Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Physical Sciences and Mathematics (4)
- Systems Engineering (4)
- Computer Sciences (3)
- Agricultural Economics (1)
- Agriculture (1)
-
- Applied Statistics (1)
- Artificial Intelligence and Robotics (1)
- Bioresource and Agricultural Engineering (1)
- Business (1)
- Business Administration, Management, and Operations (1)
- Categorical Data Analysis (1)
- Civil and Environmental Engineering (1)
- Electrical and Computer Engineering (1)
- Electrical and Electronics (1)
- Energy Systems (1)
- Entrepreneurial and Small Business Operations (1)
- Environmental Engineering (1)
- Ergonomics (1)
- Life Sciences (1)
- Materials Science and Engineering (1)
- Mechanical Engineering (1)
- Operational Research (1)
- Statistics and Probability (1)
- Institution
- Keyword
-
- Engineering education (2)
- Resilience (2)
- Systems engineering (2)
- Systems thinking (2)
- ANN (1)
-
- Absorptive (1)
- Adaptive (1)
- Advanced data analytics (1)
- Agricultural tile drainage (1)
- Anomaly Detection (1)
- Artificial Intelligence (1)
- Auto ML (1)
- Bio-oil (1)
- Choice Modeling (1)
- Complex systems (1)
- Consumption (1)
- Convolutional Neural Network (1)
- Deep learning (1)
- Durable (1)
- Energy (1)
- European Union (1)
- Flow-through model (1)
- Forecast (1)
- Graph theory and matrix approach (1)
- Industrial by-products (1)
- Infrared (1)
- Learning abilities (1)
- Leveraging (1)
- Machine Learning (1)
- Machine learning (1)
Articles 1 - 10 of 10
Full-Text Articles in Industrial Engineering
Energy Planning Model Design For Forecasting The Final Energy Consumption Using Artificial Neural Networks, Haidy Eissa
Energy Planning Model Design For Forecasting The Final Energy Consumption Using Artificial Neural Networks, Haidy Eissa
Theses and Dissertations
“Energy Trilemma” has recently received an increasing concern among policy makers. The trilemma conceptual framework is based on three main dimensions: environmental sustainability, energy equity, and energy security. Energy security reflects a nation’s capability to meet current and future energy demand. Rational energy planning is thus a fundamental aspect to articulate energy policies. The energy system is huge and complex, accordingly in order to guarantee the availability of energy supply, it is necessary to implement strategies on the consumption side. Energy modeling is a tool that helps policy makers and researchers understand the fluctuations in the energy system. Over the …
Leveraging Choice Modeling Technique For Enhancing The Cyber Resilience Of The Smart Grid, Kesava Karishma Devi Dadi
Leveraging Choice Modeling Technique For Enhancing The Cyber Resilience Of The Smart Grid, Kesava Karishma Devi Dadi
Theses and Dissertations
This research focuses on the cyber-attack of the smart grid and its retrieval to a normal state by estimating the smart grid's resilience. This study developed a theoretical model to estimate the resilience of the smart grid using choice modeling. A utility function is formulated based on various factors and sub-factors of resilience to estimate the resilience of the smart grid. Choice modeling is applied to estimate the model parameters in various fields such as marketing, energy, transportation, and health and to predict the outcome.
Deep Multi-Modal U-Net Fusion Methodology Of Infrared And Ultrasonic Images For Porosity Detection In Additive Manufacturing, Christian E. Zamiela
Deep Multi-Modal U-Net Fusion Methodology Of Infrared And Ultrasonic Images For Porosity Detection In Additive Manufacturing, Christian E. Zamiela
Theses and Dissertations
We developed a deep fusion methodology of non-destructive (NDT) in-situ infrared and ex- situ ultrasonic images for localization of porosity detection without compromising the integrity of printed components that aims to improve the Laser-based additive manufacturing (LBAM) process. A core challenge with LBAM is that lack of fusion between successive layers of printed metal can lead to porosity and abnormalities in the printed component. We developed a sensor fusion U-Net methodology that fills the gap in fusing in-situ thermal images with ex-situ ultrasonic images by employing a U-Net Convolutional Neural Network (CNN) for feature extraction and two-dimensional object localization. We …
Effects Of The Inclusion Of Rice Hull Derived Bio-Oil On Wood Pellet Production, Tyler E. Lowe
Effects Of The Inclusion Of Rice Hull Derived Bio-Oil On Wood Pellet Production, Tyler E. Lowe
Theses and Dissertations
Wood pellet production has become an advancing industry for the sake of reducing greenhouse emissions into the atmosphere especially, in European Union countries. Researchers and industry executives seek new methods and materials to improve the pelletization process. Rice hulls or husks has the potential to aid in wood pelletization as they possess high calorific values. This study focuses on using rice hull derived bio-oil from pyrolysis, which will also decrease ash content, as an additive to aid in the wood pelletization process. Using two groups of rice hull derived bio-oil as an additive in wood pelletization: Group 1 uses heavy …
A Dual Perspective Towards Building Resilience In Manufacturing Organizations, Steven A. Fazio
A Dual Perspective Towards Building Resilience In Manufacturing Organizations, Steven A. Fazio
Theses and Dissertations
Modern manufacturing organizations exist in the most complex and competitive environment the world has ever known. This environment consists of demanding customers, enabling, but resource intensive Industry 4.0 technology, dynamic regulations, geopolitical perturbations, and innovative, ever-expanding global competition. Successful manufacturing organizations must excel in this environment while facing emergent disruptions generated as biproducts of complex man-made and natural systems. The research presented in this thesis provides a novel two-sided approach to the creation of resilience in the modern manufacturing organization. First, the systems engineering method is demonstrated as the qualitative framework for building literature-derived organizational resilience factors into organizational structures …
The Development Of Authentic Virtual Reality Scenarios To Measure Individuals’ Level Of Systems Thinking Skills And Learning Abilities, Vidanelage L. Dayarathna
The Development Of Authentic Virtual Reality Scenarios To Measure Individuals’ Level Of Systems Thinking Skills And Learning Abilities, Vidanelage L. Dayarathna
Theses and Dissertations
This dissertation develops virtual reality modules to capture individuals’ learning abilities and systems thinking skills in dynamic environments. In the first chapter, an immersive queuing theory teaching module is developed using virtual reality technology. The objective of the study is to present systems engineering concepts in a more sophisticated environment and measure students learning abilities. Furthermore, the study explores the performance gaps between male and female students in manufacturing systems concepts. To investigate the gender biases toward the performance of developed VR module, three efficacy measures (simulation sickness questionnaire, systems usability scale, and presence questionnaire) and two effectiveness measures (NASA …
Using A Systemic Skills Model To Build An Effective 21st Century Workforce: Factors That Impact The Ability To Navigate Complex Systems, Morteza Nagahi
Using A Systemic Skills Model To Build An Effective 21st Century Workforce: Factors That Impact The Ability To Navigate Complex Systems, Morteza Nagahi
Theses and Dissertations
The growth of technology and the proliferation of information made modern complex systems more fragile and vulnerable. As a result, competitive advantage is no longer achieved exclusively through strategic planning but by developing an influential cadre of technical people who can efficiently manage and navigate modern complex systems. The dissertation aims to provide educators, practitioners, and organizations with a model that helps to measure individuals’ systems thinking skills, complex problem solving, personality traits, and the impacting demographic factors such as managerial and work experience, current occupation type, organizational ownership structure, and education level. The intent is to study how these …
Advanced Analytics In Smart Manufacturing: Anomaly Detection Using Machine Learning Algorithms And Parallel Machine Scheduling Using A Genetic Algorithm, Meiling He
Theses and Dissertations
Industry 4.0 offers great opportunities to utilize advanced data processing tools by generating Big Data from a more connected and efficient data collection system. Making good use of data processing technologies, such as machine learning and optimization algorithms, will significantly contribute to better quality control, automation, and job scheduling in Smart Manufacturing. This research aims to develop a new machine learning algorithm for solving highly imbalanced data processing problems, implement both supervised and unsupervised machine learning auto-selection frameworks for detecting anomalies in smart manufacturing, and develop a genetic algorithm for optimizing job schedules on unrelated parallel machines. This research also …
Applying A Statistical Approach To Develop A Sustainable Technology For Capturing Phosphorous From An Agricultural Tile Drainage System Using By-Product Phosphorous Sorbing Materials (Psm), Amir Kordijazi
Theses and Dissertations
Due to nutrient pollution, agriculture is one of the major sources of pollution in water bodies. Every time it rains, fertilizers, pesticides, and animal waste wash nutrients and pathogens—such as bacteria and viruses—into waterways. As rainfall increases due to climate change, the water problem will worsen. One of the nutrients that extensively contributes to the degradation of water quality is phosphorous (P). In this research, the performance of electric arc furnace (EAF) steel slag was investigated as a P sorbing materials (PSM) according to the conditions present in a P removal structure designed for treating water discharge from an agricultural …
Design Of A Novel Manual And Automated Penetration Testing Framework For Connected Industrial Control Systems (Ics), Rafat Elsharef
Design Of A Novel Manual And Automated Penetration Testing Framework For Connected Industrial Control Systems (Ics), Rafat Elsharef
Theses and Dissertations
This research presents the design of new framework—a manually executed and an automated penetration testing process for Connected Industrial Control Systems (ICS). Both frameworks were built using open-source security software and ICS equipment currently used in critical infrastructure, manufacturing companies, and other institutions in the United States and around the world. Existing penetration testing frameworks have largely been focused on manual testing and are specific to Information Technology (IT). In addition, a new severity scoring system framework, called Common Vulnerability Scoring System for Industrial Control Systems (CVSS-ICS), was recommended for calculating the severity score in Industrial Control Systems (ICS).The broader …