Operations Research, Systems Engineering and Industrial Engineering Commons^™

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 …

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 …

Reevaluating Order Fulfillment Decisions For E-Tailers Under True Simulated Operating Conditions, Amir H. Kalantari

Theses and Dissertations

This dissertation makes both a methodological and an applied contribution. From a methodological standpoint, this is among the very first works in the literature to explore the concepts of true simulated operating conditions and fully embedded decision-making algorithms. We illustrate the effectiveness of these concepts by applying them to an online retailer (i.e. e-tailer) order fulfillment decision making process.

Online shopping has completely transformed retail markets in recent years. For customers, it provides convenience, visibility and choice, and for retailers it provides market expansion opportunities, operational cost reduction, and many other advantages. There are fundamental differences between the supply chain …

A Microscopic Simulation Laboratory For Evaluation Of Off-Street Parking Systems, Yun Yuan

Theses and Dissertations

The parking industry produces an enormous amount of data every day that, properly analyzed, will change the way the industry operates. The collected data form patterns that, in most cases, would allow parking operators and property owners to better understand how to maximize revenue and decrease operating expenses and support the decisions such as how to set specific parking policies (e.g. electrical charging only parking space) to achieve the sustainable and eco-friendly parking.

However, there lacks an intelligent tool to assess the layout design and operational performance of parking lots to reduce the externalities and increase the revenue. To address …