Industrial Engineering Commons^™

The Evolving Use Of Strategic Planning Tools In The Manufacturing Environment: Implications For Quality 4.0 And Beyond, Richard Lee Wilson

Doctoral Dissertations

"Having a strong strategic plan is critical for success for any business no matter the size of the organization, the product or service they provide, or the industry they serve. There are many methods businesses use to develop their strategic plans. One such method is known as Hoshin Kanri, which has been in use for decades. However, recent years have seen an increase in artificial intelligence, big data, data analytics, and other technology tools to create cyber physical systems on the manufacturing floor. The increase in technology in manufacturing to integrate cyber systems with physical systems spawned a new industrial …

Synthetic Data–Driven Early Prediction Framework For Acute Kidney Injury In Patients Receiving Vancomycin And Ceftazidime/Avibactam, Maryam Ramazani

Graduate Theses, Dissertations, and Problem Reports (ETD)

Background: The nephrotoxic risks of combining ceftazidime/avibactam (AVI) with vancomycin (VAN) remain underexplored, despite both agents independently being linked to acute kidney injury (AKI). This study assessed the risk of AKI associated with concurrent VAN and ceftazidime/avibactam (VAN-AVI) therapy and developed synthetic data models to enable early prediction of AKI.

Methods: We conducted a retrospective analysis using electronic health record data from hospitalized adults between 2015 and 2022. The incidence of AKI was compared among patients receiving VAN-AVI or VAN in combination with piperacillin/tazobactam (VAN-TPZ) versus VAN monotherapy. AKI was defined as a composite of de novo and recurrent AKI …

A Strategic Infrastructure Improvement Framework For Intermodal Transportation Networks, Ayoub Abusalih

Graduate Theses, Dissertations, and Problem Reports (ETD)

In this research, we propose a novel approach to design infrastructure networks for intermodal freight transportation systems, which incorporates railways, highways, and inland waterways (IWW). The objective of our study is to identify the optimal set of hubs to be built and operated over an extended time, based on the projected domestic cargo demand. Unlike traditional hub location models, our approach introduces hybrid hubs, where hybrid transportation modes are integrated to facilitate cargo handling. This innovative integration enables more efficient intermodal connections, leading to tangible reductions in operating costs, and carbon emissions. Specifically, we propose a mixed integer programming model …

Framework For Development Environment Selection In Digital Twin Applications, Carlos Dodero Fernandez

Graduate Theses, Dissertations, and Problem Reports (ETD)

Digital Twin (DT) technology, a cornerstone of Industry 4.0, facilitates real-time synchronization between virtual models and physical manufacturing systems, enhancing operational efficiency and decision-making. However, its widespread adoption is hindered by the absence of standardized methods for selecting Development Environments (DEs) for DTs, compounded by challenges in cost, interoperability, and connectivity with Industrial Internet of Things (IIoT) protocols. This thesis proposes a Systematic Selection Framework to address this gap, offering a structured methodology to evaluate DEs based-on visualization quality, scalability, interoperability, and cost-effectiveness for manufacturing applications. The framework categorizes and compares sixteen DEs into Game Engines, Robotics Engines, and Simulation …

Forecasting Air Pollution Driven By Vehicle Growth, Public Transport, Industry, And Household Waste, Chandra Harjono, Ludy Gianto, Rachmattullah Sidik, Dyah Lestari Widaningrum

Journal of Environmental Science and Sustainable Development

Jakarta, Indonesia's bustling capital, is grappling with escalating air pollution levels attributed to a confluence of socio-economic and infrastructural factors. This study employs Vensim modelling to project PM2.5 pollution trends through 2040, analysing the dynamic interplay among major contributors: increased vehicular emissions, industrial activities, public transportation deficiencies, and waste management inefficiencies. Materials and Methods: The method that will be used in this air pollution analysis is to integrate empirical data spanning three years to construct a predictive model underpinned by a robust causal loop diagram that elucidates the relationships between system variables and air quality. The results of this paper …

Digital Twin And Cybersecurity In Additive Manufacturing, Lidong Wang

Journal of Cybersecurity Education, Research and Practice

Additive manufacturing (AM) has been applied to automotive, aerospace, medical sectors, etc., but there are still challenges such as parts’ porosity, cracks, surface roughness, intrinsic anisotropy, and residual stress because of the high level of thermal gradient. It is significant to conduct the modeling and simulation of the AM process and achieve quality products. Digital Twin (DT) can help AM with forecasting defects/errors through simulation and real-time process monitoring. DT is a concept of Industry 4.0, and its digital structure reflects the real-time behaviors of a cyber-physical or physical system. This paper introduces the progress of DT applications in AM, …

Enhanced Intellectual Property Protection Mechanisms Towards Collaborative Data Sharing In Metal-Based Additive Manufacturing, Durant Hayes Fullington

Theses and Dissertations

This dissertation aims to develop effective methodologies towards enhanced intellectual property protections for data sharing frameworks in metal-based additive manufacturing (AM). Currently, many small-to-medium sized manufacturers face data availability challenges due to the prohibitive high cost to collect, process, and analyze large amounts of process-related data for AM. Because these manufactures rely heavily on small-scale data, it can be difficult for them to effectively train complex machine learning (ML) algorithms, which are commonly used for AM process monitoring. One popular solution is to develop collaborative data sharing frameworks, where multiple independent AM users can share their data to increase the …

On Topological Measures And Network Vulnerability Patterns: A Review And Comparative Analysis, Saviz Saei

Theses and Dissertations

Despite much hope for climate change to slow down or even reverse, younger generations face a future overshadowed by extreme events. The indisputable reality is that unless the United Nations establishes comprehensive and sustained climate justice policies, children today will experience five times more extreme events than those that took place a century ago. On Monday, July 3rd of 2023, an unprecedented peak in global temperatures was documented, marking the highest global temperature ever recorded, as the U.S. National Centers for Environmental Prediction reported. These increasing temperatures indicate the ongoing and intensifying phenomenon of climate change, which amplifies the frequency …

Processing Cost Analysis For Great South Metals, Evan Briggs, Madisen Laskos, Jared Perrin

Senior Design Project For Engineers

Great south Metals (GSM), a steel processing company based in Acworth, GA, has partnered with the Kennesaw State University (KSU) Industrial and System Engineering (ISYE) department to optimize its costing model. Currently, GSM uses a flat pricing structure for GSM-owned materials and estimates costs for toll processing. However, this approach has led to inaccuracies in pricing and challenges in tracking profitability. GSM seeks to transition to a more systematic and data-driven costing model that will improve both internal and external quoting while ensuring competitiveness in the market.

To address these challenges, the project focused on developing separate costing matrices for …

A Novel Interpretation Of Average Run Length For Assessing The Performance Of Control Charts, Gonçalo Sousa

Masters Theses

The Average Run Length (ARL) is a performance measure of Control Charts widely used within Statistical Process Control. In this study we propose a new approach for the computation of the ARL that is based on a novel interpretation of out-of-control signals produced by a Control Chart. Specifically, out-of-control signals used to calculate traditional ARLs may correspond to Type I errors and may not reflect a Control Chart’s true performance. To compensate for this issue, for Shewhart and EWMA charts, constraints are applied to the calculation of ARLs so that only out-of-control signals that occur when the corresponding statistic is …

Accessibility And Usability Of Medical Devices For Users With Disabilities: Insights From A Bibliometric And Thematic Analysis, Karen Daniela Gonzalez Silva

Open Access Theses & Dissertations

No abstract provided.

Learning To Accelerate Globally Optimal Solutions: Applications In The Ac Optimal Power Flow Problem, Muhammet Fatih Cengil

Graduate Theses and Dissertations

The Alternating Current Optimal Power Flow (AC-OPF) problem is a fundamental optimization challenge critical to ensuring the economical and reliable operation of power grids. While fast heuristic methods provide upper-bound solutions, assessing their quality requires lower bounds obtained from relaxations of the AC-OPF problem. This dissertation focuses on finding globally optimal solutions to the AC-OPF problem by enhancing the effectiveness and efficiency of Quadratic Convex (QC) relaxations. Leveraging machine learning techniques, we aim to achieve tighter relaxations faster and improve computational performance, enabling practical scalability for real-time applications.

In Chapter 2, we propose a machine learning-based method to accelerate the …

Interaction-Sensitive Tree-Based Statistical Models, Xiaotong Sun

Graduate Theses and Dissertations

This dissertation introduces a tree-based framework to improve the interpretability and modeling of interaction effects among variables, essential in fields like biostatistics, healthcare, science and engineering. Traditional regression methods often fail to clearly capture complex interactions, while tree-based approaches, despite their interpretability, face performance limitations and overfitting concerns. Our proposed interaction-sensitive tree-based method, designed for seamless integration, combines various statistical techniques tailored to different data types, leveraging ensemble learning methods to enhance accuracy and mitigate overfitting. We present methods for regression, survival analysis, and classification, validated with case studies and benchmarked against traditional models using metrics like BIC and R-squared. …

Effect Of Workload And Trust On Automation Levels In Human-Robot Collaboration, Abhiram Maddula

LSU Master's Theses

Automation is becoming increasingly common in manufacturing and assembly plants. The future lies in hybrid workspaces where the strengths of humans and robots complement each other, with robots excelling in precision, speed, and strength, and humans excelling in creativity, emotional intelligence, and complex decision-making. Collaborative robots can foster a more efficient and productive work environment by bridging the gap between human and machine capabilities. This study examines how semi-automated and automated modes impact human-robot collaboration, focusing on mental workload, trust, and task performance.

In this experiment, 58 participants performed a primary task alongside a collaborative robot assembling a miniature lamppost …

Evaluating Laser Tracking For The Improvement Of Quality Control Methods Of Precast Concrete, Blake A. Barbay

LSU Master's Theses

Current quality control (QC) methods of precast concrete are outdated and present challenges of human error and lengthy inspections. Current research into modernizing QC practices revolves around the implementation of laser scanners, with less focus on the possibility of using laser trackers. The aim of this study is to evaluate the implementation of laser trackers into the QC process of precast concrete by comparing time, accuracy, and cost to the traditional method of using a tape measure. The time studies and accuracy tests were performed in the pre- and post-pour of the precast concrete process at a precast concrete plant …

Joining Wood Plastic Composites Using A New Self-Reacting Friction Stir Toolset – A Comparative Study, Mohamed Moustafa Elmeligy Mr, Ahmed Elkassas, Ammar H. Elsheikh

Journal of Engineering Research

Wood-plastic composite (WPC) is an environmentally friendly material that promotes the recycling of wood and plastic waste. However, there is a notable lack of research on methods for joining these materials. This study introduces an innovative approach using a uniquely designed self-reacting friction stir toolset specifically for WPC joining. The performance of this new toolset is evaluated against prior research that employed a hot-shoe friction stir welding toolset on a WPC with a different composition. The study focuses on key parameters such as revolutions per welding line (RPWL), rotational speed, and welding speed, emphasizing their critical impact on the quality …

Gaze Tracking Embedded Collaborative Robots For Automated Metrology And Reverse Engineering, Sachithra H. Karunathilake, Md Shahriar Forhad, Zhaohui Geng

Manufacturing & Industrial Engineering Faculty Publications

Conventional geometric metrology, or three-dimensional (3D) scanning, and reverse engineering heavily rely on the experience of the operators. With an increasing need for automation, robot arms have been adopted for this task. However, due to the large variety of parts and designs, automated path planning could provide a scanning solution that may overlook the critical area, which could potentially deteriorate the scan results. This article explores the integration of collaborative robotics (cobots) with eye-tracking technology to improve the autonomous 3D scanning process. The primary objective of this study is to enhance the accuracy and efficiency of cobots in 3D scanning, …

Data-Driven Roughness Estimation Of Additively Manufactured Samples Using Build Angles, Jose Galarza, Jose Barron Jr., Farid Ahmed, Jianzhi Li

Manufacturing & Industrial Engineering Faculty Publications

Achieving control of Laser Powder Bed Fusion (L-PBF) over the quality of the print is the main motivation for finding an optimum set of parameters in the process. Surface roughness is one of the characteristics of the print that impacts the performance of the desired functionality. This research focus is to relate the build angle with the surface roughness on the L-PBF printed specimens and utilize machine learning methods for roughness estimation of geometric features with varying build angles. The EOS M290 L-PBF printer was used to print Inconel-718 coupons using standard process parameters while varying build angles from 20 …

Enhancing Resilience In Complex Energy Systems Through Real-Time Anomaly Detection: A Systematic Literature Review, Ali Aghazadeh Ardebili, Oussama Hasidi, Ahmed Bendaouia, Adem Khalil, Sabri Khalil, Dalila Luceri, El Hassan Abdelwahed, Sara Qassimi, Antonio Ficarella

Manufacturing & Industrial Engineering Faculty Publications

As real-time data sources expand, the need for detecting anomalies in streaming data becomes increasingly critical for cutting edge data-driven applications. Real-time anomaly detection faces various challenges, requiring automated systems that adapt continuously to evolving data patterns due to the impracticality of human intervention. This study focuses on energy systems (ES), critical infrastructures vulnerable to disruptions from natural disasters, cyber attacks, equipment failures, or human errors, leading to power outages, financial losses, and risks to other sectors. Early anomaly detection ensures energy supply continuity, minimizing disruption impacts, an enhancing system resilience against cyber threats. A systematic literature review (SLR) is …

Prediction Of Tool Wear And Surface Finish Using Anfis Modelling During Turning Of Carbon Fiber Reinforced Plastic (Cfrp) Composites, Anil K. Srivastava, Md. Mofakkirul Islam

Manufacturing & Industrial Engineering Faculty Publications

Carbon fiber-reinforced plastics (CFRP) are widely used in various industries due to their high strength to weight ratio, corrosion resistance, durability, and excellent thermo-mechanical properties. The machining of CFRP composites has always been a challenge for the manufacturers. In this study, CNC turning operation with coated carbide tool is used to machine a specific CFRP and the relationship between the cutting parameters (Speed, Feed, Depth of Cut) and response parameters (Vibration, Surface Finish, Cutting Force and Tool Wear) are investigated. An adaptive-network-based fuzzy inference system (ANFIS) model with two multi-input–single-output (MISO) system has been developed to predict the tool wear …