Operations Research, Systems Engineering and Industrial Engineering Commons^™

A Review Of Energy Storage Technologies With Hydro Energy System Design For Off-Grid Electricity, Daniel H. Ngoma, Banet L. Masenga

Tanzania Journal of Engineering and Technology (TJET)

Many renewable energy sources such hydropower—particularly small-scale run-of-river and micro-hydro—offers reliable, low-cost generation. However, their inherent intermittency (due to seasonal flow variations) and inability to instantly match demand necessitate integrated energy storage to ensure a stable, continuous power supply. This review synthesizes contemporary energy storage technologies in the context of their integration with off-grid hydro energy system design.

The study examine a spectrum of storage solutions, evaluating their technical characteristics, costs, and suitability for hybrid hydro applications. Pumped Hydro Storage (PHS), while highly efficient and large-scale, is often geographically constrained and capital-intensive for small off-grid projects. Battery Energy Storage Systems …

Analysis And Study Of Telemetry Systems For Directional And Horizontal Well Drilling, Jahongir Abdiganiyev Erkin Ugli, Sherali Halloqovich Umedov

Technical science and innovation

The article discusses the issues of reducing non-productive drilling time during the construction of directional and horizontal wells. The main focus is on the analysis of drilling conditions in complex geological and high-temperature environments. Particular attention is paid to drilling conditions in the territory of the Republic of Uzbekistan, with a specific study of data from the Boysun and Ustyurt regions. An analysis and study of the performance of telemetry systems available on the market, as well as their main technical characteristics, have been conducted. Key factors affecting the accuracy of wellbore trajectory measurements under various geological and technical conditions …

Security Risks Of Ai-Generated Code In Software Development, Maame Agyekum

Cybersecurity Undergraduate Research Showcase

Artificial Intelligence(AI) has recently forced change globally, public Institutions and as well as national security. Advancement in machine learning, mixed datasets have enabled significantly powerful systems while being capable of operating at a large scale. As innovation and technological advancement increases at rapid pace, issues like a regulation gap where scientific development far exceeds the government’s ability to regulate and establish an effective oversight. As a result, Artificial Intelligence has been controlled by private companies, leading to an industry where speed and profit often outweigh safety and ethical responsibility.

Threat-Analysis Oriented Digital Twinning Of Ml-Powered Future Autonomous Weapon Systems, Thomas Neubert

Doctoral Dissertations and Master's Theses

Warfare is undergoing a rapid transformation with the integration of artificial intelligence (AI) and machine learning (ML) into autonomous weapon systems (AWS) for perception, decision support, and control. As these systems become more software-defined, their cyber attack surface expands across sensing, communications, autonomy logic, and human-machine interfaces. As human oversight diminishes, ensuring the cybersecurity, resilience, and reliability of these systems becomes critical to mission success. This thesis investigates how a digital twin-driven threat modeling framework that integrates system-centric analysis with adversary-informed methodologies can support structured cybersecurity vulnerability evaluation and defensive strategy development associated with ML-powered AWS. First, the study analyzes …

Challenges And Best Practices Of Regional Innovation Ecosystems, Mahnaz Asgari Sooran

Miners Solving for Tomorrow Research Conference

Many places around the world are developing regional innovation ecosystems to spur regional economic. Many innovation ecosystems fail or barely maintain their initial momentum after a few years. In this paper, we identified challenges and best practices facing innovation ecosystems interviews with the innovation ecosystem stakeholders. We employed the MIT REAP (Regional Entrepreneurship Acceleration Program) model to categorize the five main stakeholders of the innovation ecosystem: entrepreneurs, universities, industry, risk capital, and government. Our initial results indicated the following: (a) Access to capital and talented workforce; (b) Stakeholder discovery process is one of the critical areas to understand the basic …

Preventive Maintenance Scheduling Using Artificial Intelligence And Decision Support Agent, Samiksha Aryal

Miners Solving for Tomorrow Research Conference

Preventive Maintenance models have traditionally relied on a time-based maintenance model, which uses fixed statistical distribution to represent the time-to-failure (TTF). The requirement of data-driven models and automated decision-making systems have become essential for modern manufacturing systems. The use of fixed statistical distribution limits the ability of existing models in producing solutions in real-time. Our model overcomes these limitations by implementing an empirical distribution to represent TTF. The empirical distribution is generated using a neural network which eliminates noise from the raw maintenance log. Renewal Reward Theorem (RRT) is implemented to efficiently provide maintenance threshold in real time. The use …

Empirical Evaluation Of Policy-Based Reinforcement Learning For Dynamic Service Control In An M/M/1 Queue, Joseph Walton

Miners Solving for Tomorrow Research Conference

While reinforcement learning has been increasingly applied to stochastic control, limited work examines policy-based methods in queuing environments modeled as semi-Markov decision processes (SMDP). This study investigates how policy-based reinforcement learning (RL) algorithms perform when applied to service rate control in an M/M/1 queue, a common queuing model for manufacturing and service systems. The problem is formulated as an SMDP in which decisions occur at each new service, allowing an agent to select different service rates from a finite set of speeds, aiming to minimize an objective function that manages system congestion and energy costs. Three policy-based reinforcement learning algorithms, …

A Speed-Adjusted Centipawn Metric For Chess Cheating Detection, Benjamin Sullins, Benjamin Biehl

Miners Solving for Tomorrow Research Conference

The proliferation of chess engines has compromised the integrity of online play through both manual assistance and automated bots. This research proposes Si, a novel metric designed to quantify unnatural play by integrating move latency, the relative strength of the selected move, and the density of high-quality alternatives available in a given position. By fitting Si  values to theoretical probability distributions across specific Elo ratings and time controls, we establish a statistical baseline for human performance. Discrepancies between an individual's Si  profile and these established distributions provide a robust framework for identifying artificially inflated play, offering a potential method for …

Ai Adoption Tensions For Organ Procurement Organizations, Joely Grace Hall

Miners Solving for Tomorrow Research Conference

Artificial intelligence (AI) has the potential to improve efficiency in healthcare, yet its adoption remains limited, with only 22% of healthcare organizations having implemented domain-specific AI tools. Adoption may be especially complex in specialized domains such as organ transplantation, where ethical, legal, and operational challenges are dominant. This study examined factors influencing AI acceptance within Organ Procurement Organizations (OPOs), focusing on technological, organizational, and environmental contexts.

Semi-structured interviews with 16 OPO executives from 10 OPOs revealed key tensions shaping AI adoption. We identified five tensions that are holding back OPO leaders from AI adoption, (1) misconceptions, (2) training approach, (3) …

Insect Inspired Behavioral Strategies For Improving Multi-Agent System Resilience In The Presence Of Contagious Faults, James E. Hand

Doctoral Dissertations and Master's Theses

As Multi-Agent Systems (MASs) become increasingly involved in every aspect of everyday life the need to maintain reliability and resilience within these systems grows. However, in equal measure bad actors wishing to maliciously control or alter these systems are growing in both scale and capability. Thus, there is a present need for control schemes and agent behaviors that provide security against these threats while also avoiding large degradation in system performance as a tradeoff. Current research has covered a wide breadth of avenues and strategies that provide measurable resilience to faulted agents. However, these strategies often require group consensus, specialized …

Evaluating Uav Visual-Inertial Odometry Trajectory Error And Feature-Level Metrics Over Repetitive Floor Patterns, Anass El Mekkoussi

Doctoral Dissertations and Master's Theses

Visual-Inertial Odometry (VIO) is a widely used state estimation technique for Uncrewed Aerial Vehicle (UAV) navigation in environments where Global Navigation Satellite System (GNSS) signals are unavailable. VIO systems that rely on visual feature tracking are susceptible to performance degradation when operating over surfaces containing repetitive visual textures, where visually similar features can produce ambiguous correspondences that introduce errors into the trajectory estimate. Despite the prevalence of repetitive textures in indoor UAV operating environments such as warehouses, manufacturing facilities, and infrastructure corridors, the specific impact of different repetitive pattern geometries on per-surface VIO accuracy has received limited systematic study, and …

Artificial Intelligence In Human Spaceflight Safety-Critical Systems: A Requirements Framework For Ai-Enabled Computer-Based Control Systems, Liz Bosch

Doctoral Dissertations and Master's Theses

Currently, there is no governing standard that addresses the safe integration of AI into computer-based control systems (CBCS) in human spaceflight. The computer-based control expectations of those safety-critical systems on the International Space Station (ISS) are captured in SSP 50038, Computer-Based Control System Safety Requirements, with one caveat: the standard was not designed with AI applications in mind. SSP 50038 does not cover the probabilistic behavior, opacity, and training-data dependency of modern AI/ML systems. The objectives of this work is to develop an AI taxonomy relevant to safety characteristics (determinism, transparency, data dependency, failure predictability), systematically map AI characteristics against …

Visual Pattern Mining With Similarity Metrics For Model-Free Trading In The Korean Futures Market, Juhyeon Jang, Jaeyun Kim, David Enke

Engineering Management and Systems Engineering Faculty Research & Creative Works

The fractal market hypothesis highlights multi-scale dynamics in financial time series and provides a theoretical foundation for pattern-based analysis. This study proposes a model-free visual pattern mining framework that transforms high-frequency market data into image representations to support intelligent decision-making. By converting 1-minute KOSPI200 futures data into candlestick chart and Bollinger band images, the method effectively captures structural patterns and volatility dynamics. The framework applies similarity metrics and Intersection over Union (IoU)-based visual comparison to identify historically similar patterns and generate intelligent trading signals without model training or complex parameter tuning. Experimental results demonstrate that combining visual features of candlestick …

Demonstrating Sysml V2’S Utility With Syside And Syson For Systems Modeling, Quinn Galen

Student Research Symposium (SRS)

This study highlights the practical utility of SysML v2’s kernel language, a formal, text based foundation for consistent, cross tool model definitions, in Model Based Systems Engineering (MBSE), using Air Traffic Management (ATM) as an illustrative example. SysIDE, an open source textual editor, enables rapid model creation with the kernel’s concise syntax, allowing users to define system components and behaviors (e.g., ATM radar or flight path interactions) with real time validation. SysON, a web based graphical tool, complements this by facilitating collaborative visualization of system architectures. Using ATM as an example case, we can showcase how the kernel language enhances …

Ai-Scm Cmm: A Capability Maturity Model For Artificial Intelligence Integration In Supply Chain Management, Lordt Becklines, Omar F. El-Gayar, Patti Brooks, Insu Park

Annual Research Symposium

Artificial intelligence is increasingly deployed in supply chain management, yet many organizations struggle to align adoption efforts with process readiness, data quality, governance, and workforce capabilities, and they still lack validated supply chain specific roadmap for assessing readiness, sequencing investments, and reducing implementation risk. This study develops and evaluates a Capability Maturity Model for Artificial Intelligence Integration in Supply Chain Management to address that gap. Using a design science research approach, the study synthesizes prior literature and practitioner knowledge to define maturity dimensions, capability indicators, and staged progression levels for AI integration in supply chain contexts. The artifact and assessment …

A Causal Inference Methodology For Root-Cause Diagnosis In Nonstationary Industrial Time Series, Cansu Yalim

Knowledge and Creativity Expo

Industrial fault diagnosis lacks a procedure that learns time-varying causal structure from observational time series, makes identifiability limits explicit, and uses intervention-based reasoning to support root-cause assessment under industrial constraints. Although predictive maintenance can reduce downtime, diagnosis is often expert-rule-based or association-driven; pipelines may elevate downstream symptoms alongside true drivers and provide limited guidance on which feasible action would change a fault trajectory under current operating conditions. Because operating phases and fault progression create regime shifts, industrial systems rarely follow a single stable mechanism. This study develops and evaluates a three-stage, regime-aware causal diagnostic protocol based on a time-varying Dynamic …

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 …

Analogy2kg: An Automatic Pipeline For Deriving Knowledge Graphs From Long-Text Analogies, Kara Combs, Lance E. Champagne, Bruce A. Cox, Christine M. Schubert Kabban, Trevor Bihl, Grace Lemming

Faculty Publications

Analogical reasoning is an increasingly popular, lightweight solution to enable large language model (LLM)-level reasoning without computational complexity. Still, it has yet to be adopted due to its reliance on strictly hand-formatted data. Therefore, we propose Analogy2KG (“Analogy to Knowledge Graph”), as an automatic pipeline that transforms text into a KG format via a fine-tuned version of information extraction (IE) algorithms for long-text analogies. The need to verify that the complex underlying analogical structure of the data is maintained was done via paired samples tests in the creation and validation of this pipeline. Graph density was used to evaluate the …

Optimizing Warranty Policies For Remanufactured Products: When Should They Be Longer, Shorter, Or Identical To New Product Warranties?, Kunpeng Li, Jun-Yeon Lee

Faculty Publications

Manufacturers adopt different warranty strategies for remanufactured products, offering shorter, identical, or longer warranty periods compared to new products. However, prior research has only focused on manufacturers offering either shorter or identical warranties. In addition, the existing literature has not captured the diminishing returns of warranties, i.e., as the warranty coverage increases, its incremental benefits begin to decrease but the costs continue to increase. To address these gaps, we develop an optimization model that jointly considers pricing and warranty decisions while accounting for warranty’s diminishing effect on consumer’s willingness to pay for remanufactured products. We show that all three observed …

Multi-Objective Optimization Of Waste Incineration For Minimal Carbon Monoxide And Sulfur Dioxide Emission And Rate Maximization: A Case Study Of Mbezi, Mkuranga-Pwani, Tanzania, Grangay M. Nyanghura, Enock W. Nshama

Tanzania Journal of Science

Incineration is widely employed for hazardous waste disposal, but results in harmful flue gas emissions. This study optimizes a double-chamber incineration process to reduce sulfur dioxide (SO2) and carbon monoxide (CO) emissions while maximizing the incineration rate. The effects of waste mass, primary chamber temperature (PT), and secondary chamber temperature (ST) were analyzed using a full factorial design of 27 experiments. ANOVA revealed that mass had the greatest impact on emissions and incineration time, ST had a moderate effect, and PT had little influence. Regression analysis provided models for incineration time, CO, and SO2 emissions. Single-objective optimization using sequential quadratic …