Operations Research, Systems Engineering and Industrial Engineering Commons^™

Artificial Intelligence And Additive Manufacturing As A Coupled Design System: Rethinking Inference, Manufacturability, And Design Education, Charul Chadha, Garth Crosby, Sabit Ekin, Mohamed Gharib, Eman Hammad, Congrui Jin, Ali Ahmad Malik, Noemi Mendoza Diaz, Calahan Mollan, Monsuru Ramoni

Manufacturing & Industrial Engineering Faculty Publications

Artificial intelligence (AI) is becoming deeply integrated into additive manufacturing (AM) workflows, reshaping how designers approach geometry, materials, and process constraints. AI holds significant potential by accelerating design exploration, revealing complex patterns in AM behavior, and supporting earlier assessment of manufacturability. At the same time, it introduces new risks related to model transparency, data quality, physical validity, and the potential for overreliance by students and practitioners. This perspective examines these issues through four guiding questions that address the role of AI in AM-enabled design, the gaps that limit or enable AI contribution, the implications for engineering education, and the responsibilities …

Harnessing Ml And Iiot For Traceability In Continuous Production Systems: A Conceptual Framework, Kholoud M. Abdelaal

Theses and Dissertations

In the era of rapid technological advancement, the manufacturing sector faces increasing pressure to leverage emerging technologies to enhance operational efficiency and minimize waste. In this context, traceability plays a pivotal role, as it provides complete visibility of processes and products throughout manufacturing systems, enabling them to identify areas for improvement and take corrective actions accordingly. Additionally, traceability ensures compliance, supports product recalls, provides a clear understanding of the system’s performance, and enables fact-driven decision-making in multiple aspects of the manufacturing system. Although the broad spectrum of traceability applications in batch production-based plants, traceability remains challenging to achieve in continuous …

Performance, Economic And Environmental Evaluation Of A Solar-Assisted Vacuum Deaeration Heating System., Liew Shan Kun

Student Works (2020-2029)

This research evaluates the performance of a solar-assisted heating (SAH) system for makeup water in a vacuum deaeration process. The system integrates solar energy into the heating process, with parametric analysis conducted across varying configuration of total solar radiation and water flow rates. The total solar radiation at the experimental site in Kuala Kangsar, Perak, Malaysia, characterized by tropical weather, fell within the range between 414W/m2 to 568W/m2. Performance analysis showed that a flow rate of 0.4 LPM achieved the target temperature of 61°C required for the deaeration process. Thermal efficiency peaked at 62.60% under a solar radiation of 900 …

Reinforced Scan: A Reinforcement Learning Enabled Optimal Laser Scan Path Planning In Laser Powder Bed Fusion Additive Manufacturing, Chaoran Dou, Jihoon Chung, Raghav Gnanasambandam, Yuhao Wu, Jianzhi Li, Zhenyu James Kong

Manufacturing & Industrial Engineering Faculty Publications

Additive Manufacturing is an innovative technology that fabricates parts layer by layer. However, in Laser Powder Bed Fusion (LPBF), printed metal parts often exhibit residual stresses, deformations, and other defects due to non-uniform temperature distribution during the printing process. To mitigate these issues, an optimized scan sequence within each layer can improve thermal uniformity. Traditional optimization methods, which rely on domain knowledge and employ trial-and-error or heuristic approaches, often fail to achieve optimal solutions due to the complex nature of the problem. One major challenge in improving scan strategies lies in the vast search space required to optimize the scan …

Long Short-Term Memory (Lstm) -Based Neural Network Model For Optimizing Composite Manufacturing Process Using Autoclave, Sourav Bolar, Steven Corns, Nayan Pundhir, Kumbla Chandrashekhara

Engineering Management and Systems Engineering Faculty Research & Creative Works

Producing high-quality fiber-reinforced composites requires precise temperature control during autoclave curing, as even small variations can lead to defects that compromise strength and reliability. At the same time, manufacturers aim to reduce energy use and shorten curing cycles without sacrificing material performance. To address these challenges, this study develops a data-driven Long Short-Term Memory (LSTM) neural network model capable of forecasting temperature evolution inside the autoclave throughout the curing cycle. The model is trained on time-series temperature data collected from multiple sensing locations, enabling it to learn the spatial and temporal trends that govern heat flow during curing. Data augmentation …

Direct Ink Writing Of Shear Exfoliated Two-Dimensional Nanomaterial- Elastomeric Multifunctional Nanocomposite, Md Abdur Rahman Bin Abdus Salam, Asif Hasan Ridoy, A K M Abirul Haque, Muhammad Shahbaz Rafique, Md Arafat Hossain, Md Shahriar Forhad, Matthew G. Boebinger, Farid Ahmed, Karen Lozano, Ali Ashraf

Manufacturing & Industrial Engineering Faculty Publications

Direct ink writing (DIW) of polymer nanocomposites with high loadings of two-dimensional (2D) nanofillers (graphene and hexagonal boron nitride (hBN)) is challenging because of potential clogging, use of hazardous solvents, and agglomeration. Here, in this work, a shear exfoliation and sieving method to prepare DIW ink with high loading of nanofillers produced from low-cost bulk layered materials such as graphite and bulk hBN powder for successful DIW printing without the use of any solvents, binders, or plasticizers. The single-step exfoliation technique resulted in a composite with substantial layer reduction along the c-axis, as confirmed by SEM, TEM, XRD, and Raman …

Ai-Based Porosity Detection In Babbitt Bore Turning, Kaylee Leggett, Hannah Adams Gemmell, Kaisa Shingleton

Williams Honors College, Honors Research Projects

For this project, an external company reached out to the University of Akron requesting assistance with defect detection during their vertical turning operations. As babbitt is removed in a vertical turning process, it occasionally reveals defects, mainly porosity, which can lead to costly downstream failures of the part. Current inspection techniques involve use of dye penetrant, which is time consuming, labor intensive, unergonomic, and a source of human error. The goal of the project is to create an alternative inspection method using an AI-based machine-learning model. After the turning operation, a camera is deployed to perform an in-place inspection, taking …

Lean Service System Optimization In U.S. Automotive Maintenance Centers: A Time Study And Simulation-Based Approach To Reducing Service Cycle Time And Increasing Efficiency, Rakibul Hasan Sarker

All Graduate Theses, Dissertations, and Other Capstone Projects

The primary objective of this study is to measure the current service time at a U.S. automobile service center, with the aim of reducing waste and optimizing service operations through time study and simulation modeling. Inefficiencies in those service centers increase service time and labor costs, reduce service quality, and reduce workshop productivity, thereby increasing customer waiting time. In this study, real-world shop floor data were collected from a single service center, namely Jiffy Lube. Over the course of ten working days, 205 vehicle data points were acquired. Service time, bay time, and overall process time were computed and examined …

A Study Of Perceptions, Readiness, Benefits, And Barriers Related To Exoskeleton Adoption In New Jersey’S Warehousing Sector, Terry Asante

Theses

The warehousing industry in New Jersey remains a vital component of the region's logistics network, employing more than 200,000 workers who routinely engage in lifting, bending, overhead reaching, and other physically demanding activities. These exposures contribute to musculoskeletal disorder (MSD) rates that exceed national averages, particularly affecting the low back and shoulders. Nationally, MSDs account for an estimated $420 billion in combined direct and indirect costs each year, underscoring the need for interventions that can effectively reduce biomechanical strain. Industrial exoskeletons have emerged as a potential solution, with prior research demonstrating reductions in muscle activation, perceived exertion, and fatigue during …

Analysis Of Leakage In Nearshore Pipelines Using Fitness For Service Method To Ensure Mechanical Integrity Based On Api-579 Level 3, Elriandri Elriandri, Dedi Priadi

Journal of Materials Exploration and Findings

The Fitness for Service (FFS) analysis is performed as a quantitative assessment to evaluate the integrity condition of a pipeline. Essentially, FFS assessment helps determine whether equipment components can operate safely despite existing deficiencies. This evaluation is carried out using the Finite Element Method (FEM). In the case of an underwater pipeline that experiences leak due to anchor pull at the flange connection, it undergoes plastic deformation and is lifted approximately 1 meter. As a mitigation step, inspection and repairs have been carried out by the company. Subsequently, modeling is performed to reconstruct the deformation process of the pipeline. Then, …

Assessment Of The Melt Quality Of A 30% Scrap Adc12 Aluminium Alloy Using The Inclusion And Fluidity Measurement Instrument (Ifmi) With Mullite Ceramic Filters, Gusti Ruri Ruri Lestari, Sandya Ananda Riswan, Muhammad Anis, Ahmad Ashari, Paramita Vidya Ayuningtyas, Bambang Suharno Prof, Donanta Dhaneswara

Journal of Materials Exploration and Findings

The increasing demand for sustainable practices in the metal casting industry has driven the use of recycled aluminum alloys such as ADC12. However, the addition of aluminum scrap tends to increase oxide inclusions, which reduce melt fluidity and compromise casting quality. This study utilizes the Inclusion and Fluidity Measurement Instrument (IFMI), equipped with mullite ceramic filters, to assess the melt quality of ADC12 aluminum alloy containing 30% scrap. Fluidity and inclusion characteristics were evaluated at five pouring temperatures (660°C, 680°C, 700°C, 720°C, and 740°C). The results show that fluidity increased with temperature, reaching a peak of 84.6 g·s⁻¹ at 740°C, …

Equipment Criticality Analysis To Determine Asset Integrity Management System Scheme In Supporting Production Optimization Scenarios In The Aeging Field, Donny Andryanto, Donanta Dhaneswara

Journal of Materials Exploration and Findings

This research investigates the production decline and cost increase in the X&Y oil and gas fields from 2022 to 2023. Production fell by 34%, while production costs per barrel rose by 79%. To address these issues, a series of optimization processes are proposed. These aim to restructure and enhance the production facilities to reduce current production costs. The optimizations include reducing pressure at the PPP Platform in 2024. Additional steps include shutting down CPP-ORF 14” pipelines and most processes at CPP 2 Platform by 2027 to convert it into an accommodation platform. Further, the plan involves optimizing the release of …

Morphological Test Of Areca Nut Fiber Ceramic Membrane Using Scanning Electron Microscopy Energy Dispersive X-Ray Mapping Spectroscopy, Amelia Marzain, Siti Umi Kalsum, Marhadi Marhadi, Ahmad Nabil Shahab

Journal of Materials Exploration and Findings

This study investigates the potential of ceramic membranes derived from areca nut fiber as a cost-effective and environmentally sustainable material for the removal of iron (Fe) and manganese (Mn) from groundwater. Two types of membranes were fabricated: one without activation and one chemically activated using 10% sodium hydroxide (NaOH). The morphological and elemental characteristics of both membranes were analyzed using Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray (EDX) mapping. The concentrations of Fe and Mn before and after treatment were measured using Atomic Absorption Spectroscopy (AAS). The NaOH-activated membrane exhibited a more porous surface structure and higher oxygen content, …

Detecting Non-Axisymmetric Instabilities In Fluid-Based Manufacturing Via Multi-View Tensor Analysis., Bidusi Khadka

Electronic Theses and Dissertations

Fluid-based manufacturing processes, such as inkjet printing and electrospinning, fabricate micro- and nano-scale structures with high precision, but are prone to complex fluid dynamics exhibiting axisymmetric and non-axisymmetric instabilities. Conventional monitoring often relies on single-camera inputs and symmetry assumptions, limiting the detection of three-dimensional anomalies like jet deflection. This study presents a novel multi-view streaming video-based anomaly detection framework to address this gap. The framework employs a modified Tensor Sequential Sampling (TSS) algorithm with edge-based sampling to capture geometric spatiotemporal features of each camera view using the videos obtained from an orthogonally positioned dual-camera setup. These features are fused with …

Full Factorial Design Of Carbon Content And Heating Temperature On Height Reduction In Bonnell Springs, Yurida Ekawati, Cendana Anggun Sasmitha, Mochamad Syamsul Ma’Arif

Journal of Mechanical Engineering Science and Technology (JMEST)

The durability of Bonnell springs, which are widely used in the manufacture of spring beds, is often compromised by height reduction during use, which negatively impacts product comfort and quality. This study aims to minimize spring height reduction by investigating the effects of heating temperature and carbon content in the spring steel. A full factorial experimental design was applied using two factors: heating temperature (250°C, 260°C, and 270°C) and carbon content (0.72%, 0.73%, and 0.74%). Nine treatment combinations were tested, with five replicates each, and the height reduction values were measured after 100 compression cycles. The data were analyzed using …

Experiential Learning And The Revitalization Of Manufacturing Education At The University Of Dayton, Sean Cahill

Research and Reflection on Learning and Teaching in Higher Education

This perspective paper explores the role of experiential learning in preparing future-ready manufacturing engineers at the University of Dayton, set against the backdrop of Dayton’s legacy as an industrial innovator and the broader national movement to revitalize domestic manufacturing. As automation, cyber-physical systems, and Industry 4.0 technologies reshape the manufacturing landscape, there is a growing need for engineers who possess both technical fluency and systems-thinking capabilities. To meet this need, the manufacturing engineering technology department implemented hands-on, integrated lab-and-lecture modules through support from the Experiential Learning Innovation Fund for Faculty (ELIFF). Grounded in Kolb’s Experiential Learning Theory and constructivist learning …

User Interface And Watchstation Improvements Required For Multi-Vehicle Usv Operations, Val Schmidt, Joshua Bergeron

Faculty Publications

In October 2024, the University of New Hampshire and NOAA’s Uncrewed Systems Office embarked on a mapping mission in the Gulf of Maine, simultaneously operating two DriX Un-crewed Surface Vehicles. Goals of the project were focused on testing hypotheses related to concepts of operation, including the safety of operations, cognitive loading of operators, management of vehicle endurance, vehicle logistics, maintenance and field support, refueling and a host of others.

Intelligent Real-Time Flotation Froth Stability Monitoring Using Embedded Computer Vision: Lead (Pb) Processing Case Study, Ahmed Bendaouia, Taha Ismaili, Ismail Najib, Oussama Hasidi, Intissar Benzakour, Jianzhi Li, El Hassan Abdelwahed

Manufacturing & Industrial Engineering Faculty Publications

Froth stability in flotation refers to the ability of the froth layer to remain intact and avoid collapsing during the flotation process. A stable froth layer is crucial to maximizing mineral recovery and ensuring the efficient operation of flotation cells. Several factors influence the stability of the froth, including the depth of the froth, the crowding, the size of the bubbles, and the rate of movement of the froth. In this study, our main objective is to analyze and evaluate froth stability in real time, since it plays a critical role in process optimization for flotation-based mineral processing. We propose …

Process-Driven Manufacturability Constraints In Design For Wire Arc Additive Manufacturing, Monsuru Ramoni, Sampson Gholston, Albert E. Patterson

Manufacturing & Industrial Engineering Faculty Publications

Wire arc additive manufacturing (WAAM) has emerged as a useful option for large-scale metal additive manufacturing. It has gained widespread use in the aerospace industry and other applications that require large and complex custom parts. The process is a combination of a precise control system and a welding process, typically GTAW or MIG welding. It is a member of the directed energy deposition (DED) family of AM processes. Compared with many metal AM processes, it is relatively simple and cost-effective but almost always requires a significant amount of postprocessing before parts can be used. The AM-based nature of the process …

Adoption Of Agrivoltaics In Developing Countries: A Review On Challenges, Opportunities And Future Prospects, Abdi J. Athumani, Pater Makolo

Tanzania Journal of Engineering and Technology (TJET)

This paper provides a review of agrivoltaics technology and how it has been applicable in developing countries, including African countries. Agrivoltaics, the integration of agricultural production with photovoltaic energy generation, offers promising solutions to water- energy-food nexus in developing countries. This technology offers the dual benefit of increasing agricultural productivity while generating clean energy, which is very important for regions facing frequent electricity shortages and declining agricultural yields due to climate change. However, despite its potential, the adoption of agrivoltaics in developing nations remains limited in comparison to developed countries due to financial, technical and policy constraints. This paper explores …

Cnn-Based Hybrid Model For Detecting Blight Diseases In Potato Crops With Advanced Image Processing Techniques, Farian S. Ishengoma

Tanzania Journal of Engineering and Technology (TJET)

Potato production plays a vital role in global agriculture as a major food source for large populations. However, potato crops are highly susceptible to diseases, particularly Early Blight and Late Blight, which result in substantial yield losses. Timely detection and effective control of these diseases are essential for maintaining stable crop output. This study explores the integration of Convolutional Neural Networks (CNNs) and advanced image processing techniques to differentiate between diseased and healthy potato plants accurately. Two datasets comprising original and enhanced images were used to train four CNN models: InceptionV3, Xception, Densenet201, and Resnet152V2. The original images underwent background …

Transparent Eeg Analysis: Leveraging Autoencoders, Bi-Lstms, And Shap For Improved Neurodegenerative Diseases Detection, Badr Mouazen, Ahmed Bendaouia, Omaima Bellakhdar, Khaoula Laghdaf, Aya Ennair, El Hassan Abdelwahed, Giovanni De Marco

Manufacturing & Industrial Engineering Faculty Publications

Highlights

• Novel hybrid architecture: Combined autoencoders with bidirectional LSTM networks for enhanced EEG signal classification, achieving 98% accuracy in distinguishing AD, FTD, and healthy controls.

• Explainable AI integration: Implemented SHAP (SHapley Additive exPlanations) framework to enhance model transparency and identify entropy as the most influential feature for neurodegenerative disease detection.

• Optimal temporal segmentation: Demonstrated that 5-s EEG windows with 50% overlap provide the best balance between classification accuracy and computational efficiency.

• Comprehensive feature extraction: Utilized Power Spectral Density (PSD) analysis across standard frequency bands (Delta, Theta, Alpha, Beta, Gamma) following autoencoder-based dimensionality reduction.

• Superior performance validation: Outperformed traditional machine learning …

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Using Statistical Clustering Of Trajectory Data To Support Analysis Of Subject Movement In A Virtual Environment, Martin Galicia Avila, Douglas Timmer, Alley C. Butler

Manufacturing & Industrial Engineering Faculty Publications

Gracia de Luna conducted experiments with an HMD virtual environment in which human subjects were presented with surprise distractions. His collected data for head, dominant hand, and non-dominant hand included 6 DOF human subject trajectories. This paper examines this data from 57 human subject responses to those surprise virtual environment distractions using statistical trajectory clustering algorithms. The data is organized and processed with a Dynamic Time Warping (DTW) algorithm and then analyzed using the Density Based Spatial Clustering (DBSCAN) algorithm. The K-means method was used to determine the appropriate number of clusters. Chi Squared goodness of fit was used to …

A Study Of Wear Measurement And Life Prediction Of Insert Chute Liner On Gold Ore Processing, Ferry Ardika Natanael, Nony Maulidya, Dedi Priadi

Journal of Materials Exploration and Findings

Chutes are critical materials handling assets to transport solid particles from one process step to another in mineral processing, coal mining and cement industries. The material transport, because of material characteristics, cause severe wear on internal lining of chutes or bins’ structure. The wear problem on internal lining of bins or chutes needs to be checked to keep production efficiency. Therefore, not checked wear rate causes liner replacement schedule becomes unpredictable. It leads to production loss and highly cost maintenance in industry. This study shows that condition-based maintenance through regular thickness measurement using Ultrasonic Transducer (UT) to predict life service …

Techno-Enviro-Economic Approach For Electrification Of Rural And Shrimp Farming Regional Development Of An Isolated Island In Indonesia By Utilizing Hybrid Renewable Energy Systems, Fiqih Akbar Wijaya, Mohammad Akita Indianto

Journal of Materials Exploration and Findings

One of the challenges in developing and archipelagic countries such as Indonesia is maintaining energy demand in rural and isolated areas due to difficulties in electrical distribution. For instance, in areas like Bawean Island, no additional electricity capacity has been introduced in the past year, leading to an unmet potential customer demand. One of the possible options is by utilizing Hybrid Renewable Energy Systems (HRES) that are integrated with existing fossil fuel-based energy systems to support the growing energy demand in the remote island. A case study in Bawean Island is conducted with the projected energy demand covers the energy …

Remaining Life Assessment And Fitness For Service Evaluation Of Aging Chemical Reactors In Polyethylene Terephthalate Resin Industry, Aditya Pahlawan Munthe, Donanta Dhaneswara, Wahyuaji Narottama Putra, Gama Widyaputra

Journal of Materials Exploration and Findings

Aging chemical reactors in the polyethylene terephthalate (PET) resin industry require comprehensive evaluation to ensure safe continued operation. This study conducts a remaining life assessment (RLA) and fitness-for-service (FFS) evaluation on five 30-year-old reactors, based on API 510, API 579/ASME FFS-1, and ASME BPVC Section VIII Div. 1 standards. The analysis involves corrosion rate measurement, future corrosion allowance (FCA) projection, and minimum thickness verification. Among the reactors, R-120 was found to have the shortest remaining life less than 15 years. FFS assessments using three criteria Average Measured Thickness, MAWP from Point Thickness Readings, and Minimum Measured Thickness confirm that R-120 …

Analysis Of Leak Testing Planning For Carbon Dioxide Piping Systems In The Development Of Carbon Capture, Utilization, And Storage Facilities In The Bintuni Basin, Devi Sentiani, Akhmad Herman Yuwono Professor

Journal of Materials Exploration and Findings

Carbon Capture, Utilization, and Storage (CCUS) technologies have become a key strategic response to global efforts to reduce CO₂ emissions. This study presents a leak testing strategy designed for a carbon dioxide (CO₂) piping system as part of a Carbon Capture, Utilization, and Storage (CCUS) project in the Bintuni Basin, West Papua, Indonesia. This study aims to ensure the system is properly prepared before commissioning by designing a leak test plan that is both practical and technical, based on ASME B31.3, ASME PCC-2, and API STD 520 Part 1. We conducted the process, which involves identifying the system boundaries, …

Machine Learning And Clinical Eeg Data For Multiple Sclerosis: A Systematic Review, Badr Mouazen, Ahmed Bendaouia, El Hassan Abdelwahed, Giovanni De Marco

Manufacturing & Industrial Engineering Faculty Publications

Multiple Sclerosis (MS) is a chronic neuroinflammatory disease of the Central Nervous System (CNS) in which the body’s immune system attacks and destroys the myelin sheath that protects nerve fibers, leading to a wide range of debilitating symptoms and causing disruption of axonal signal transmission. Accurate prediction, diagnosis, monitoring and treatment (PDMT) of MS are essential to improve patient outcomes. Recent advances in neuroimaging technologies, particularly electroencephalography (EEG), combined with machine learning (ML) techniques — including Deep Learning (DL) models — offer promising avenues for enhancing MS management. This systematic review synthesizes existing research on the application of ML and …

A Machine Learning Approach To Detect Pores In Laser Powder Bed Fusion Additive Manufacturing, Jose Galarza, Jose Barron Jr., Luis Jimenez, Tamer Oraby, Jianzhi Li, Farid Ahmed

Manufacturing & Industrial Engineering Faculty Publications

Real-time detection of pores in the Laser Powder Bed Fusion (LPBF) metal Additive Manufacturing (AM) process is proposed in this study and can be utilized for in-situ process monitoring and quality control. The average light emission data from the process captured by an optical tomography camera can be integrated into a defect detection module to characterize defects after the deposition of a layer. The light emission contains information on the process zone which could be extracted with the appropriate data techniques. In this paper, we proposed a machine-learning approach that utilizes the mean light intensity data from the melt-pool monitoring …

Human Comfort Modeling, Measurement, And Improvement In Human–Robot Collaboration, Yuchen Yan

All Dissertations

A dissertation is proposed to explore human comfort in human-robot collaboration (HRC) through modeling, prediction, and enhancement methodologies. Human comfort is a crucial yet underexplored factor in HRC, directly influencing task efficiency, trust, and overall collaboration effectiveness. Understanding the influential factors, developing computational models, and refining methods to improve human comfort in HRC are essential steps toward advancing the field of collaborative robotics. To address these challenges, multiple studies have been conducted. A series of experimental studies were performed to investigate how robot motion-based parameters affect human comfort in HRC. These studies examined both analytical comfort modeling approaches and physiological …