Engineering Commons^™

Cluster-Based Chained Transfer Learning For Energy Forecasting With Big Data, Yifang Tian

Electronic Thesis and Dissertation Repository

Smart meter popularity has resulted in the ability to collect big energy data and has created opportunities for large-scale energy forecasting. Machine Learning (ML) techniques commonly used for forecasting, such as neural networks, involve computationally intensive training typically with data from a single building/group to predict future consumption for that same building/group. With hundreds of thousands of smart meters, it becomes impractical or even infeasible to individually train a model for each meter. Consequently, this paper proposes Cluster-Based Chained Transfer Learning (CBCTL), an approach for building neural network-based models for many meters by taking advantage of already trained models through …

Space Optimization And Process Improvement, Harith Alshareef

Senior Design Project For Engineers

Siemens Energy warehouse located in Suwanee, GA runs out of space in the Precision Lab due to rapid growth, seasonal peaks, and poor space utilization. The objective of the project is to redesign the Precision Lab layout and improve the tool assessment process to increase efficiency, productivity, and profitability.

The first solution is to add shelves in the Precision lab as well as the Torque lab and reduce the honeycombing effect on the shelves, which results in a 120%-150% increase in the storage space. We propose adding Tablets that include barcode scanner features to reduce the time spent on the …

Mazak Laser Optimization, Maylon Ellington, Terrilian E. Agbor Oji, William N. Palm

Senior Design Project For Engineers

Starflex Fabrication is a manufacturing company that thrives to provide custom, precision fabricated parts, and assemblies to their customers.The Mazak laser is Starflex Fabrication’s primary cutting machine and is critical to the overall process for each order. Team Flex will look to optimize the laser’s process and improve overall shop throughput.

Process Improvement And Lift Design For The Installation Of A Metrology Machine Assembly, Dalt J. Lasell, James Mitchell O'Meara, Matthew Steensma

Industrial and Manufacturing Engineering

The objective is to work with Onto Innovations, a leading provider of semiconductor metrology and manufacturing solutions, to develop a system that safely installs a 250lb optics plate into the Atlas III: one of their metrology machines. Based in Milpitas, CA, Onto Innovations utilizes a variety of operations to create different products and assembles each product on site. The 250lb optics plates are WIP that are transferred between fixtures and the Atlas III using a combination of lifts and human workers. The WIP have long lead times, high tolerances, and large costs associated with their manufacturing process.

Onto Innovations identified …

Automation Of Data Analysis In Formula 1, Adam Joseph Mourad, Prescott Jeanne Delzell, Patrick Conner Mccabe

Industrial and Manufacturing Engineering

This paper explores economic solutions for Formula 1 racing companies who are interested in data visualization tools. The research was conducted on the current development of data gathering, data visualization, and data interpretation in Formula 1 racing. It was found that a large chunk of racing companies within the league needs an affordable, effective, and automated visualization tool for data interpretation. As data collection in Formula 1 arises, the need for faster and more powerful software increases. Racing companies profit off-brand exposure and the more a racing team wins, the more exposure they receive. The goal of the paper focuses …

A Game Modeling Of A Closed-Loop Supply Chain In A Water-Energy Nexus: Technology Advancement, Market Competition And Capacity Limit, Nabeel Hamoud

Theses and Dissertations

Water and energy are two scarce and concerning resources interconnected in the water-energy nexus. In the nexus, production of energy needs water, and production of water needs energy. For better management of these resources in the nexus, this research considers a supply chain that consists of water suppliers, power suppliers, and consumers of these commodities. In the chain, water suppliers purchase power from power suppliers, and power suppliers purchase water from water suppliers. Other consumers can also buy these resources at the water and power markets. Each firm tries to maximize its own profit. The suppliers of water and power …

Extracting Patterns In Medical Claims Data For Predicting Opioid Overdose, Ryan Sanders

Graduate Theses and Dissertations

The goal of this project is to develop an efficient methodology for extracting features from time-dependent variables in transaction data. Transaction data is collected at varying time intervals making feature extraction more difficult. Unsupervised representational learning techniques are investigated, and the results compared with those from other feature engineering techniques. A successful methodology provides features that improve the accuracy of any machine learning technique. This methodology is then applied to insurance claims data in order to find features to predict whether a patient is at risk of overdosing on opioids. This data covers prescription, inpatient, and outpatient transactions. Features created …

Optimizing Block-Stacking Operations With Relocation, Hueon Lee

Graduate Theses and Dissertations

The focus of the dissertation is developing the optimization problem of finding the minimum-cost operational plan of block stacking with relocation as well as devising a solution procedure to solve practical-sized instances of the problem. Assuming changeable row depth instead of permanent row depth, this research is distinguished from conventional block stacking studies.

The first contribution of the dissertation is the development of the optimization problem under the assumption of deterministic demand. The problem is modeled using integer programming as a variation of the unsplittable multi-commodity flow problem. To find a good feasible solution of practical-sized instances in reasonable time, …

Dynamic Vehicular Trajectory Optimization For Bottleneck Mitigation And Safety Improvement, Wenqing Chen

Theses and Dissertations

Traffic bottleneck is defined as a disruption of traffic flow through a freeway or an arterial, which can be divided as two categories: stationary bottleneck and moving bottleneck. The stationary bottleneck is mainly formed by the lane drops in the multi-lane roadways, while the moving bottleneck are due to the very slowing moving vehicles which disrupt the traffic flow. Traffic bottlenecks not only impact the mobility, but also potentially cause safety issues.

Traditional strategies for eliminating bottlenecks mainly focus on expanding supply including road widening, green interval lengthening and optimization of intersection channelization. In addition, a few macroscopic methods are …

Contributions Of Role-Playing Games: Advantages Of Incorporating Social Media In Disaster Response, Erin Mullin

Graduate Theses and Dissertations

After a disaster, emergency managers need to know who needs help, what type of help they need, and how soon they need it. Traditionally, they have relied on 911 calls and ground assessments to collect this information. Because the needs of a population are not able to be identified in a timely manner by ground assessments and because individuals are often unable to get through to 911, many civilians in distress turn to social media outlets as a last-ditch effort to obtain the services they need. Due to the uncertainty concerning the accuracy of social media posts, responding to disaster …

Machine Learning Applications To Predict Road Crash And Soccer Game Outcomes, Lu Bai

Master's Theses

Machine learning has become a cutting-edge and widely studied data science field of study in recent years across many industries and disciplines. In this thesis, two problems (1- crash severity prediction, 2- soccer game outcome prediction.) were investigated by using a set of machine learning approaches, namely: Ridge regression, Lasso Regression, Support Vector Machine (SVM), Neural Network (NN), Random Forest (RF).

The first study is focused on investigating the critical factors affecting crash severity on a comprehensive time-series state-wide traffic crash data. The dataset covers crashes occurred in the state of Connecticut between 1995 and 2014. Traffic crashes are an …

A Data-Driven Predictive Model Of Reliability Estimation Using State-Space Stochastic Degradation Model, Farhad Balali

Theses and Dissertations

The concept of the Industrial Internet of Things (IIoT) provides the foundation to apply data-driven methodologies. The data-driven predictive models of reliability estimation can become a major tool in increasing the life of assets, lowering capital cost, and reducing operating and maintenance costs. Classical models of reliability assessment mainly rely on lifetime data. Failure data may not be easily obtainable for highly reliable assets. Furthermore, the collected historical lifetime data may not be able to accurately describe the behavior of the asset in a unique application or environment. Therefore, it is not an optimal approach anymore to conduct a reliability …

A Case Study: The First Coastal Nuclear Decommissioning Project In California, Willie Aaron Quiros

Construction Management

San Onofre Nuclear Generating System (SONGS) is one of two nuclear power plants in California. Since the shut down in 2012, there is only one actively remaining, Diablo Canyon Nuclear Power Plant, which is set to shut down in 2024. This paper will examine the decommissioning of SONGS thus far; the first coastal nuclear decommissioning project in California’s stringent permitting process. This project was awarded as a joint venture to AECOM and Energy Solutions, both having experiencing in the field of nuclear decommissioning. This paper will outline what nuclear decommissioning challenges have been in the past; general steps of decommissioning …

Aisle Design For Order Picking Operations With Unit-Load Replenishment., Dominic Ian Sleigh

Electronic Theses and Dissertations

The warehouse design problem has been addressed in the last decade with fewer constraints than ever before. Between optimization for unit load and order picking warehouses, the former has had extensively more research performed. Unit load optimization efforts have promised labor savings of 20-22%. Of the existing research for order-picking warehouses, only small improvements of less than 4% have been claimed. We propose the design optimization for order-picking warehouses requires consideration for inherently incurred unit load operations from pallet inbound activities, as well as forward-pick area replenishment. We perform experiments comparing optimization of aisle design using order picking data with …

Rfid Item-Level Tagging In A Grocery Store Environment, Brian Truman

LSU Master's Theses

The purpose of this research was to investigate how effective item-level Radio Frequency Identification (RFID) tagging would be using current RFID technology as a replacement for barcodes in a supermarket/grocery store environment.

To accomplish this, an experiment was be performed that utilized commercially available RFID technology. Passive Ultra High Frequency (UHF) RFID Tags were affixed to various grocery store items of different material categories (Food, Metal, Plastic, Liquid, and Glass), and placed in a metal shopping cart. Eight (8) antenna arrangements were created, comprised of different combinations of four (4) antennas in different locations around the cart.

The experiment was …

Energy Supply Chain Of Co-Firing System To Generate Electricity, Abinash Panda

Major Papers

The problem of air pollution on the streets of the national capital of India, New Delhi is a major concern. Majority of the pollutants are generally originated from either the vehicles on the roads or the burning of crops from the neighbouring states of the National Capital Region (NCR). To improve the condition of the air quality by the vehicles, implementation of the Electric Vehicles (EVs) in an energy supply chain is a suitable plan. The objective of this paper is to plan a supply chain of generation of electricity by the process of co-firing that prompts benefits both in …

Algorithms For Multi-Objective Mixed Integer Programming Problems, Alvaro Miguel Sierra Altamiranda

USF Tampa Graduate Theses and Dissertations

This thesis presents a total of 3 groups of contributions related to multi-objective optimization. The first group includes the development of a new algorithm and an open-source user-friendly package for optimization over the efficient set for bi-objective mixed integer linear programs. The second group includes an application of a special case of optimization over the efficient on conservation planning problems modeled with modern portfolio theory. Finally, the third group presents a machine learning framework to enhance criterion space search algorithms for multi-objective binary linear programming.

In the first group of contributions, this thesis presents the first (criterion space search) algorithm …

Stakeholder Engagement In Marine Spatial Planning Of Bangladesh, Mohammad Samsul Mannan

World Maritime University Dissertations

No abstract provided.

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 …

Combining Human Factors And Data Science Methods To Evaluate The Use Of Free Text Communication Orders In Electronic Health Records, Swaminathan Kandaswamy

Doctoral Dissertations

Medication errors are a leading cause of death in the United States. Electronic Health Records (EHR) along with Computerized Provider Order Entry (CPOE) are considered promising ways to reduce these errors. However, EHR systems have not eliminated medication errors. Moreover, in some cases they have facilitated errors due to issues such as poor usability and negative effects on clinical workflows. The use of unexpected free text within a CPOE system can serve as a marker that the system does not adequately support clinical workflow. Prior studies have looked at the use of free text within medication orders, but the inclusion …

Topology Network Optimization Of Facility Planning And Design Problems, Ravi Ratan Raj Monga

Masters Theses

The research attempts to provide a graphical theory-based approach to solve the facility layout problem. Which has generally been approached using Quadratic Assignment Problem (QAP) in the past, an algebraic method. It is a very complex problem and is part of the NP-Hard optimization class, because of the nonlinear quadratic objective function and (0,1) binary variables. The research is divided into three phases which together provide an optimal facility layout, block plan solution consisting of MHS (material handling solution) projected onto the block plan. In phase one, we solve for the position of departments in a facility based on flow …

Generalized Relay Network Design And Collaborative Dispatching In Truckload Transportation, Amin Ziaeifar

Operations Research and Engineering Management Theses and Dissertations

The truckload industry faces a serious problem of high driver shortage and turnover rate which is typically around 100\%. Among the major causes of this problem are extended on-the-road times where drivers handle several truckload pickup and deliveries successively; non-regular schedules and get-home rates; and low utilization of drivers dedicated time. These are by-and-large consequences of the driver-to-load dispatching method, which is based on point-to-point dispatching or direct shipment from origin-to-destination, commonly employed in the industry. In this dissertation, we consider an alternative dispatching method that necessitates careful design of an underlying network. In this scheme, a truckload on its …

Systems Approach To Evaluating Mih-Cp (Mobile Integrated Healthcare – Community Paramedicine): A Case Study Of East Baton Rouge Parish (Ebrp) Emergency Medical Services (Ems) Community Paramedicine Program Initiative, Oluwakemi Aiyedun

LSU Doctoral Dissertations

This study applied a holistic method of healthcare program assessment, known as systems approach, to evaluate the efficacy of the East Baton Rouge Parish (EBRP) EMS Community-integrated Health Program (CIHP). The author developed assessment metrics following the Quadruple Aim Framework: IHI (Institute for Healthcare Improvement) Triple Aim + Provider Experience.

Results showed that the CP program in this study delivers high ratings on patient experience and provided a 51% return on investment (ROI) through reduced emergency service utilization, ED visits and inpatient hospital admissions. However, findings did not demonstrate meaningful improvement in patients’ health-related quality of life (HRQoL) and self-efficacy …

Equilibrium Modeling And Policy Analysis Of A Biofuel Supply Chain With A Hydroelectric Reservoir, Jinwoo Bae

Theses and Dissertations

This research proposesd a game theoretic model of a biofuel supply chain (BSC) where a utility company supplies reservoir water to two farmers, located in downstream and upstream of a hydropower dam. The decision-making process of the model is formulated as a three-stage Stackelberg game. We analyze the equilibrium of the decentralized systems and the effect of the government subsidy on energy crop (switchgrass) production for cellulosic biofuel industries, with two forms of subsidy: (1) discriminated subsidies and (2) equalized subsidies.

The results show that both forms of subsidy improve social welfare in the BSC unless the amount of subsidy …

Direct Assessment Of Entrepreneurial Minded Learning Through Integrated E-Learning Modules, Aadtiyasinh Rana

Master's Theses

Entrepreneurial Minded Learning (EML) has a significant emphasis in engineering education

today. Several approaches have been used to assess the impact of various EML approaches. Many indirect assessment techniques have been used and a few direct assessment techniques have been developed. The work presented in this thesis investigates the effectiveness of two specific measurement methods to quantify entrepreneurial minded learning in students.

The University of New Haven has adopted the approach of integrating e-learning modules on entrepreneurial topics and related contextual activities into courses as the primary approach of developing an entrepreneurial mindset (EM) in students. This study focuses on …

Evaluation Of Data Collection Operations For Real-Time Influenza Surveillance During An Emergency, Yuwen Gu

Dissertations

It is unclear how data collection operations for surveillance alter the disease portrayal that influenza reported trends attempt to provide during an emergency. This study developed a model that simulates the collection and testing of influenza specimens after an outbreak is declared in Michigan. It performed simulation based optimization to understand which operational factors affect the biases between the growth rates of original and observed influenza incidence trends, and to quantify the predictive power of the influenza incidence trends at different points of data collection. The results show that emergency driven high risk perception increases the reporting, which leads to …

Dynamic Prediction Of Treatment Outcomes For Recurrent Tuberculosis Patients, Nicole Hayes

Industrial Engineering Undergraduate Honors Theses

Tuberculosis (TB) is a disease that affects people around the world, especially people in underdeveloped countries. TB is one of the top ten causes of death globally so improvement in understanding diagnosis and treatment of TB affected patients could lead to major improvements in world health. This thesis research evaluated relapse patients specifically, deeming a relapse patient as one who has either been cured or completed their last treatment and then is diagnosed with TB again.

This research uses dynamic predictive modeling, based upon the random forest algorithm, to predict treatment outcomes for recurrent TB patients using demographic and follow-up …

Probabilistic Models For Order-Picking Operations With Multiple In-The-Aisle Pick Positions, Jingming Liu

Graduate Theses and Dissertations

The development of probability density functions (pdfs) for travel time of a narrow aisle lift truck (NALT) and an automated storage and retrieval (AS/R) machine is the focus of the dissertation. The multiple in-the-aisle pick positions (MIAPP) order picking system can be modeled as an M/G/1 queueing problem in which storage and retrieval requests are the customers and the vehicle (NALT or AS/R machine) is the server. Service time is the sum of travel time and the deterministic time to pick up and deposit a pallet (TPD).

Our first contribution is the development of travel time pdfs for retrieval operations …

Power System Planning In Disparate Systems: Modeling Sustainability And Electricity Access, Destenie Nock

Doctoral Dissertations

Electricity goals around the world tend to focus on increasing social benefit through one of two avenues: (1) increasing overall system sustainability or (2) increasing access to electricity. These goals guide the transition of the power system. In pursuit of these goals decision makers will need modeling tools that can inform decisions, in a way that is flexible enough to include a wide range of preferences and goals. It is clear that the future generation mix of the power system will change, but the most sustainable solution, will change based on a country's goals. This dissertation will explore the various …

A Computational Simulation Model For Predicting Infectious Disease Spread Using The Evolving Contact Network Algorithm, Buyannemekh Munkhbat

Masters Theses

Commonly used simulation models for predicting outbreaks of re-emerging infectious diseases (EIDs) take an individual-level or a population-level approach to modeling contact dynamics. These approaches are a trade-off between the ability to incorporate individual-level dynamics and computational efficiency. Agent-based network models (ABNM) use an individual-level approach by simulating the entire population and its contact structure, which increases the ability of adding detailed individual-level characteristics. However, as this method is computationally expensive, ABNMs use scaled-down versions of the full population, which are unsuitable for low prevalence diseases as the number of infected cases would become negligible during scaling-down. Compartmental models use …