly recent yet popular single-solution heuristic for solving discrete optimization problems. Even though the heuristic has been a popular choice for researchers in recent times, the parallelization of this algorithm is not widely studied in the literature compared to the other classical metaheuristics. To extend the existing literature, this study proposes several different parallel schemes to parallelize the basic/sequential ALNS algorithm. More specifically, seven different parallel schemes are employed to target different characteristics of the ALNS algorithm and the capability of the local computers. The schemes of this study are implemented in a …