Operations Research, Systems Engineering and Industrial Engineering Commons^™

Drivers’ Hazard Avoidance During Vehicle Automation: Impact Of Mental Models And Implications For Training, Ganesh Pai Mangalore

Doctoral Dissertations

Advanced Driver Assistance Systems (ADAS) are vehicle automation systems that have become more accessible and prevalent in vehicles in recent years. But the introduction of such technologies introduces new human factors challenges. Past literature suggests that users of vehicle automation lack the necessary and appropriate knowledge about their automation system. This may play a negative role in their hazard avoidance abilities when driving with automation features. Improving mental models and knowledge could generally lead to safer interactions with vehicle automation systems, but any effort to develop hazard avoidance skills when driving with vehicle automation is impeded by the lack of …

Smart Warehousing Implementaion And Education Of Supply Chain Management Leaders, David Quintanilla

Doctoral Dissertations

Paper #1 Overview

Businesses have to adapt to new challenges and technologies in the marketplace which influence warehousing. In order to support this growth, Industry 4.0 technologies have been implemented along the value chain to optimize their organizations and production processes; however, there are still gaps for warehousing research for Industry 4.0. We present four pillars¾location strategy, infrastructure/design, data management, and advanced planning and control¾ as a framework for businesses to use for their adaptation into smart warehousing. In particular, this framework will guide companies in their logistics journey into Industry 4.0. Industry experts and senior logistics professionals were interviewed …

Understanding And Simulating Wildfire Changes Using Advanced Statical And Process-Oriented Models, Rongyun Tang

Doctoral Dissertations

This study aims to investigate the spatiotemporal dynamic of global wildfires, their underlying climate-driving mechanisms, and their predictability by utilizing multiple data sources (both process-based model simulations and satellite-based observations) and multiple analytical methods including machine learning techniques (MLTs).

We first explored the global wildfire interannual variability (IAV) and its climate sensitivity across nine biomes from 1997 to 2018, leveraging the state-of-art U.S. Department of Energy’s Energy Exascale Earth System Model (E3SM) land component (ELM-v1) simulations with six sets of climate forcings. Results indicate that 1) ELM simulations could reproduce the IAV of wildfire in terms of magnitudes, distribution, bio-regional …

A Novel Approach To Orbital Debris Mitigation, Timothy S. Turk

Doctoral Dissertations

Since mankind launched the first satellite into orbit in 1957, we have been inadvertently, yet deliberately, creating an environment in space that may ultimately lead to the end of our space exploration. Space debris, more specifically, orbital debris is a growing problem that must be dealt with sooner, rather than later. Several ideas have been developed to address the complex problem of orbital debris mitigation.

This research will investigate the possibility of removing orbital debris from the Low Earth Orbit (LEO) regime by using a metaheuristic algorithm to maximize collection of debris resulting from the February 2009 on-orbit collision of …

Novel Mixed Integer Programming Approaches To Unit Commitment And Tool Switching Problems, Najmaddin Akhundov

Doctoral Dissertations

In the first two chapters, we discuss mixed integer programming formulations in Unit Commitment Problem. First, we present a new reformulation to capture the uncertainty associated with renewable energy. Then, the symmetrical property of UC is exploited to develop new methods to improve the computational time by reducing redundancy in the search space. In the third chapter, we focus on the Tool Switching and Sequencing Problem. Similar to UC, we analyze its symmetrical nature and present a new reformulation and symmetry-breaking cuts which lead to a significant improvement in the solution time. In chapter one, we use convex hull pricing …

Quality And Productivity Improvements In Additive Manufacturing, Huseyin Kose

Doctoral Dissertations

Additive manufacturing (AM) is a relatively new manufacturing technology compared to the traditional manufacturing methods. Even though AM processes have many advantages, they also have a series of challenges that need to be addressed to adapt this technology for a wide range of applications and mass production.

AM faces a number of challenges, including the absence of methods/models for determining whether AM is the best manufacturing process for a given part. The first study of this thesis proposes a framework for choosing specific AM processes by considering the complexity level of a part. It has been proven that the method …

Three Essays On Data-Driven Optimization For Scheduling In Manufacturing And Healthcare, Ekin Koker

Doctoral Dissertations

This dissertation consists of three essays on data-driven optimization for scheduling in manufacturing and healthcare. In Chapter 1, we briefly introduce the optimization problems tackled in these essays. The first of these essays deals with machine scheduling problems. In Chapter 2, we compare the effectiveness of direct positional variables against relative positional variables computationally in a variety of machine scheduling problems and we present our results. The second essay deals with a scheduling problem in healthcare: the team primary care practice. In Chapter 3, we build upon the two-stage stochastic integer programming model introduced by Alvarez Oh (2015) to solve …

Modeling Performance, Cost, Delivery, And Trip Distribution Of Demand Responsive Transit Systems With Zoning, Mahour Rahimi

Doctoral Dissertations

Demand responsive transit (DRT) services are expensive to operate, so it is crucial to understand the factors that drive the agency costs and be able to investigate and predict the effect of possible changes in specific operating parameters as well as demand and service coverage areas on total costs. In this research, we adopt the concept of the analytical model proposed by Daganzo (1978) to present continuum approximation (CA) models that can estimate important service related factors. As the first step, we propose three analytical models to approximate the operation related variables of DRT services; Fleet Size, Vehicle Hours Traveled …

Theory And Practice Of Supply Chain Synchronization, Michael Prokle

Doctoral Dissertations

In this dissertation, we develop strategies to synchronize component procurement in assemble-to-order (ATO) production and overhaul operations. We focus on the high-tech and mass customization industries which are not only considered to be very important to create or keep U.S. manufacturing jobs, but also suffer most from component inventory burden. In the second chapter, we address the deterministic joint replenishment inventory problem with batch size constraints (JRPB). We characterize system regeneration points, derive a closed-form expression of the average product inventory, and formulate the problem of finding the optimal joint reorder interval to minimize inventory and ordering costs per unit …

Flight Risk Management And Crew Reserve Optimization, Ying Zhang

Doctoral Dissertations

There are two key concerns in the development process of aviation. One is safety, and the other is cost. An airline running with high safety and low cost must be the most competitive one in the market. This work investigates two research efforts respectively relevant to these two concerns.

When building support of a real time Flight Risk Assessment and Mitigation System (FRAMS), a sequential multi-stage approach is developed. The whole risk management process is considered in order to improve the safety of each flight by integrating AHP and FTA technique to describe the framework of all levels of risks …

Exploring A Semi-Virtual Reality System Impacting Learning Curves Of College Students, Hongbiao Yang

Doctoral Dissertations

Virtual reality (VR) is a trending technology used in a broad range of fields including education and has become one of the most promising directions for educators. In this research, the investigation focuses on how the semi-immersive VR application can be used for educational purposes by exploring the VR factors and the interactions between these factors. A theoretical learning framework is also proposed to offer an explanation for the beneficial effects of education brought by VR at a high level.

This research consists of three parts. First, this research will introduce the development of Walk-in-Place Learning System (WIPLS), a semi-immersive …

Transition To Electric Vehicles In The California Automobile Industry, Jinglu Song

Doctoral Dissertations

This dissertation presents a comprehensive study on the market adoption of electric vehicle and policy impact of the Zero Emission Vehicle (ZEV) mandate in the California automotive market. This research is primarily consisting of three parts. The author first built a technology innovation pricing model based on multi-nomial logit modelling method. This studies the dynamics among customer preferences, market acceptance and policy impact on vehicle pricing in the California automotive market. Results show that the ZEV mandate could profoundly enhance the market adoption of electric vehicles. There is a threshold on the magnitude of policy intervention. If the number of …

Retail Analytics And Optimization For Store-Wide Shelf-Space Management, Tulay Flamand

Doctoral Dissertations

A major constituent of modern-time economies, retailing is a vibrant business sector that is marked by high competition, tight profit margins, novel business strategies in online and in-store environments, and demanding consumers. Driven by massive volumes of point-of-sale data, retail analytics has become instrumental for unveiling better managerial practices. Our research falls under the umbrella of retail shelf space management. In self-service outlets, shelf space constitutes a scarce resource and its management is central to ensuring an attractive shopping experience and a profitable business. We investigate how, under a given store layout, the allocation of product categories can be optimized …

A Tool Kit For Building Hbcu Technology Transfer Supply Chain Networks Using An Advanced Planning System, Clovia Hamilton

Doctoral Dissertations

This mixed methods study describes the development of a university technology transfer that Historically Black Colleges and Universities (HBCUs) can use to become more self-reliant financially. HBCUs lag behind their peer non-HBCUs because historically they have been under-served and were originally established largely as teaching and blue collar trade schools. Increased involvement in research oriented activities such as technology transfer will likely enable HBCUs to grow into new or stronger research institutions. The literature review revealed several problem areas with non-HBCUs university technology transfer include: (1) lack of quality standard benchmarks; (2) resource planning issues; (3) processing delays; and (4) …

Fault Diagnosis And Failure Prognostics Of Lithium-Ion Battery Based On Least Squares Support Vector Machine And Memory Particle Filter Framework, Mohammed Ali Lskaafi

Doctoral Dissertations

123456A novel data driven approach is developed for fault diagnosis and remaining useful life (RUL) prognostics for lithium-ion batteries using Least Square Support Vector Machine (LS-SVM) and Memory-Particle Filter (M-PF). Unlike traditional data-driven models for capacity fault diagnosis and failure prognosis, which require multidimensional physical characteristics, the proposed algorithm uses only two variables: Energy Efficiency (EE), and Work Temperature. The aim of this novel framework is to improve the accuracy of incipient and abrupt faults diagnosis and failure prognosis. First, the LSSVM is used to generate residual signal based on capacity fade trends of the Li-ion batteries. Second, adaptive threshold …

Guidelines For Scheduling In Primary Care: An Empirically Driven Mathematical Programming Approach, Hyun Jung Alvarez Oh

Doctoral Dissertations

Primary care practices play a vital role in healthcare delivery since they are the first point of contact for most patients, and provide health prevention, counseling, education, diagnosis and treatment. Practices, however, face a complex appointment scheduling problem because of the variety of patient conditions, the mix of appointment types, the uncertain service times with providers and non-provider staff (nurses/medical assistants), and no-show rates which all compound into a highly variable and unpredictable flow of patients. The end result is an imbalance between provider idle time and patient waiting time. To understand the realities of the scheduling problem we analyze …

How Much Do In-Vehicle Tasks With Swapping, Switching And Spillover Effects Interfere With Drivers’ Ability To Detect And Respond To Threats On The Forward Roadway?, Siby Samuel

Doctoral Dissertations

Distractions have long been associated with crashes. A review of the literature shows drivers engaging in secondary tasks to be three times as likely to crash as compared to attentive drivers. Although several studies report that excessively long glances away from the forward roadway elevate the risk of crashes, little research has been conducted to determine how long a driver needs to glance towards the forward roadway in between glances inside the vehicle to perform a secondary task in order to detect threats present in or emerging from the forward roadway. To determine this, drivers were asked to perform simulated …

Prognostic-Based Life Extension Methodology With Application To Power Generation Systems, Seyed Ahmad Niknam

Doctoral Dissertations

Practicable life extension of engineering systems would be a remarkable application of prognostics. This research proposes a framework for prognostic-base life extension. This research investigates the use of prognostic data to mobilize the potential residual life. The obstacles in performing life extension include: lack of knowledge, lack of tools, lack of data, and lack of time.

This research primarily considers using the acoustic emission (AE) technology for quick-response diagnostic. To be specific, an important feature of AE data was statistically modeled to provide quick, robust and intuitive diagnostic capability. The proposed model was successful to detect the out of control …

Proactive Model To Determine Information Technologies Supporting Expansion Of Air Cargo Network, Grayson C. Mcclain

Doctoral Dissertations

Shippers and recipients expect transportation companies to provide more than just the movement of a package between points; certain information must be available to them as well, to enable forecasts and plans within the supply chain.

The transportation companies also need the information flow that undergirds a transportation grid, to support ad-hoc routing and strategic structural re-alignment of business processes.

This research delineates the information needs for an expanding air cargo network, then develops a new model of the information technologies needed to support expansion into a new country. The captured information will be used by shippers, recipients, and the …

A Dea Model To Optimize Insurance Payment Plans Based On Pacs, Gagan Rajpal

Doctoral Dissertations

Healthcare industry has evolved dramatically over the time. From being a “cottage industry” to an “organized industry” has brought lot of changes. The changes have been both good and bad. Among the problems that have surfaced in past couple of decades, rising healthcare cost has been one of the most significant. The rising healthcare cost has been documented to be a symptom of several factors. Since the inception of healthcare as an organized industry several payment models for providers and hospitals have been adopted. Current healthcare reforms have proposed new payments models to curb the rising cost and provide consumer …

Moldable Items Packing Optimization, Sima Maleki

Doctoral Dissertations

This research has led to the development of two mathematical models to optimize the problem of packing a hybrid mix of rigid and moldable items within a three-dimensional volume. These two developed packing models characterize moldable items from two perspectives: (1) when limited discrete configurations represent the moldable items and (2) when all continuous configurations are available to the model. This optimization scheme is a component of a lean effort that attempts to reduce the lead-time associated with the implementation of dynamic product modifications that imply packing changes.

To test the developed models, they are applied to the dynamic packing …

Solving Combinatorial Optimization Problems Using Genetic Algorithms And Ant Colony Optimization, Gautham Puttur Rajappa

Doctoral Dissertations

This dissertation presents metaheuristic approaches in the areas of genetic algorithms and ant colony optimization to combinatorial optimization problems.

Ant colony optimization for the split delivery vehicle routing problem

An Ant Colony Optimization (ACO) based approach is presented to solve the Split Delivery Vehicle Routing Problem (SDVRP). SDVRP is a relaxation of the Capacitated Vehicle Routing Problem (CVRP) wherein a customer can be visited by more than one vehicle. The proposed ACO based algorithm is tested on benchmark problems previously published in the literature. The results indicate that the ACO based approach is competitive in both solution quality and solution …