Industrial and Manufacturing Systems Engineering electronic theses and dissertations (MU)
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The items in this collection are the theses and dissertations written by students of the Department of Industrial and Manufacturing Systems Engineering. Some items may be viewed only by members of the University of Missouri System and/or University of Missouri-Columbia. Click on one of the browse buttons above for a complete listing of the works.
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Item Robust facility location selection frameworks for service systems(University of Missouri--Columbia, 2025) Golghamat Raad, Nima; Rajendran, Suchithra[EMBARGOED UNTIL 08/01/2026] This dissertation develops a unified robust optimization framework for strategic facility-location decisions in service logistics under uncertainty. Motivated by the growing need for infrastructure resilience against demand volatility, budget constraints, and environmental targets, this research integrates multi-criteria decision-making (MCDM) methodologies with stochastic, fuzzy, and regret-based optimization techniques across increasing levels of network complexity. Study 1 focuses on robust single-facility location under uncertainty, proposing a two-stage potential-assessment and siting approach for regional airports. The methodology combines a Robust Slack-Based Measure Data-Envelopment Analysis (SBM-RDEA) to assess existing facilities, regression modeling to identify influential factors, and GIS-based weighted overlays for suitability mapping. Applied to Sistan-and-Baluchestan Province, Iran, the model significantly narrows the candidate location area, pinpointing Zahedan County as optimal, outperforming conventional entropy--AHP methods. Building upon this approach, Study 2 expands the scope to multiple-facility network location under uncertainty, specifically addressing a closed-loop dry-port network. It employs a hybrid Fuzzy SWARA-COPRAS method to derive expert-validated weights for economic, environmental, infrastructural, and socio-political criteria. These weights guide a multi-stage fuzzy-stochastic chance-constrained program utilizing a novel robustness metric that balances expected benefit, worst-case profit, and bounded relative regret. An Iranian national case illustrates that establishing four strategically located inland terminals interconnected by rail substantially reduces costs, lowers COâ‚‚ emissions, and maintains profitability under significant demand fluctuations. Study 3 further advances the model by integrating routing considerations into multiple facility location decisions, focusing on depot and battery-swapping networks for delay-sensitive drone deliveries. The research formulates a lexicographic, regret-aware location--routing MILP that simultaneously maximizes on-time service reliability, extends spatial coverage, and minimizes capital investments amidst drone endurance uncertainties. Computational experiments using adaptive large-neighborhood search achieve near-optimal solutions for metropolitan-scale problems. A case in Dallas--Fort Worth demonstrates the practical benefits of optimized depot layouts in meeting critical service deadlines for medical deliveries at reduced infrastructure investment. Collectively, the dissertation reframes robustness as a comprehensive design principle, bridging strategic location planning with tactical network optimization and operational routing decisions. By coupling data-driven criteria weighting with robust and tractable optimization models, it provides actionable frameworks for planners in air transport, inland freight logistics, and drone delivery services. These tools enable informed decision-making, effectively balancing cost, resilience, and sustainability across diverse future scenarios.Item Design and evaluation of EV charging networks : a case study of the SF--LA corridor(University of Missouri--Columbia, 2025) El-Rjoob, Sora; Rajendran, Suchithra[EMBARGOED UNTIL 08/01/2026] The growing adoption of electric vehicles (EVs) presents both opportunities and challenges for transportation systems, particularly in high-volume corridors. Although EVs provide environmental and economic benefits, inadequate charging station capacity can lead to congestion, long waiting times, and grid strain. This study employs a simulation-based model to evaluate EV network performance along the San Francisco--Los Angeles corridor, utilizing real-world arrival rates, behavioral factors, and grid constraints. The model implements a non-stationary M(t)/M/c simulation approach in Python to estimate and compare waiting times, booth requirements, and related costs across several scenarios under demand uncertainty, driver behaviors, and grid constraints. The simulation results show how booth allocation and system performance metrics respond to arrival rates and behavioral variations. This provides a flexible framework, supporting decision-making for infrastructure planners and offers guidance on trade-offs between costs, sustainability, and service quality.Item Microelectronic assembly - capacity, supply and assurance(University of Missouri--Columbia, 2025) L. Kutney, James; Rajendran, Suchithra[EMBARGOED UNTIL 05/01/2026] This thesis uses a survey of literature method to lay the foundation for recommendations that minimize the probability of unintended supply disruptions, shortages, or sabotage of microelectronic assemblies. This paper describes manufacturing (microchip manufacturing, electronic design, wafer preparation, photolothography, material addition/removal/modification, chiplet assembly, packaging and testing) of a microelectronic assembly, including the semiconductor chip. This paper reviews the microassembly industry standards (via Appendix) according to general test method categories (functional, parametric, reliability, structural, burn-in and packaging) and by major standards organization (JEDEC, MIL-STD, IEC, IEEE, AEC and IPC) as well as specialty standards organizations involved in specialized methods and applications such as chiplets (UCIe) and defense procurement (DFARS). With the above background, the author introduces technical and non-technical market trends threatening assurance of microelectronics capacity and supply such as geopolitics, international and domestic tariff and subsidy policies, supplier concentration, dis-intermediation of integrated fabs, electronic design automation startups and advanced node (photolithography-limit-driven) technologies like 3D, FinFET and factory optimization tools. With a basis of understanding of the manufacturing processes, quality standards and market forces, the thesis introduces artificial intelligence, and machine learning (via Appendix) in the context of human-included, or human-in-the-loop decision processes focused on microelectronic assembly capacity, supply and assurance. The author then demonstrates the benefits of commercial large language models for the testing of queries on such critical items as: current standard coverage and gaps in technical standards for custom integrated circuits and 'comparison of performance parameters' for advanced testing equipment. The thesis then considers mixed human-in-the-loop and model-based exercises that have value for group supply chain problem solving using enhanced human-included artificial intelligence.Item Developing a gemba board deployment and assessment system in a multidisciplinary hospital setting(University of Missouri--Columbia, 2024) Tucker, John Alton; Noble, James S.The healthcare industry has struggled for decades to create and sustain a culture of high reliability, specifically within the continual process improvement realm. Implementing methods by which all staff in the healthcare system have an avenue to foster a culture of improvement is needed. One Lean tactic that aids in those efforts seen in other industries are the use of Gemba Boards. A literature review was conducted, and it was found that the use of Gemba Boards was primarily only in pockets of a healthcare organization, mostly nursing. A gap exists that this research aims to fill is establishing a framework that a hospital can undergo when no system of huddling for improvement exists that is standardized in every facet and department within the healthcare system. A framework was developed in two phases, to establish the initial deployment of Gemba Boards, followed by the progression to a sustained cyclical system and program for the Gemba Boards to be assessed for comprehension and return on investment for high reliability efforts. The framework established in this research was piloted in a study within a hospital system that had no formal huddling for improvement or Gemba Boards as a part of their culture. The integration of Boards into every department in the hospital was analyzed as a first attempt to examine how all facets of a healthcare system comprehend and execute the tool at the same time. The objective through statistical analysis is to advance the confidence in the industry that though uniquely different, with the use of the framework developed, deploying Gemba Boards and the philosophy behind them can produce results in any type of healthcare department and environment. Additionally, analysis will be conducted to gain insight into how the model functions when not just one area or pocket of the hospital is deploying this system of huddling, but the entire organization concurrently when pushed and supported by leadership.Item Power plant vibration monitoring using wavelet feature extraction and functional design of experiments(University of Missouri--Columbia, 2024) Oguejiofor, Benjamin Nwakile; Seo, KangwonIn a nuclear plant power generation, analysis of vibration signal constitutes an integral part of predictive maintenance for rotating equipment such as pumps, motors, turbine generators, etc. Vibration signals are continuously monitored via sensors and thresholds for alarms maybe set up to identify equipment malfunction. Improved methods for decomposition and analysis of power plant vibration signals using wavelet feature extraction and functional design of experiment (FDOE) have not been sufficiently investigated for applicability in analyzing these signals for better detection of equipment faults. Chapter 1 introduces the general concepts and methods to be applied in our research study. In Chapter 2, we present the application of discrete wavelet transform (DWT) to decompose a reactor coolant pump vibration signal into frequency sub-bands and the generation of a number of features from some statistics. A principal component analysis (PCA) is used to reduce the large set of variables into a few principal components which can be applied in future monitoring of normal vibration signals. From the insights gained using PCA, Chapter 3 studies the linear discriminant analysis (LDA) to simulated vibration signals, to distinguish between normal and abnormal signals. In Chapter 4, we apply the functional principal component analysis (FPCA) in characterizing the vibration signals generated under several different levels of an environmental factor, a flow rate, associated with a condensate pump. An FDOE is applied with the target vibration curve and used to obtain an optimal flow rate. The obtained flow rate was found comparable to the theoretical pump curve best efficiency point (BEP) and recommended for use for optimal pump performance and reliability. In Chapter 5, we perform an extensive review of literature on FDOE and its applications. A standard FDOE framework was shown and demonstrated the five basic steps to be applied when using JMP Pro 17. Chapter 6 provided overall conclusions and suggestions for future work.