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Full-Text Articles in Industrial Engineering
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 …