Industrial Engineering Commons^™

Evaluation Of Patient Experience Using Natural Language Processing Algorithms, Sofia Veronica Ortega

Open Access Theses & Dissertations

INTRODUCTION: Healthcare organizations are making extensive efforts to improve the patient experience. Enhancing patient/client experience and outcomes is crucial for patient-centered care and can reveal improvement opportunities. Healthcare settings currently rely on surveys (e.g., HCAHPS) and patient feedback to measure patient experience. Studies have identified that utilizing patient journey mapping can better capture patient experience throughout all stages of the patient's journey and provide quality and process improvement recommendations at specific hotspots. However, these measurement techniques are time-consuming and resource intensive. AIM: This research aims to measure patient experience of breast cancer patients from social media data using natural language …

Multistage Stochastic Programming: Algorithms, Modelling And Applications, Murwan Siddig

All Dissertations

This dissertation comprises four di˙erent topics related to multistage stochastic program-ming (MSP) algorithms, modeling, and applications.

First, we extend the adaptive partition-based approach for solving two-stage stochastic programs with a fixed recourse matrix and a fixed cost vector to the MSP setting, where the stochastic process is assumed to be stage-wise independent. The proposed algorithms integrate the adaptive partition-based strategy with a popular approach for solving multistage stochastic programs, the stochastic dual dynamic programming (SDDP) algorithm, according to two main strategies. These two strategies are distinct from each other in the manner by which they refine the partitions during the …

Machine Learning Models For Lodi Indices., Lucas A. Bruns

Electronic Theses and Dissertations

Two indices published monthly by the Logistics and Distribution Institute (LoDI) predict changes in logistics and distribution activity levels nationally and regionally and are useful for organizations when planning projects and expenses. This research validates the current linear regression model, updates the index conversion method, and introduces machine learning models.

New source data are introduced to the models to validate the current linear regression model and a comparative analysis verifies that the current source data are robust. A rolling average is used for index conversion in place of a fixed reference month to reflect recent changes in employment levels.

Three …

Assessment Of The Impacts Of Climate Variability On Hydropower Generation: A Case Study Of The New Pangani Falls, Tanzania, Dativa Byarufu

Tanzania Journal of Engineering and Technology (TJET)

Climate change poses potential impacts on hydropower generation either positively by increasing or negatively by decreasing river flow. This study assessed the impacts of climate variability on hydropower with a focus on the New Pangani Falls in Tanzania. Rainfall and temperature time series data from 1980-2014 were analyzed in relation to river discharge and associated impacts to hydropower generation. The Man-Kendall test was used to detect trend in both annual and seasonal time series. The results showed a negative trend in annual rainfall with Z= -2.41 at α = 0.05 and the slope Q = -0.964. Seasonal trend analysis showed …

Rheological Properties Of Aged Crude Hard Wood Pyrolysis Oil, Divina D. Kaombe

Tanzania Journal of Engineering and Technology (TJET)

Upon storage of the pyrolysis oil, aging reactions may initiate phase separation and change of the rheological properties. These changes lead to unfavourable fuel characteristics in handling, transportation and applications. Efforts have been made for alleviation including methods on how to avoid these aging effects and development of equipment capable of handling aged pyrolysis liquids with unfavourable fuel characteristics. Therefore, the aim of this study was to explore the rheological properties of phase separated pyrolysis liquid fuel. Two batches of a well – stored poplar wood pyrolysis oils were used for the investigation; one batch was diluted with water to …

Prediction Of Uniaxial Compressive Strength Of Granite Rock Samples Of Lugoba Quarry Using Rebound Hammer Test, Moses Kongola, Karim Baruti

Tanzania Journal of Engineering and Technology (TJET)

Rebound hammer test is widely used as an indirect measure of uniaxial compressive strength for engineering materials such as concrete, soil, and rock in both civil and mining engineering works. In quarries, uniaxial compressive strength is a crucial parameter in the analysis of geotechnical problems involving rock stability and rock blasting design. This study aims at establishing the empirical models of uniaxial compressive strength fits on rebound hammer number that can be used to predict uniaxial compressive strength of granitic rock at Lugoba Quarry. Data for direct uniaxial compressive strength were obtained from uniaxial compressive strength test carried out on …

Prediction Of Four-Days Soaked California Bearing Ratio (Cbr) Values From Soil Index Properties, Pascal Ambrose, Siya P. Rimoy Dr

Tanzania Journal of Engineering and Technology (TJET)

California Bearing Ratio (CBR) laboratory testing is the conventional method for determining soaked strengths of pavement subgrades. The test requires careful preparation of soil samples followed by four days of water soaking before penetrating the samples using a standard plunger at prescribed rates to set depths. When the number of samples becomes large the determination of soaked CBR values becomes cumbersome as the test is laborious and time consuming. This study aimed at establishing an alternative way of determining soaked CBR by developing a model that would be used for estimating soaked CBR of fine- and coarse- grained soils without …

Embedded Curriculum With Industry-Recognized Certifications To Improve The Marketability Of Engineering Technology Graduates, Immanuel Edinbarough, Jesus A. Gonzalez-Rodriguez

Manufacturing & Industrial Engineering Faculty Publications

Embedded Curriculum with Industry Recognized Certifications to Improve the Marketability of Engineering Technology Graduates

The Fourth Industrial Revolution is challenging the industries to change the way they manage and operate the manufacturing environment. This leads to the transformation of the world through artificial intelligence, next-generation robotics, automation, big data analytics, 5G technology and Internet of Things. This idea of Industry 4.0 forces the change in the industries of today and tomorrow. In this, cyber physical systems communicate with one another using the Internet of Things. The manufacturing sector takes full advantage of these technologies to produce innovative products to enhance …

An Improved Earned Value Management Method Integrating Quality And Safety, Brian Briggs

LSU Doctoral Dissertations

The construction industry invests significant time and money to improve quality and safety while reducing cost and schedule impacts. The industry has a sincere desire to improve construction project management methods to improve efficiency. Historically, quality and safety underperformances result from undermanaged quality control and safety activities. The cost and schedule impacts associated with poor quality work have always had an impact on construction operations. The unprecedented challenges and uncertainties of COVID-19 highlighted the need to improve the Earned Value Management (EVM) method within construction to reflect these quality and safety activities. The central goal of this dissertation is to …

Study Of Friction And Wear Effects In Aluminum Parts Manufactured Via Single Point Incremental Forming Process Using Petroleum And Vegetable Oil-Based Lubricants, Jose M. Diabb Zavala, Oscar Martinez-Romero, Alex Elias-Zuniga, Hector Manuel Leija Gutierrez, Alejandro Estrada-De La Vega, Jaime Taha-Tijerina

Manufacturing & Industrial Engineering Faculty Publications

This paper focuses on studying how mineral oil, sunflower, soybean, and corn lubricants influence friction and wear effects during the manufacturing of aluminum parts via the single point incremental forming (SPIF) process. To identify how friction, surface roughness, and wear change during the SPIF of aluminum parts, Stribeck curves were plotted as a function of the SPIF process parameters such as vertical step size, wall angle, and tool tip semi-spherical diameter. Furthermore, lubricant effects on the surface of the formed parts are examined by energy dispersive spectroscopy (EDS) and scanning electron microscope (SEM) images, the Alicona optical 3D measurement system, …

Healthcare Data Analytics For Predicting Health Outcomes Of Older Adults And Emergency Responses Of Aged Care Facilities, Nazmus Sakib

USF Tampa Graduate Theses and Dissertations

The United States (US) is experiencing rapid growth in its older adult population, who may suffer from multiple chronic diseases, injuries, and impairments. To meet with the excess demand without compromising the quality of care for older adults, the current aged care systems, such as nursing home systems, will face unprecedented challenges of healthcare resource shortage with rising costs. Accurate prediction of health outcomes of individual older adults will facilitate the aged care professionals to better prioritize healthcare resources for the most at-risk individuals with more focused care and provide more proactive and individualized treatment and care delivery. In addition, …

A Machine Learning Approach To Understanding Emerging Markets, Namita Balani

Graduate Theses and Dissertations

Logistic providers have learned to efficiently serve their existing customer bases with optimized routes and transportation resource allocation. The problem arises when there is potential for logistics growth in an emerging market with no previous data. The purpose of this work is to use industry data for previously known and well-documented markets to apply data analytic techniques such as machine learning to investigate the uncertainty in a new market. The thesis looks into machine learning techniques to predict miles per stop given historical data. It mainly focuses on Random Forest Regression Analysis, but concludes that additional techniques, such as Polynomial …

Knowledge Discovery From Complex Event Time Data With Covariates, Samira Karimi

Graduate Theses and Dissertations

In particular engineering applications, such as reliability engineering, complex types of data are encountered which require novel methods of statistical analysis. Handling covariates properly while managing the missing values is a challenging task. These type of issues happen frequently in reliability data analysis. Specifically, accelerated life testing (ALT) data are usually conducted by exposing test units of a product to severer-than-normal conditions to expedite the failure process. The resulting lifetime and/or censoring data are often modeled by a probability distribution along with a life-stress relationship. However, if the probability distribution and life-stress relationship selected cannot adequately describe the underlying failure …

Enabling The “Easy Button” For Broad, Parallel Optimization Of Functions Evaluated By Simulation, Andrew Gibson

Graduate Theses and Dissertations

Java Optimization by Simulation (JOBS) is presented: an open-source, object-oriented Java library designed to enable the study, research, and use of optimization for models evaluated by simulation. JOBS includes several novel design features that make it easy for a simulation modeler, without extensive expertise in optimization or parallel computation, to define an optimization model with deterministic and/or stochastic constraints, choose one or more metaheuristics to solve it and run, using massively parallel function evaluation to reduce wall-clock times.

JOBS is supported by a new language independent, application programming interface (API) for remote simulation model evaluation and a serverless computing environment …

Printing Quality Improvement For Laser-Induced Forward Transfer Bioprinting: Numerical Modeling And Experimental Validation, Jie Qu, Chaoran Dou, Ben Xu, Jianzhi Li, Zhonghao Rao, Andrew Tsin

Manufacturing & Industrial Engineering Faculty Publications

Laser-induced-forward-transfer (LIFT)-based laser assisted bioprinting (LAB) has great advantages over other three-dimensional (3D) bioprinting techniques, such as none-contact, free of clogging, high precision, and good compatibility. In a typical LIFT based LAB process, a jet flow transfers the bioink from the ribbon to the substrate due to bioink bubble generation and collapse, and the printing quality is highly dependent on the jet flow regime (stable or unstable), so it is a great challenge to understand the connection between the jet flow and the printing outcomes. To tackle this challenge, a novel computational-fluid-dynamics (CFD)-based model was developed in this study to …

Scheduling Allocation And Inventory Replenishment Problems Under Uncertainty: Applications In Managing Electric Vehicle And Drone Battery Swap Stations, Amin Asadi

Graduate Theses and Dissertations

In this dissertation, motivated by electric vehicle (EV) and drone application growth, we propose novel optimization problems and solution techniques for managing the operations at EV and drone battery swap stations. In Chapter 2, we introduce a novel class of stochastic scheduling allocation and inventory replenishment problems (SAIRP), which determines the recharging, discharging, and replacement decisions at a swap station over time to maximize the expected total profit. We use Markov Decision Process (MDP) to model SAIRPs facing uncertain demands, varying costs, and battery degradation. Considering battery degradation is crucial as it relaxes the assumption that charging/discharging batteries do not …

Quantitative Set-Based Design For Complex System Development, Nicholas J. Shallcross

Graduate Theses and Dissertations

This dissertation comprises a body of research facilitating decision-making and complex system development with quantitative set-based design (SBD). SBD is concurrent product development methodology, which develops and analyzes many design alternatives for longer time periods enabling design maturation and uncertainty reduction. SBD improves design space exploration, facilitating the identification of resilient and affordable systems. The literature contains numerous qualitative descriptions and quantitative methodologies describing limited aspects of the SBD process. However, there exist no methodologies enabling the quantitative management of SBD programs throughout the entire product development cycle. This research addresses this knowledge gap by developing the process framework and …

Optimization Of Vaccine Supply Chains In Low- And Middle-Income Countries Utilizing Drones, Maximilian Kolter

Graduate Theses and Dissertations

Despite tremendous efforts from governments and humanitarian organizations, millions of children in low- and low-middle-income countries (LICs and LMICs) are still excluded from the benefits of immunization. The vaccine distribution in LICs and LMICs is challenging for several reasons, such as limited cold chain capacities, vaccine wastage, uncertain demand, and lack of access to immunization services. A promising avenue to address these issues is the utilization of drones for vaccine delivery. Drones can fly at high speed on direct paths and could enable on-demand deliveries to mitigate limited storage capacities. Further, their independence of road networks could allow them reaching …

Resilience-Driven Post-Disruption Restoration Of Interdependent Critical Infrastructure Systems Under Uncertainty: Modeling, Risk-Averse Optimization, And Solution Approaches, Basem A. Alkhaleel

Graduate Theses and Dissertations

Critical infrastructure networks (CINs) are the backbone of modern societies, which depend on their continuous and proper functioning. Such infrastructure networks are subjected to different types of inevitable disruptive events which could affect their performance unpredictably and have direct socioeconomic consequences. Therefore, planning for disruptions to CINs has recently shifted from emphasizing pre-disruption phases of prevention and protection to post-disruption studies investigating the ability of critical infrastructures (CIs) to withstand disruptions and recover timely from them. However, post-disruption restoration planning often faces uncertainties associated with the required repair tasks and the accessibility of the underlying transportation network. Such challenges are …

Using Advanced Driving Simulation And Vibrotactile Cues To Train Drivers To Interact With Next-Generation Autonomous Vehicles, Gaojian Huang

Link Foundation Modeling, Simulation and Training Fellowship Reports

There are six levels of vehicle automation, from Level 0 – no automation to Level 5, fully autonomous [1]. According to several projections, the majority of vehicles on the road will be at intermediate levels for the next several years, meaning that vehicle-to-human takeover will be required in cases where the systems can no longer function due to design limitations, such as under poor weather conditions or in a construction zone [2], [3]. As shown in Fig. 1, the takeover process consists of signal response and post-takeover phases, which involves multiple steps, including perceiving the takeover requests (TOR), moving hands …