Industrial Engineering Commons^™

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 …

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 …

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.

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 …

Exploring Human Responses In Conversations With Ai Entities, Phillip Semenov, Miguel Coronado

College of Engineering Summer Undergraduate Research Program

This study argues that while AI systems have become increasingly advanced, they still evoke distinct emotional responses compared to human interactions, potentially limiting their effectiveness in emotionally-driven environments. We used the Emotiv Insight brain-computer interface to monitor participants' emotional responses during controlled interactions with both AI systems and other humans. Key emotional metrics, such as arousal, focus, and stress, were recorded in real time, providing a detailed picture of the emotional dynamics at play in each type of interaction. Participants exhibited higher levels of excitement, stress, and focus during interactions with humans compared to AI systems, while other emotions like …

An Agent-Based Approach For Designing A Sustainable Supplier Selection In Stochastic Environment: A Simulation Study, Sheida Etemadidavan

Engineering Management & Systems Engineering Theses & Dissertations

In the 21st century, businesses are constantly striving for competitive advancement and increasing their economic performance in the rapidly changing market. Collaboration with other businesses and partnerships with them are becoming more common. As such, businesses are starting to invest in finding the right partners to stay competitive in an ever-changing business landscape. Suppliers play a crucial role in businesses' decision-making as they provide the materials, goods, and services necessary for a company to operate and succeed. Therefore, their selection, management, and relationship must be carefully considered to ensure optimal performance and profitability. A sustainable framework in a business's relationship …

An Interaction Between Mental Integration And Levels Of Automation: An Analytic Approach Applying Systems Factorial Technology, Shelby Kate Scarbrough Long

Psychology Theses & Dissertations

Automation has become nearly ubiquitous in modern society, supporting human performance in personal and professional tasks. Recent works have begun to focus on human-automation performance in speeded perceptual-cognitive tasks using workload capacity analysis, a novel mathematical analysis to measure efficiency of a human-automation team. The present dissertation examined how level of automation and demand for mental integration of information influence human-automation efficiency. Participants performed a multi-element probabilistic decision task with or without the assistance of an automated aid where level of automation and task demand were manipulated. Experiment 1 employed a mixed design with Automation (present vs. absent) and Task …

Fatigue-Resistant Mechanoresponsive Color-Changing Hydrogels For Vision-Based Tactile Robots, Jiabin Liu, Wei Li, Yu She, Sean Blanchard, Shaoting Lin

School of Industrial Engineering Faculty Publications

Mechanoresponsive color-changing materials that can reversibly and resiliently change color in response to mechanical deformation are highly desirable for diverse modern technologies in optics, sensors, and robots; however, such materials are rarely achieved. Here, a fatigue-resistant mechanoresponsive color-changing hydrogel (FMCH) is reported that exhibits reversible, resilient, and predictable color changes under mechanical stress. At its undeformed state, the FMCH remains dark under a circular polariscope; upon uniaxial stretching of up to six times its initial length, it gradually shifts its color from black, to gray, yellow, and purple. Unlike traditional mechanoresponsive color-changing materials, FMCH maintains its performance across various strain …

A Data-Driven Framework For Analyzing And Predicting Social Media Engagement During Rumor Propagation, Joseph E. Faza

Master's Theses

The spread of rumors on social media has become a significant concern, as platforms like X (formerly known as Twitter) enable rapid dissemination of unverified information. These rumors can shape public perception and behavior, making it crucial to understand the dynamics of their spread. The main objective of this study is to explore how users interact with rumor-related tweets and identify key factors that predict tweet engagement. By analyzing tweets from seven different rumor events, this research aims to uncover patterns in user engagement and provide insights into the spread of misinformation. The study utilized a dataset of tweets from …

Order-Picking Strategies And Efficiency Models For The Fulfillment Of Multi-Line E-Commerce Grocery Orders, Zijia Wang

Dissertations

The fulfillment process for Buy Online Pickup from Store grocery orders (BOPS-Grocery) is particularly challenging, given the large item count per order and the low-profit margins. This research investigates the BOPS-Grocery model and pursues the following objectives: (i) Defining and specifying the BOPS-Grocery fulfillment process. Differentiating the process from classical warehouse order picking., identifying performance objectives, and characterizing design options and facility layout. (ii) Modelling and developing order picking algorithms specific to the straight aisle section. Formulated as an order hatching problem with picker movement minimization. No order splitting, and (iii) modeling and developing order picking algorithms specific to the …

Creating A Wholistic Manufacturing Score To Highlight The Effects Of Hidden Inefficiencies In Automated Manufacturing Caused By Soft Dedication And Preventative Maintenance Failures, Oded Tal

LSU Doctoral Dissertations

The semiconductor industry is one of the most advanced manufacturing sectors, operating at an unparalleled scale and complexity. A new manufacturing facility costs between $500 million and $15 billion, and the industry's investment in automation is unmatched. However, the intricate and cyclical nature of semiconductor manufacturing creates very complex manufacturing facilities where the boundaries between planning and real-time operations often blur.

For the industry to keep improving, there is a need to create a new method that allows comparison among different manufacturing environments to uncover hidden losses that may be obscured by automation.

To better understand these hidden losses, the …

Assessment Of The Factors Affecting The National Ict Broadband Backbone (Nictbb) Systems Restoration Time, Victoria Mahabi

Tanzania Journal of Engineering and Technology (TJET)

This study investigates the factors affecting the prolonged system restoration time when national ICT broadband backbone (NICTBB) services are affected by breakdown incidents. NICTBB is the government-owned backbone infrastructure constructed nationally by the Republic of Tanzania to increase the usage of ICT for equitable and sustainable socio-economic development and accelerate poverty reduction. This study utilised a mixture of exploratory and descriptive study approaches. The sample size determination was executed using purposing and simple random sampling, thus involving 289 respondents. The data reliability test was undertaken. It was followed by factor analysis, analysis of variances (ANOVA), linear regression analysis, and confirmed …

Investigation Of Heavy Metal Composition And Associated Health Risks From Selected Groundwater Wells In Temeke, Dar-Es-Salaam, Justin M. Jeremiah

Tanzania Journal of Engineering and Technology (TJET)

Water quality continues to be the challenge to residents in Dar es Salaam due to various anthropogenic activities in the city. This study was conducted to assess groundwater quality by determining concentrations of heavy metals. Both probability and Nonprobability sampling techniques were used to collect samples from 40 groundwater wells in 24 wards of Temeke municipal and analysed using Microwave Plasma Atomic Emission Spectrometer (Agilent 4210 MP-AES) at the Geochemistry Laboratory of the University of Dar es Salaam. Results indicated varying heavy metal concentrations ranging from 0.71 ± 0.08 to 6.64 ± 0.21 mg/l for As, 0.02 ± 0.01 to …

Lean Manufacturing Practices In Tanzania: Exploring Awareness, Training And Capital Investment, Francis D. Sinkamba

Tanzania Journal of Engineering and Technology (TJET)

With the growing competition among industries in the world, manufacturing industries are now forced to adopt the Lean Manufacturing philosophy to improve their competitive abilities. The adoption of the philosophy is very low in developing countries such as Tanzania, as is demonstrated with 1% of publications and the lack of knowledge and capital for Lean Manufacturing implementation causes this. Furthermore, the contribution of the sector to the Gross Domestic Product in Tanzania is low and stands at 8.4%. The study wants to bridge the gap in training, capital and awareness of Lean Manufacturing in Tanzania. Survey and purposive sampling techniques …

Inspection Planning Of Subsea Pipeline Using Risk-Based Inspection, Ni Luh Triska Adelia, Badrul Munir, Johny Wahyuadi Soedarsono

Journal of Materials Exploration and Findings

Pipelines are an important tool in oil and gas exploration. Pipeline is a transmission and liquid collection lines, including their accessories, which transport fluids from one plant to another. In transmission and collection process, there is a possibility of failure which can have minor to major impact on personnel injury, the environment and interrupt the business process. To maintain safety and to prevent accidents, the source and cause of failure needs to be calculated. Risk-based inspection (RBI) is a method that can be used to calculate the risk and determine the inspection planning both schedule and method, by combining the …

Safety And Risk Management Strategies For Achieving Regulatory Compliance In Construction Projects, Danny Rodriguez

Harrisburg University Dissertations and Theses

The architectural and construction business places great importance on safety and regulatory compliance because of its inherent high-risk nature and strict legal obligations. The prevalence of accidents and infractions at construction sites underscores the imperative for enhanced safety management systems and compliance with rules, notwithstanding substantial endeavors. The main objective of this study is to examine the many elements that impact the effectiveness of safety management, adherence to regulations, and the development of a safety culture, with the ultimate purpose of improving safety outcomes on construction sites.

The issue statement pertains to the difficulties associated with safety management and compliance …

Quantifying Lock Criticality For Inland Waterway Navigation Using An Agent-Based Simulation, Ashwin Narayan

Industrial Engineering Undergraduate Honors Theses

Inland waterway travel has tremendous potential to improve multimodal transportation in the United States due to its environment-friendly and safe nature. Waterway travel has proven to be much cheaper per ton-mile and more fuel efficient than trucks. Millions of dollars have recently been invested in inland waterway networks to facilitate travel. The waterway infrastructure must be resilient to enable efficient waterway travel and prevent unnecessary delays. Locks, an important component of waterway infrastructure, enable vessels to travel between waterways of varying depths and must be maintained consistently to avoid unexpected failures. However, with limited resources, it is difficult to preserve …

Application Of Agent-Based Simulation And Game Theory In Evaluating Implementation Of Whole Genome Sequencing In Treating Lung Cancer, Fateme Ghalenoei

Master's Theses

Cancer, particularly lung cancer, presents significant diagnostic and economic challenges globally. Timely diagnosis and cost management play pivotal roles in treatment success. A biomarker is any measurable molecule in blood, bodily fluids, or tissues, indicating the potential presence of an abnormal bodily process, condition, or disease. Biomarker testing is a laboratory test in oncology that is used in the selection of targeted cancer treatments and to help avoid ineffective treatments. Whole Genome Sequencing (WGS), is a biomarker test which while more comprehensive, comes at a higher cost. This study proposes an agent-based simulation model within a game-theoretic framework to examine …