Operations Research, Systems Engineering and Industrial Engineering Commons^™

Developing Leading And Lagging Indicators To Enhance Equipment Reliability In A Lean System, Dhanush Agara Mallesh

Masters Theses

With increasing complexity in equipment, the failure rates are becoming a critical metric due to the unplanned maintenance in a production environment. Unplanned maintenance in manufacturing process is created issues with downtimes and decreasing the reliability of equipment. Failures in equipment have resulted in the loss of revenue to organizations encouraging maintenance practitioners to analyze ways to change unplanned to planned maintenance. Efficient failure prediction models are being developed to learn about the failures in advance. With this information, failures predicted can reduce the downtimes in the system and improve the throughput.

The goal of this thesis is to predict …

Developing A Platform For Integrating Disability Issues Into City Municipality Decisions; Case Study: City Of Knoxville, Sravanthi Pamu

Masters Theses

The People with Disabilities (PWD) & Senior Citizen (SC) are isolated from the mainstream society, and they face several barriers in everyday life. There is no communication platform for them to express their concerns, in turn, participate in the city municipality policy decisions related to PWD- & SC-friendly city development. The purpose of this research is to integrate disability and senior citizen issues in the city of Knoxville to the city council decisions. The comprehensive literature search is done to identify the frequently mentioned disability and age-friendly city factors. An effective survey was designed to identify the issues in collaboration …

Impacts Of The Heterogeneity In Consumer Valuation Of Fuel Economy On Corporate Average Fuel Economy Standards Compliance, Nawei Liu

Masters Theses

This study investigated potential impacts of the heterogeneity in consumer valuation of fuel economy on the compliance with fuel economy standards with two analytical approaches. One approach is to provide theoretical analysis of the heterogeneity impacts on the market acceptance of high-efficiency vehicles. The other approach utilizes a consumer choice based simulation method to analyze the heterogeneity impacts on the compliance with the Corporate Average Fuel Economy (CAFE) Standards for the entire light duty vehicle fleet in the U.S. Our findings suggest two possible conditions which are defined based on relative acceptance of high-efficiency vehicles in the market, and they …

Two Multi-Objective Stochastic Models For Project Team Formation Under Uncertainty In Time Requirements, Fahimeh Rahmanniyay

Masters Theses

Team formation is one of the key stages in project management. The cost associated with the individuals who form a team and the quality of the tasks completed by the team are two of the main concerns in team formation problems. In this study, two mathematical models to optimize simultaneously cost and quality in a team formation problem are developed. Because team formation problem arises in uncertain environment, different scenarios are defined for the time requirement of the project. Two-stage stochastic programming and multi-stage stochastic programming are applied to solve the first and the second model respectively. The presented models …

Reducing Wait Time Prediction In Hospital Emergency Room: Lean Analysis Using A Random Forest Model, Gajanan Arha

Masters Theses

Most of the patients visiting emergency departments face long waiting times due to overcrowding which is a major concern across the hospital in the United States. Emergency Department (ED) overcrowding is a common phenomenon across hospitals, which leads to issues for the hospital management, such as increased patient s dissatisfaction and an increase in the number of patients choosing to terminate their ED visit without being attended to by a medical healthcare professional. Patients who have to Leave Without Being Seen (LWBS) by doctors often leads to loss of revenue to hospitals encouraging healthcare professionals to analyze ways to improve …

Viability Of Additive Manufacturing For Production And Tooling Applications: A Development Of The Business Case, Christopher Charles Griffin

Masters Theses

As marketplace competition drives industrial innovation to increase product value and decrease production costs, emerging technologies foster a new era through Industry 4.0. One aspect of the movement, additive manufacturing, or 3D [three-dimensional] printing, contains potential to revolutionize traditional manufacturing techniques and approach to design. However, uncertainties within the processes and high investment costs deter corporations from implementing and developing the technology. While several industries are benefitting from additive manufacturing’s current state, as the technology continues to progress, more companies will need to evaluate it for industrial viability and adoption. As such, there exists a need for a framework to …

Revisiting The One-Sided Ewma Control Chart Design, Duy Anh Duong-Tran

Masters Theses

Over the past half-century, Exponential Weighted Moving Average (EWMA) control charts have been widely used in Statistical Process Control to detect small and persistent process shifts. In theory, EWMA control limits monotonically increase over time to account for the continual growth of the EWMA statistic’s variance. These control limits are often assumed constant and are set to their respective asymptotic limits. While not theoretically correct, this simplifies the process of applying and analyzing the EWMA control chart while having little effect on the chart’s performance. One-Sided EWMA charts are often implemented when it is only desirable to detect shifts in …

Explorations Into Machine Learning Techniques For Precipitation Nowcasting, Aditya Nagarajan

Masters Theses

Recent advances in cloud-based big-data technologies now makes data driven solutions feasible for increasing numbers of scientific computing applications. One such data driven solution approach is machine learning where patterns in large data sets are brought to the surface by finding complex mathematical relationships within the data. Nowcasting or short-term prediction of rainfall in a given region is an important problem in meteorology. In this thesis we explore the nowcasting problem through a data driven approach by formulating it as a machine learning problem.

State-of-the-art nowcasting systems today are based on numerical models which describe the physical processes leading to …

Data Analysis Of Lane Merge And Lane Shift Sign Configurations In A Freeway Workzone, Satwinder Singh Thind

Masters Theses

"In this study, driver responses to alternative lane shift and lane merge signs are analyzed and compared using a driving simulation system. In particular, driver responses to the lane merge signs proposed by the Missouri Department of Transportation (MoDOT) are compared to the current lane merge signs recommended by the Manual on Uniform Traffic Control Devices (MUTCD) and driver responses to the lane shift signs proposed by MoDOT are compared to current lane shift signs recommended by MUTCD. The driving simulation system is composed of a driving simulator and a PC with data recording program such that the position coordinates, …

A Bounded Actor-Critic Algorithm For Reinforcement Learning, Ryan Jacob Lawhead

Masters Theses

"This thesis presents a new actor-critic algorithm from the domain of reinforcement learning to solve Markov and semi-Markov decision processes (or problems) in the field of airline revenue management (ARM). The ARM problem is one of control optimization in which a decision-maker must accept or reject a customer based on a requested fare. This thesis focuses on the so-called single-leg version of the ARM problem, which can be cast as a semi-Markov decision process (SMDP). Large-scale Markov decision processes (MDPs) and SMDPs suffer from the curses of dimensionality and modeling, making it difficult to create the transition probability matrices (TPMs) …

Shortest-Distance And Minimum-Cost Self-Charging Path Problems: Formulations And Application, Marc Monroe Teeter

Masters Theses

"In this study, self-charging paths for an electric bus are analyzed. Wireless-power-transfer technologies, when integrated on a road network, enable dynamic charging of electric vehicles. Roads implemented with a wireless-power-transfer technology are referred to as electric-roads in this study. Electric vehicles traversing on electric-roads, therefore, can be dynamically charged. This can further eliminate the need for static charging, i.e., the electric vehicle will not need to stop for charging.

This thesis analyzes the design of transit routes for an electric-bus so that the electric-bus is charged by only electric-roads. Specifically, the focus is on designing a path, which passes through …

Micro-Grid Implementation Of A Rooftop Photovoltaic System, Pranav Nitin Godse

Masters Theses

"In recent years, solar power has been a popular form of renewable energy. This research conducts a cost analysis in implementing a rooftop photovoltaic system as part of an energy management schema for a university campus. The proposed system would be installed on the roof of one of the largest buildings on campus at Missouri University of Science and Technology, Toomey Hall; the objective function of the research involves reducing dependence on conventional energy sources on campus. Toomey Hall houses the Department of Mechanical and Aerospace Engineering (MAE) and is the largest academic unit on campus. Considering the vast expanse …

Developing Restoration Schemes For A Road Transportation Network In The Event Of A Disaster, Ebin Antony

Masters Theses

"Transportation systems such as rail, road, and waterways are key component of critical infrastructure systems, providing connectivity between other components to enable the production and distribution of goods and services. During large scale disasters such as earth quakes and floods, this connectivity is disrupted, restricting or completely halting the flow of goods and services. To ensure that the connectivity between the different modes of transportation are restored in an aftermath of these disruptions, the interdependence between them and the importance of individual elements to the overall connectivity have to be studied and formulated to develop a system-level restoration plan. This …

A New Reinforcement Learning Algorithm With Fixed Exploration For Semi-Markov Decision Processes, Angelo Michael Encapera

Masters Theses

"Artificial intelligence or machine learning techniques are currently being widely applied for solving problems within the field of data analytics. This work presents and demonstrates the use of a new machine learning algorithm for solving semi-Markov decision processes (SMDPs). SMDPs are encountered in the domain of Reinforcement Learning to solve control problems in discrete-event systems. The new algorithm developed here is called iSMART, an acronym for imaging Semi-Markov Average Reward Technique. The algorithm uses a constant exploration rate, unlike its precursor R-SMART, which required exploration decay. The major difference between R-SMART and iSMART is that the latter uses, in addition …