Industrial Engineering Commons^™

Mathematical Modelling Of Nitrification And Denitrification Processes Based On Neuro-Fuzzy Bioreactor Models, Mirkhalil Agzamovich Ismailov, Boburbek Zokirjon Ugli Mannobjonov

Technical science and innovation

This paper presents the development and investigation of hybrid neural network and fuzzy models for the mathematical modelling of nitrification and denitrification processes in a biological wastewater treatment bioreactor. A comprehensive approach is proposed, integrating a mechanistic model of the ASM1/ASM2d type with neural networks (LSTM and Gaussian Process Regression), as well as a fuzzy control system based on an extended set of expert rules. A digital twin of the bioreactor was developed to allow for the prediction of the dynamic behavior of key parameters such as NH₄⁺, NO₃⁻, dissolved oxygen, etc. within a prediction range of 1 to 12 …

Integrating Gis With Interim Payment Valuation In Road Construction Projects: A Conceptual Framework, Abdulrahman I. Iro, Juma M. Matindana, Julian Ijumulana

Tanzania Journal of Engineering and Technology (TJET)

Abstract

Interim Payment Valuation is a critical process in road construction contract administration, yet conventional valuation practices remain heavily dependent on manual measurements, fragmented documentation, spreadsheets, and professional judgement. These limitations can affect measurement accuracy, transparency, traceability, and the timeliness of payment certification. Although Geographic Information Systems have increasingly been applied to construction planning, quantity measurement, progress monitoring, infrastructure management, and decision support, their integration with contractual and financial processes for interim payment valuation remains insufficiently explored. This study therefore develops a conceptual framework for integrating GIS with Interim Payment Valuation in road construction projects. A PRISMA-guided structured literature review …

Voltage-Related Power Quality Issues And Impacts On Distribution Networks With Sensitive Loads - A Review, Godwin Elinazi Mnkeni, Jackson Justo, Aviti Thadei Mushi, Bakari M. M. Mwinyiwiwa

Tanzania Journal of Engineering and Technology (TJET)

Voltage disturbances are the most important power quality (PQ) complications that customers and power utilities face in this smart era. The growing adoption of sophisticated electronic equipment and integration of renewable energy sources (RES) into power grids has increased the susceptibility of power distribution networks (PDNs) to voltage sags, swells, interruptions, flicker, and voltage imbalance. These disturbances, mainly caused by upstream faults, switching operations, and RES integration, compromise voltage PQ and system reliability. Consequently, they accelerate equipment degradation, increase electronic waste (e-waste), raise reactive power demand and maintenance costs, increase power losses, and impose substantial economic losses on customers and …

Thermal Monitoring Of Solidification In Molded Casting Of Drone Landing Leg, Sadettin Cem Altıparmak, Maher Zayed, Samuel Hawk, Mohamed Baddi, Jesus Degollado, Ahmed Bendaouia, Jianzhi Li

Manufacturing & Industrial Engineering Faculty Publications

This paper presents the design, fabrication, and thermal characterization of an acrylonitrile butadiene styrene (ABS) mold produced by fused deposition modeling (FDM) extrusion-based additive manufacturing used for the wax casting of a drone landing leg. A thermal monitoring framework, consisting of four K-type thermocouples logged at 1 s intervals, was deployed across six casting trials to capture the complete solidification cycle, yielding 84,717 time-stamped measurements. The study focuses on thermal data analysis and materials science interpretation through descriptive statistics, normality diagnostics, inter-trial Kruskal–Wallis tests, phase-duration analysis, rolling-variance monitoring, and inter-channel Pearson correlation. Key findings include a persistent spatial temperature hierarchy …

Spatial Markov Equilibrium Models For Taxi Services: Driver Decision, Search Friction, And Locational Pricing, Yanchao Liu

Industrial and Systems Engineering Faculty Research Publications

This paper develops a modeling framework for stochastic multi-agent systems and applies it to equilibrium and pricing analysis in urban taxi markets. Travel demand is represented as a trip network and embedded in a Markov chain that captures both locational and in transit taxi states, with transition dynamics reflecting trip durations, search frictions, spatial competition, and drivers’ perceptions of long-term value. The framework features a parametric Markov chain with endogenous transition probabilities and a behavioral model in which agents’ decisions depend on anticipated long-term rewards. We establish equilibrium existence and examine two locational pricing schemes that align individual incentives with …

Exploring Consultancy-Related Variations In Public Building Projects: A Review Towards A Management Framework, Grayson Bambaza, Ismail W. R. Taifa, George S, Mwaluko

Tanzania Journal of Engineering and Technology (TJET)

Consultancy-related variations remain one of the leading causes of cost overruns, schedule delays, quality deficiencies, and contractual disputes in public building projects. Although various studies have been undertaken to document the causes of variations in construction works, the same level of interest has not been shown for consulting services variations across the consulting services spectrum and their consequences for effective management. This study explores variations in consulting services for public works by systematically reviewing the existing literature using the PRISMA (Preferred Reporting Items for Systematic reviews and Meta Analyses) guidelines. Relevant articles published from 2020 to 2026 were retrieved from …

Decision Support Tool For The Maintenance Of Meter Gauge Railway Permanent-Way Infrastructures: A Concept Paper, Hamisi J. Maulid, Beatus A.T Kundi, Juma M. Matindana, Ismail W. R. Taifa Dr

Tanzania Journal of Engineering and Technology (TJET)

A Decision Support Tool (DST) represents a transformative way of modernising maintenance practice on the permanent-way infrastructure of Meter Gauge Railway (MGR). Maintenance practice remains largely reactive, as the MGR plays a strategic role in transporting both freight and passengers, resulting in inefficient resource allocation, high operational risk, and growing Lifecycle expenses. This concept paper explores the potential and the design challenges for a DST that combines fuzzy analytic hierarchy process (Fuzzy-AHP) modelling, multi-criteria decision analysis (MCDA), Geographic Information Systems (GIS) and predictive machine learning (ML) analytics for evidence-based, future-oriented maintenance management. The paper draws on peer-reviewed studies from …

Optimization Of Gas Consumption, Cost And Production Rate For Computerized Numerical Control Oxy-Acetylene Flame Cutters, Eustace K. William, Simon I. Marandu, Enock W. Nshama

Tanzania Journal of Science

This study examined the impact of flame cutting parameters (i.e., cutting speed, plate thickness and nozzle diameter) on oxy-acetylene gas consumption, cost and production rate. A full factorial design of experiments was used to generate 27 experiments, which were conducted using a CNC flame cutter. The analysis of variance (ANOVA) method was used to determine significant process parameters, followed by regression analysis using the MINITAB ® software. The technique for order preference by similarity to ideal solutions (TOPSIS) was used to determine the optimal cutting parameters for minimizing the consumption and cost estimation of oxy- acetylene gas and maximizing the …

Bridging Models And Real-World Performance: Capturing Represented, Hidden, And Unrepresented Dynamics In Complex Systems, Dixizi Liu

All Dissertations

Complex systems often depend on adaptive performance that is difficult to capture using structured data or formal models alone. This dissertation asks how predictive modeling, coordination-cost measurement, and simulation can be integrated to better represent the visible, hidden, and unrepresented dynamics that shape real-world system performance.

Sterile Processing Departments (SPDs) provide the empirical context for this work because they support safe and timely surgical care while operating under high workload variability, time pressure, and tight coordination with operating rooms. Hospitals rely on SPDs to clean, assemble, sterilize, and deliver surgical instrument trays so surgeries can start on time and proceed …

Human-Centered Design Of Extended Reality For Learning Adoption, Effectiveness, And Collaborative Training Performance, Bhargav Upadhyay

All Dissertations

Extended reality (XR) technologies like virtual reality (VR) and augmented reality (AR) can be used for technical training to help students learn and practice complex tasks in a safe digital environment. Despite known benefits evidence is required to explore the effectiveness of these technologies to support student learning outcomes. Furthermore, technical training programs need evidence about when these tools improve learning, what are the barriers to adoption of these technologies, and how training should be designed by leveraging these technologies. This dissertation examined how XR technologies can support higher education and workforce training, specifically focusing on barriers and facilitators to …

A Hybrid Machine Learning-Based Feasibility Prediction Of 3d Mechanical Designs Using Scalar And Geometric Features, Md Mohsin Uddin Fahim

Open Access Theses & Dissertations

The computational bottleneck of structural feasibility screening frequently hinders the transition from a digital 3D model to a physically manufactured component. Traditionally, engineers have relied on either overly rigid heuristic constraint checks or computationally exhaustive finite element simulations. To address this inefficiency, this thesis proposes and validates a hybrid machine-learning framework to predict the structural manufacturability of 3D mechanical designs. Moving beyond the conventional reliance on isolated scalar parameters, the proposed methodology extracts and integrates both scalar manufacturing constraints (e.g., tolerance, minimum feature thickness) and spatial geometric descriptors (e.g., bounding volume, aspect ratio) directly from STL mesh data. Utilizing a …

Prevention Vs Detection: A Discrete-Event Simulation Assessment Of Inspection Staffing, Pick-To-Light, And Ai-Based Inspection In Aerospace Wire Harness Kitting, Jorge Mares

Open Access Theses & Dissertations

Aerospace wire harness manufacturing operates under conditions that standard industrial engineering methods were not designed to address. Volumes are low, configurations change between orders, assembly is performed manually by certified labor that cannot be expanded quickly, and IPC/WHMA-A-620 Class 3 acceptance requires that every unit be verified rather than sampled. Kit assembly concentrates the resulting risk, because each item retrieved from the rack is an independent selection decision, and the attributes distinguishing a correct item from an incorrect one are frequently not visible to the operator. Errors introduced there are discovered downstream, after substantial certified labor has been invested. A …

A Causal Inference Protocol For Root-Cause Diagnosis In Non-Stationary Industrial Time Series, Cansu Yalim

Engineering Management & Systems Engineering Theses & Dissertations

Industrial fault diagnosis increasingly relies on data-driven methods, yet most approaches assume process stationarity and treat association-based rankings as sufficient evidence for root-cause identification. Neither assumption holds when operating phases and fault progression create distinct behavioral regimes with shifting relationships among variables, and neither answers which feasible corrective action would alter a fault trajectory. The absence of a procedure addressing non-stationarity, causal identifiability, and decision-relevant effect estimation constitutes the gap this dissertation targets. In this context, a regime is a time period in which the process operates under a relatively consistent setting, so the relationships among variables are approximately stable …

Spatial Analysis Of The Environmental And Climatic Explanatory Relationship Of Photovoltaic Potential For Sustainable Shrimp Farming, Dyah Lestari Widaningrum, Roikhanatun Nafi'ah, Religiana Hendarti, Alexandra Catherine Djunaedi, Evaristus Didik Madyatmadja

Journal of Environmental Science and Sustainable Development

Sustainable shrimp aquaculture requires reliable and affordable energy, particularly for coastal pond aeration. However, identifying suitable locations for photovoltaic (PV) deployment remains challenging because ground-based solar-resource measurement is expensive, spatially limited, and difficult to maintain across large coastal regions. This study develops a village-level spatial framework to evaluate PV potential for shrimp aquaculture using open geospatial datasets. The analysis covered villages across Central Java, Special Region of Yogyakarta, and East Java. PV power potential (PVout), Global Horizontal Irradiation (GHI), and Direct Normal Irradiation (DNI) were obtained from the Global Solar Atlas; land surface temperature (LST) and precipitation were derived from …

Leveraging Data Science And Analytics For Next-Generation Transportation And Logistics: Literature Review And Regional Analysis, Kazi Humayra Shams

Graduate Theses and Dissertations

The increasing integration of data science and analytics into next-generation transportation and logistics planning and operations offers improved system performance but requires managing and interpreting vast and complex datasets. The Arkansas Smart Transportation Research, Infrastructure and Data-Driven Engineering Systems (AR-STRIDES) program (NSF Award No. 2445877) is working to develop data science solutions and data-driven supply chain technologies for next-generation transportation and logistics systems. This thesis supports AR-STRIDES by providing a comprehensive literature review of recent literature studying data science and analytics in transportation and logistics systems and conducting a regional analysis of Arkansas to create a database of companies, higher …

Customer Adoption And Trust In Indonesian Islamic Banking: A System Dynamics Perspective, Imam Wahyudi Mr., Komarudin Komarudin, Prof. Rifki Ismal

ASEAN Marketing Journal

Research Aims: This study reframes the growth challenge of Indonesia’s Islamic banking as a financial-service marketing problem: strengthening customer adoption, trust, and perceived value to expand market penetration in a dual-banking environment while maintaining resilience.

Design/Methodology/Approach: Using a system dynamics perspective, the study develops a causal loop diagram (CLD) grounded in a review of policy-document and prior empirical marketing/Islamic banking literature. A multi-actor lens is applied to map how regulators, government, customers, conventional banks, fintech, and ESG investors shape adoption and competitive dynamics.

Research Findings: The CLD identifies seven reinforcing loops that can accelerate adoption and market share (capability reinvestment, …

Adopting Critical Power Grid Infrastructure Technologies: An Organizational Cybersecurity Assessment Against Ransomware, Fayez Alsoubaie

Dissertations and Theses

For many years, researchers and practitioners have studied emerging technologies in field of energy production and distribution. Power grid systems carry major weights in the energy branch of the economy. Researchers and scientists have been interested in finding ways to connect the power grid gap and improve protection for its technologies.

The research supports organizational adoption and prioritization of critical cybersecurity technologies for ransomware protection in power grid infrastructure. As utilities increasingly integrate digital technologies, they become more vulnerable to sophisticated cyberattacks that can disrupt services and put public safety at risk. The main focus of the study is to …

Integrating Production And Repair Operations Through Data Driven Defect Flow Analytics For Yield And Resource Optimization In Pcba Manufacturing, Ali Tahmasebi, Yingge Zhou, Daryl Santos, Sai Srikanth Reddy Kolli, Edward Wong

Systems Science and Industrial Engineering Student Scholarship

In Printed Circuit Board Assembly (PCBA) manufacturing, maintaining a closed loop connection between production and repair operations is critical to improving product quality and operational efficiency. However, in the manufacturing environment that motivated this work, production and repair data are often managed separately, and repair findings are not systematically fed back to production teams, limiting visibility into defect routing patterns and repair workload drivers. This study developed a data-driven framework that integrates production and repair data streams to analyze defect flow and support repair resource planning. The framework applies descriptive statistics, cross tabulations of repair inflow by product/project and repair …

A Simulation-Based Lean Six Sigma Framework For Process Optimization In Textile Manufacturing Toward Industry 4.0, Md Shafiqul Islam Chowdhury

Masters Theses

This study focuses on integrating simulation modeling with Lean Six Sigma (LSS) within the DMAIC (Define, Measure, Analyze, Improve, Control) framework for process optimization in textile manufacturing industry. Although traditional LSS framework such as Value Stream Mapping (VSM) and Root Cause Analysis are effective in identifying waste, they mainly rely on static and historical data which make their capability limited for real analysis or predictive decision making. As a result, many textile manufacturing processes still face challenges such as production delays, excessive work-in-process (WIP), high cycle time, and inefficient resource utilization. To address this issue, this research proposes a simulation-based …

Investigation Of Process Parameters To Fabricate Tiwmo Refractory Medium Entropy Alloy Via Laser Powder Bed Fusion, Abdullah Al Masum Jabir, Lindsey A. Salazar, Jianzhi Li

Manufacturing & Industrial Engineering Faculty Publications

This paper presents an experimental study on the fabrication of a TiWMo refractory medium-entropy alloy (RMEA) using laser powder bed fusion (PBF-LB/M, commonly known as selective laser melting) from elemental powders as well as successful alloy formation on titanium substrates. The effects of tungsten particle size and process parameters on successful TiWMo RMEA fabrication have been explored using scanning electron microscopy (SEM), x-ray diffraction, hardness measurement and microstructural analysis. Scanning electron microscope (SEM) analysis revealed that the lowest percentage (0.01%) of unmelted tungsten particles was observed at a laser power of 350 W and scanning speed of 250 mm/s, particularly …

A Novel Hexagonal-Zigzag Cellular Infill Structure For Additive Manufacturing, Md. Saidur R Roney, Amm Nazmul Ahsan, Prosenjit Barua

Manufacturing & Industrial Engineering Faculty Publications

The rigidity of the Additively Manufactured objects can be tailored by manipulating the infill lattice type and density. In this research, an island type novel infill structure termed as Hexagonal-Zigzag pattern is introduced, and its mechanical performance is investigated. In this pattern, the zigzag raster reflects the repeating hexagonal shaped cell constituting the parallel-oriented islands and 90° rotation of the pattern in each layer distributes the island span along both transverse and longitudinal directions of the printing contour. A mathematical model is established to illustrate the effect of the infill parameters on hexagon unit cell size and relative infill density. …

Can Generative Ai Make Farming Decisions? Current Status And Future Pathways: A Case Study In Row Crop Production With Chatgpt, Nipuna Chamara, Yufeng Ge, Joe Luck, Yu Pan, Saleh Taghvaeian, Cory Walters, Christopher Proctor, Daran Rudnick, Daren Redfearn

Department of Agricultural and Biological Systems Engineering: Faculty Publications

The agricultural decision-making process is experience-based, knowledge-dependent, time-sensitive, complex, and driven by historical data. Planting, fertilization, irrigation, and chemigation are key categories in farm decision-making, and currently there is no one-shot decision-support tool that covers all these activities. Generative Artificial Intelligence (AI) models are more advanced than traditional machine learning and deep learning models. These models have been trained on vast amounts of data from the internet, allowing them to accept unstructured data in various forms and generate human-like text, solutions to problems, and scenario predictions. Given this capability, we became interested in exploring the potential of generative AI in …

Bridging Images And Language In Radiology: A Comprehensive Prisma Systematic Review Of Transformer Vision-Language Models And Clinical Readiness, Mohammad T. Khasawneh Dr., Sadaf Tabatabaee

Systems Science and Industrial Engineering Student Scholarship

Transformer vision-language models (VLMs) promise end-to-end automation of radiology reporting and related multimodal tasks. However, evidence remains fragmented across datasets, architectures, evaluation practices, and levels of clinical validation, limiting fair comparison and safe translation into practice. Following PRISMA 2020/PRISMA-S, search engines including PubMed, IEEE Xplore, Web of Science, and Google Scholar were systematically searched for peer-reviewed, English-language studies published between 2019 and 2025 that used paired radiology images and free-text reports. Dual reviewers screened records and extracted data using a locked schema covering datasets, modalities, architectures, training objectives, evaluation metrics, and indicators of clinical readiness. Free-text model descriptions were normalized …

Material Costs, Karima Weinman

Masters Theses

This thesis investigates how migration fatality and disappearance data can be reinterpreted through material craft to create a more reflective encounter with information. Working with the Missing Migrants Project's dataset, this project asks how design can communicate dimensions of human loss that conventional data visualization cannot reach.

The work situates contemporary border violence within a longer colonial history, arguing that the logics of surveillance and quantification that structured European imperial expansion persist in the databases that govern mobility in the Mediterranean today.

Terrazzo is a 15th-century Venetian flooring technique built from discarded fragments bound together into a unified surface. This …

Data Driven Estimation Of Pore Size Using 1d Light Emissions For Laser Powder Bed Fusion Additive Manufacturing, Jose Galarza, Jorge Barron, Luis Jimenez, Tamer Oraby, Jianzhi Li, Farid Ahmed

Manufacturing & Industrial Engineering Faculty Publications

The quality assurance of the Laser Powder Bed Fusion Process (LPBF) has been extensively investigated over the last decade for in-situ monitoring of metal additive manufacturing. The process inherently generates voids within the bulk of the part, which can detrimentally affect the quality of the printed part. The characterization of these voids by estimating their size and identifying their geometrical features remains a challenge. This study introduces a Machine Learning (ML) based framework for estimating void sizes of varying geometries using layer-wise one-dimensional (1D) average light intensity signal obtained from the optical tomography system during the 3D printing of metallic …

Improving And Supporting Flight Instructor’S Decisions For First Solo, Isabella Piasecki

Theses and Dissertations

Flight instructors have the burden of determining when a student is ready for their first solo flight, and many have expressed uncertainty over their own decision-making skills during this phase of a student’s training. Prior studies have examined flight instructors’ pre-solo decisions in other countries, but no such study has been conducted with American flight instructors. For this study, current flight instructors with multiple prior endorsements for a student pilot’s first solo were interviewed to identify the more abstract concepts they use to guide their decision. Qualitative themes were identified from their experiences. Using this information, a checklist was developed …

Feasibility-Aware Deep Reinforcement Learning For Sustainable Timber Procurement Under Hurricane Demand Uncertainty, Jarod Wright

Theses and Dissertations

The timber supply chain connects landowners and mills to provide wood products but faces challenges from stochastic demand, seasonal variations, and disruptions such as hurricanes. Fur- thermore, sustainability concerns like transportation emissions create trade-offs in procurement. This study proposes a feasibility-aware Deep Reinforcement Learning framework for sustainable timber procurement and inventory control under joint demand–hurricane uncertainty. We develop a stochastic mathematical model capturing mill-landowner interactions, seasonal demand, hurricane- driven pricing, and carbon emissions. The problem is formulated as a constrained Markov decision process and solved using Proximal Policy Optimization with a feasibility-enforcing layer. A Mississippi-based case study with 2,100 landowners …

Machine Learning-Based Decision Support Models With Applications In Postsecondary Education, Marco Paolo Anglesio

Theses and Dissertations

This dissertation investigates the deployment of machine learning methodologies in an industrial engineering framework for the development of advanced decision support systems in the context of enrollment management. Drawing on techniques from educational data mining, the research addresses three key phases in the lifecycle of traditional and non-traditional students. First, it analyzes student retention using predictive classification models designed to identify individuals at elevated risk of attrition. Second, it employs temporal convolutional networks for time series forecasting, estimating aggregate enrollment levels over highly variable, finite planning horizons on the basis of partially observed data and using an asymmetric loss function. …

Development Of A Putting Green Manufacturing Process, Jose Andres Cepeda Santiago

Honors Theses

Our Capstone project investigates the end-to-end design, development, and production of a 6‑foot long portable putting green marketed for individuals seeking a high quality, competitively priced golf product for home or office use. The capstone project examines the full lifecycle of product creation applying manufacturing principles learned through the center of manufacturing’s coursework. From the initial concept through engineering design, market research, prototyping, manufacturing optimization, and final production the project emphasizes cross‑functional collaboration across engineering, business, and accountancy majors. Methods used to gather data included marketing surveys, CAD drawings, time studies during production runs, value stream mapping, and controlled documentation …

Modeling Individual Self-Protective Behavior During Epidemics, Geonsik Yu, Michael J. Garee, Mario Ventresca, Yuehwern Yih

Faculty Publications

Protecting public health from infectious diseases requires collective action, as individual behaviors—such as vaccination and mask-wearing—directly influence disease dynamics. During the COVID-19 pandemic, unexpected public responses often undermined the effectiveness of interventions, highlighting the need to understand collective behavioral patterns and motivations to design more effective mitigation strategies. This study presents an agent-based simulation model that captures how individuals adjust self-protective behaviors based on evolving opinions about disease risk and examines how these decisions interact with external factors, such as public health interventions, to shape collective outcomes. To improve the representativeness of the simulated population, multiple datasets were integrated to …