Industrial Engineering Commons^™

How Individuals’ Opinions Influence Society’S Resistance To Epidemics: An Agent-Based Model Approach, Geonsik Yu, Michael Garee, Mario Ventresca, Yuehwern Yih

Purdue University Libraries Open Access Publishing Fund

Background

Protecting public health from infectious diseases often relies on the cooperation of citizens, especially when self-care interventions are the only viable tools for disease mitigation. Accordingly, social aspects related to public opinion have been studied in the context of the recent COVID-19 pandemic. However, a comprehensive understanding of the effects of opinion-related factors on disease spread still requires further exploration.

Methods

We propose an agent-based simulation framework incorporating opinion dynamics within an epidemic model based on the assumption that mass media channels play a leading role in opinion dynamics. The model simulates how opinions about preventive interventions change over …

Automated Image Registration For Titanium Aircraft Components Via Resolution-Robust Parallel Neural Networks, Paige T. Luebbering

Theses and Dissertations

Titanium alloys are vital to the structural integrity of military and commercial aircraft, comprising numerous critical components. These components are composed of microtexture regions (MTRs) that, at a specific size and orientation, can lead to aircraft failure. Existing MTR testing methods, such as Electron Backscatter Diffraction, often fall short in effectively detecting these MTRs without causing damage to the component. Addressing this gap, this thesis develops a Parallel Convolutional Neural Network (CNN) model tailored for multi-resolution image registration of Polarized Light Microscopy (PLM) images to enhance MTR identification in a non-invasive manner. The findings reveal a significant enhancement in the …

Hybrid Features Extraction For The Online Mineral Grades Determination In The Flotation Froth Using Deep Learning, Ahmed Bendaouia, El Hassan Abdelwahed, Sara Qassimi, Abdelmalek Boussetta, Intissar Benzakour, Abderrahmane Benhayoun, Oumkeltoum Amar, François Bourzeix, Karim Baïna, Mouhamed Cherkaoui, Oussama Hasidi

Manufacturing & Industrial Engineering Faculty Publications

The control of the froth flotation process in the mineral industry is a challenging task due to its multiple impacting parameters. Accurate and convenient examination of the concentrate grade is a crucial step in realizing effective and real-time control of the flotation process. The goal of this study is to employ image processing techniques and CNN-based features extraction combined with machine learning and deep learning to predict the elemental composition of minerals in the flotation froth. A real world dataset has been collected and preprocessed from a differential flotation circuit at the industrial flotation site based in Guemassa, Morocco. …

Assessing Adoption Barriers Of Sustainable Packaging In Egypt, Carol Ramses Morgan

Theses and Dissertations

Sustainable packaging has become an essential part of business decisions and corporate directions. With the rise of environmental damages due to improper waste management and unsustainable practices, businesses have a major responsibility to analyze their products’ life cycles and redesign them with sustainability in mind. Applying sustainable packaging could save companies large amounts of resources, therefore cutting costs, while also achieving the legal and social duty as a corporation towards society and the environment. Many developing countries, with specific focus on Egypt, have recently focused on legislative and corporate decisions in order to encourage more sustainable practices. Egypt’s new Waste …

Evaluation Of Environmental Management System For Small And Medium Enterprises In Dar Es Salaam, Tanzania, Juma M. Matindana

Tanzania Journal of Engineering and Technology (TJET)

A system that manages environmental issues of Small and Medium Enterprises (SMEs) from the time of acquisition of raw materials up to disposal of the product is not well clear, especially in Tanzania. Most of the studies have been conducted in the field of environment management but few of them address the evaluation of the management of SMEs activities with respect to the environment. Although the nature of activities of SMEs has little noticeable environmental implications at the individual level but the impact is large due to diversification and labour intensity of these SMEs. SMEs employ about 20% of the …

A Two-Stage Based Life Cycle And Principal Component Analysis For Decision Support Of Potential Municipal Solid Wastes Management Scenarios, Case Study Dar Es Salaam, Tanzania, Edwin Richard Ndibalema Dr

Tanzania Journal of Engineering and Technology (TJET)

In most of the urban areas of Tanzania, poor and inadequate solid waste management is a growing environmental and public health concern. Despite an array of solid waste management options, choosing an appropriate one remains a challenge. This study applied a novel two-stage-based approach to assess the environmental impacts and sustainability performance of the 27 scenarios for municipal solid wastes (MSW) management of Dar es Salaam City, Tanzania. In the first stage, the study utilized a life cycle analysis (LCA) to quantify the environmental impacts of MSW scenarios. In the second stage, the study used the principal component analysis (PCA) …

Augmented Finite Control Set Mpc Design Technique For Wide Speed Range Control Of Permanent Magnet Synchronous Motor Drives, Francis Mwasilu

Tanzania Journal of Engineering and Technology (TJET)

The effective motion control task is highly influencing the final drive performance in wide-range motor drives applications such as electric vehicles (EVs), washing machines, compressors, elevators and lathe machines. Recently, permanent magnet synchronous motor (PMSM) drive has been widely employed in these applications to achieve desired performances such as high efficiency, high torque requirements with minimum size “occupancy”. The PMSM drive features combining with these modern drive applications are highly nonlinear and the desired operation requirements demand high-performance control schemes with fast system response and robustness features. Linear control schemes are usually implemented to drive the PMSM that entail trade …

Nature Of Occupational Incidents Among Roofing Contractors: A Data Mining Approach, Ikechukwu Sylvester Onuchukwu, Pouya Gholizadeh, Genian Liko, Behzad Esmaeili

Purdue University Libraries Open Access Publishing Fund

Given that roofing contractors in the construction industry have the highest fatality rate among specialty contractors, understanding the root cause of incidents among roofers is critical for improving safety outcomes. This study applied frequency analysis and decision tree data-mining techniques to analyze roofers’ fatal and non-fatal accident reports. The frequency analysis yielded insights into the leading cause of accidents, with fall to a lower level (83%) being the highest, followed by incidence sources relating to structures and surfaces (56%). The most common injuries experienced by roofing contractors were fractures (49%) and concussions (15%), especially for events occurring in residential buildings, …

Cost Estimation Proxy Models For Economic Evaluations In Petroleum Projects: A Case Study From The Onshore Gas Field In The Southern Coastal Tanzania Basin, Fulmence Kaborogo

Tanzania Journal of Engineering and Technology (TJET)

Petroleum economic evaluation involves estimating revenues from forecasted production profiles and field costs including capital expenditures (CAPEX), drilling expenses (DRILLEX), and operating expenses (OPEX). The existing cost-estimating tool requires several inputs making it time-intensive and difficult to use with few data during the early stages of projects. Majority of the previously developed time saving cost estimations proxy models rely on unrealistic assumptions that include uniform operational costs for different fields with a different number of wells, casings, and drilled depths. This work focused at developing proxy models that consider the variability of the development costs with different parameters. The developed …

A Review On Additive Manufacturing For Aerospace Application, Radhika C, Ragavanantham Shanmugam, Monsuru Ramoni, Gnanavel Bk

Manufacturing & Industrial Engineering Faculty Publications

Additive manufacturing, a cutting-edge technology often colloquially known as 3D printing, is a transformative process used to meticulously fabricate complex components by adding material layer upon layer. This revolutionary manufacturing method allows for precise control and customization, making it a go-to choice in various industries, from aerospace to healthcare. The adroitness of additive manufacturing in creating a complex geometry as a whole is very much harnessed by the aerospace Industry. Generating a component using additive manufacturing involves optimal design, methods, and processes. This review gives a broad knowledge in developing a part or product by choosing the appropriate design, method, …

Containerization Of Seafarers In The International Shipping Industry: Contemporary Seamanship, Maritime Social Infrastructures, And Mobility Politics Of Global Logistics, Liang Wu

Dissertations, Theses, and Capstone Projects

This dissertation discusses the mobility politics of container shipping and argues that technological development, political-economic order, and social infrastructure co-produce one another. Containerization, the use of standardized containers to carry cargo across modes of transportation that is said to have revolutionized and globalized international trade since the late 1950s, has served to expand and extend the power of international coalitions of states and corporations to control the movements of commodities (shipments) and labor (seafarers). The advent and development of containerization was driven by a sociotechnical imaginary and international social contract of seamless shipping and cargo flows. In practice, this liberal, …

Application Of Learning Processes For Improving Last-Mile Logistics Optimization At Scale, Seyedeh Shaghayegh Rabbanian

LSU Doctoral Dissertations

The escalating demands of omnichannel retailing, rapid urbanization and shifting customer behaviors have propelled last-mile vehicle routing logistics to the forefront of research. This last-mile phase, recognized as a significant contributor to costs and pollution in the supply chain, necessitates efficient route optimization to minimize expenses and environmental impact. This research delves into machine learning based techniques for solving large-scale Vehicle Routing Problem (VRP), a fundamental concern in last-mile logistics, aiming to optimize delivery vehicle routing amidst diverse customer nodes and operational constraints. Three primary research subproblems are analyzed: utilizing machine learning for constructive solutions, Variable Neighborhood Search (VNS) metaheuristic, …

Exploring Clustering Patterns In Msmes And Large Enterprises In Maharashtra: Analyzing Industrial Dynamics Using Cluster Coefficient And Other Economic Indicators, Priyanshu Bist

2024 REYES Proceedings

The paper discusses an attempt to explore and assess the economic clustering in Maharashtra by focusing on the MSMEs (Micro, Small and Medium Enterprises) and large enterprises in six major districts, namely Konkan, Nashik, Pune, Aurangabad, Amravati, and Nagpur. Cluster coefficients, total number of workers, and other economic indicators of units were considered to understand how industries are spread and perform regionally. Our research was a combination of exploratory and descriptive research, ensuring the data to be garnered had already been collected from the reports and records of the governments concerned and of industries. This entails that we have a …

Exploring Service Quality Among Us Hajj Pilgrims In Compliance With Vision 2030 Objectives, Majid Abdulmalik Alshaibi

Graduate Thesis and Dissertation 2023-2024

Saudi Arabia is progressing with Vision 2030, an ambitious blueprint for economic variation, global connection, and improved quality of life. The Hajj pilgrimage is addressed by the Doyof Al Rahman Program (DARP), one of the vision's programs aiming to enhance the Hajj experience. The Hajj pilgrimage is one of the world's largest annual massive gatherings and it has already received increased attention from researchers combining elements of pilgrimage and tourism. This dissertation aims to explore Hajj service quality and pilgrims' satisfaction. To attain this objective, a narrative and systematic literature review was conducted to develop a framework with standardized …

A Simulation Model Analysis In The Us-Mexico Border, Carlo A. Zorola, Hiram Moya, Aditya Akundi

Manufacturing & Industrial Engineering Faculty Publications

Supply Chain (SC) is the flow of goods or services between supply and demand points. New or innovative strategies in SC have been researched and developed to deal with disruptive events, such as COVID-19, hurricanes, geopolitical, and even climate change. These challenges create supply imbalances, logistical challenges, and policy restrictions for transborder commerce. The DHS has implemented the Free and Secure Trade (FAST) program in both the US-Mexico and US-Canada border. These lanes are dedicated queues for commercial vehicles. In 2022, the government of Nuevo León, México, opened a dedicated lane just for Tesla´s northbound commercial traffic. There has been …

Artificial Intelligence For Enhanced Flotation Monitoring In The Mining Industry: A Convlstm-Based Approach, Ahmed Bendaouia, El Hassan Abdelwahed, Sara Qassimi, Abdelmalek Boussetta, Intissar Benzakour, Oumkeltoum Amar, Oussama Hasidi

Manufacturing & Industrial Engineering Faculty Publications

In the mining industry, accurate monitoring of the elemental composition in the flotation froth is crucial for efficient minerals separation. The hybrid deep learning algorithms offer powerful computational intelligence for real-time monitoring of froth quality in flotation processes. This soft sensor tool can provide valuable information for process control, including predictions of the elemental chemical composition. In this study, we propose a novel approach based on a Convolutional Long Short-Term Memory (ConvLSTM) neural network for real-time monitoring of chemical composition grades in flotation froth. The proposed model effectively extracts spatial and temporal patterns from video data, providing a better …

Models Of Information Diffusion And The Role Of Influence, Chathura Jj Don Dimungu Arachchige

Graduate Thesis and Dissertation 2023-2024

Information diffusion is significant in fields such as propagation prediction and influence maximization, with applications in viral marketing and rumor control. Despite conceptual differences, existing diffusion models may not represent identical underlying generative structures. A classification of diffusion of information models is developed based on infection requirements and stochasticity. The study involves analyzing seven existing DOI models on directed scale-free networks. The distinctive properties of each model are identified through simulations and analysis of experimental results. Our analysis reveals that similarity in conceptual design does not imply similarity in behavior concerning speed, the final state of nodes and edges, and …

Large Retail Logistics Warehouse Execution System, Michael Broughton

Graduate Research Theses & Dissertations

In this study, integrated technical solutions designed for large retail logistics (LRL) material handling equipment (MHE) were integrated with advanced technical industry trends to create a warehouse execution/warehouse control system (WES/WCS) distribution center (DC) model. This model was executed using a distributor profitability framework. The resulting process metrics, financial elements, and forecasted financial drivers within the new model were tested against a standard warehouse management system (WMS) DC model without WES or integrated WCS technical solutions. The hypothesis was that using the WES/WCS DC model in automating store functionality would result in superior cost-effective solutions for the P&L/EBITDA lines of …

การพัฒนาระบบสารสนเทศของกระบวนการปล่อยผลิตภัณฑ์ยางรถยนต์, นัยรัตน์ เดชเสงี่ยมศักดิ์

Chulalongkorn University Theses and Dissertations (Chula ETD)

งานวิจัยนี้มีวัตถุประสงค์เพื่อพัฒนาระบบสารสนเทศสำหรับการปล่อยผลิตภัณฑ์ยางรถยนต์ โดยเปลี่ยนจากการใช้ระบบตรวจสอบในรูปแบบเอกสารกระดาษไปสู่กระบวนการประมวลผลข้อมูลผ่านเทคโนโลยีคอมพิวเตอร์ เพื่อแก้ไขปัญหาความล่าช้า ความไม่ถูกต้อง และความซ้ำซ้อนในกระบวนการปัจจุบัน การดำเนินงานประกอบด้วยการใช้เครื่องมือวิเคราะห์ เช่น ผังงาน แผนภูมิกระบวนการไหล และแผนภาพการไหลของกระบวนการ เพื่อจำลองและวิเคราะห์ขั้นตอนต่าง ๆ ที่ก่อให้เกิดความสูญเปล่า รวมถึงการประยุกต์ใช้เครื่องมือวิเคราะห์คุณภาพ ได้แก่ แผนผังก้างปลา การวิเคราะห์โหมดความล้มเหลวและผลกระทบ (FMEA: Failure Mode and Effects Analysis) และการวิเคราะห์แบบ Why-Why Analysis เพื่อค้นหาสาเหตุที่แท้จริงของปัญหา และกำหนดแนวทางแก้ไขอย่างเป็นระบบ ผลลัพธ์ของการวิจัยคือการออกแบบและพัฒนาแอปพลิเคชันออนไลน์ที่รองรับการทำงานแบบอัตโนมัติ และสามารถเชื่อมต่อกับระบบตรวจสอบระยะไกลแบบเรียลไทม์ โดยใช้วงจรชีวิตการพัฒนาซอฟต์แวร์ (Software Development Life Cycle: SDLC) ภายใต้ Waterfall Model เป็นกรอบการดำเนินงานหลัก มีการวิเคราะห์และสร้างแบบจำลองข้อมูลผ่าน Data Flow Diagram (DFD) และ Entity-Relationship Diagram (ERD) รวมถึงการออกแบบฐานข้อมูลโดยใช้กระบวนการ Normalization เพื่อลดความซ้ำซ้อนของข้อมูล แอปพลิเคชันได้รับการออกแบบตามหลักการของ UX/UI และผ่านการทดสอบการใช้งานด้วยวิธี Usability Testing โดยมีผู้ใช้งานจำนวน 10 คนเข้าร่วมการทดสอบ ผลการทดสอบพบว่าระบบมีความเป็นมิตรต่อผู้ใช้งาน โดยมีอัตราความสำเร็จในการใช้งาน 100% และได้รับคะแนนความพึงพอใจเฉลี่ย 86.23 จาก 100 คะแนน นอกจากนี้ ระบบใหม่ยังสามารถลดระยะเวลารวมของกระบวนการปล่อยผลิตภัณฑ์ยางรถยนต์ได้ถึง 24.62% และช่วยลดต้นทุนแรงงาน รวมถึงค่าใช้จ่ายด้านกระดาษและการจัดการเอกสารได้มากถึง 75,567 บาทต่อปี

การประยุกต์ใช้ปัญญาประดิษฐ์เพื่อวิเคราะห์การสั่นสะเทือนของเครื่องจักร ผ่านระบบอินเทอร์เน็ตของสรรพสิ่ง, ทศพล ลัทธปรีชา

Chulalongkorn University Theses and Dissertations (Chula ETD)

ในยุคอุตสาหกรรมสมัยใหม่การนำปัญญาประดิษฐ์ (AI) ร่วมกับอินเทอร์เน็ตของสรรพสิ่ง (IoT) มาประยุกต์ใช้ในระบบการผลิตและบำรุงรักษาเครื่องจักรนั้นเป็นสิ่งสำคัญที่ช่วยเพิ่มประสิทธิภาพและลดต้นทุนการดำเนินงาน โดยระบบ IoT ช่วยให้เครื่องจักรสามารถเชื่อมต่อและแลกเปลี่ยนข้อมูลกันได้แบบเรียลไทม์ผ่านเครือข่ายอินเทอร์เน็ต ทำให้สามารถตรวจสอบสภาพการทำงานของเครื่องจักรได้อย่างต่อเนื่อง การตรวจจับปัญหาก่อนเกิดความเสียหายจะช่วยลดค่าใช้จ่ายในการซ่อมบำรุงและยืดอายุการใช้งานของเครื่องจักร ในโรงงานอุตสาหกรรม เครื่องจักรหมุนรอบเช่น มอเตอร์ ที่มักจะแสดงสัญญาณความผิดปกติในรูปของการสั่นสะเทือนที่ผิดปกติ และโดยทั่วไปมักไม่มีเซนเซอร์ตรวจจับการสั่นสะเทือนเนื่องจากค่าใช้จ่ายที่สูง งานวิจัยนี้จึงมุ่งพัฒนาแบบจำลอง AI ร่วมกับระบบ IoT ในการตรวจจับและวิเคราะห์การสั่นสะเทือนจากเครื่องจักร โดยใช้ ADXL345 Accelerometer และ ESP32 Microcontroller ซึ่งมีทั้งประสิทธิภาพและราคาที่ย่อมเยาว์ โดยเริ่มต้นจากการเก็บข้อมูลการสั่นสะเทือนจากมอเตอร์ทดลองและปรับข้อมูลให้เป็นรูปแบบ Frequency Domain ด้วยวิธี Fast Fourier Transform (FFT) ต่อมาใช้ข้อมูลนี้ในการฝึกและทดสอบแบบจำลอง AI เพื่อนำมาใช้งานบนอุปกรณ์ โดยการเชื่อมโยงการรับส่งข้อมูลผ่านอินเทอร์เน็ตเป็นระบบ IoT งานวิจัยนี้แสดงให้เห็นถึงความเป็นไปได้ในการพัฒนาระบบตรวจสอบการสั่นสะเทือนที่มีราคาย่อมเยาว์ โดยใช้เทคโนโลยี AI และ IoT ในการบำรุงรักษาเครื่องจักรในภาคอุตสาหกรรม