Communities in PRCR
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- Colecciones de la Albizu University
- Colecciones digitales de Atenas College
- Colecciones de los Centros Sor Isolina Ferré
- Materiales utilizados para la certificación.
Recent Submissions
Evaluation of a Weight Measurement System in a Manufacturing Process Using Gage R&R Analysis
(Polytechnic University of Puerto Rico, 2026) Rodríguez Reynoso, Oasis; Morales Morales, José Alberto
Measurement systems play a role in manufacturing environments because process decisions depend on accurate and reliable data. This study evaluates the performance of a digital weighing system through a Measurement System Analysis using a Gage Repeatability and Reproducibility approach. The objective was to determine whether the system can produce consistent and reproducible measurements suitable for quality related decision making. The study involved ten parts, three operators, and three repeated measurements per part, a total of ninety observations. Statistical analysis was performed using the Analysis of Variance method to quantify repeatability, reproducibility, and total measurement variation. Results showed a total Gage R&R value of 3.97 percent, indicating that the system meets industry acceptance criteria. Variation was attributed to part-to-part differences, while the Number of Distinct Categories confirmed discrimination capability. These findings demonstrate that the measurement system is stable, reliable, and appropriate for manufacturing process control and quality assurance applications.
Forecasting-Based Production Planning System to Improve PPLH Performance in Extrusion Manufacturing Using Power BI
(Polytechnic University of Puerto Rico, 2026) Montoya Villalta, Pedro; Morales Morales, José Alberto
This study focuses on improving labor productivity control in an extrusion manufacturing environment by addressing inefficiencies in aligning production volume with operational hours. The objective of this research is to develop a forecasting-based production planning system that improves Pounds Per Labor Hour (PPLH) performance. The methodology includes analysis of historical production data and development of a data-driven model using Power BI. Results indicate that aligning labor scheduling with production demand improves utilization and stabilizes productivity. The findings demonstrate that data-driven planning enhances operational efficiency.
Process Improvement for Enterprise OT Asset Intelligence & Lifecycle Management
(Polytechnic University of Puerto Rico, 2026) Guzmán Huertas, Stephanie; González Miranda, Carlos J.
This design project aims to improve the Operational Technology (OT) asset management process by implementing a centralized infrastructure for managing and monitoring industrial automation assets across manufacturing facilities. The initiative focuses on optimizing OT asset inventory and lifecycle management processes to reduce inefficiencies, improve data accuracy, strengthen cybersecurity risk management, and drive standardization across the enterprise. The improvement initiative was conducted following the DMAIC (Define, Measure, Analyze, Improve, Control) methodology, ensuring a systematic and data-driven approach. Currently, OT asset inventory is maintained through offline lists that require manual updates whenever systems are upgraded or newly introduced to the manufacturing sites. This approach often leads to data inaccuracies, limited visibility, and delayed updates. By implementing a centralized system with automated network discovery, asset information will be continuously updated and validated in real time. This ensures greater data accuracy, improved lifecycle management, and enables faster, more effective responses to identified vulnerabilities, helping improve system reliability and overall cybersecurity.
Characterization of Alginate Hydrogels with Air-Plasma Surface Treatment
(Polytechnic University of Puerto Rico, 2026) Crespo, Abdel; Rondón Contreras, Jairo J.
Traditional wound dressings, such as gauze, present several limitations, including poor moisture retention, frequent replacement, and prolonged healing times, which may increase healthcare costs and nursing workload. This study focuses on the development of an alginate-based hydrogel dressing crosslinked with calcium chloride and plasticized with glycerol to enhance flexibility and hydration properties. Additionally, the hydrogel is modified through air plasma treatment under controlled conditions to alter surface characteristics such as hydrophilicity and porosity. Characterization techniques, including Fourier Transform Infrared (FT-IR) spectroscopy, optical microscopy, impedance analysis, and sol–gel fraction evaluation, were employed to assess structural and functional changes before and after plasma exposure. The results indicate that plasma treatment induces surface-level chemical modifications and changes in interaction properties. These findings suggest that plasma-treated alginate hydrogels may have relevance for biomedical wound dressing applications, while further studies are required to fully validate their clinical performance. Keywords ⎯ Alginate, Characterization, Hydrogels, Plasma Treatment.
Improving Early Diagnosis of Amyotrophic Lateral Sclerosis: A Multimodal Literature Review
(Polytechnic University of Puerto Rico, 2026) Ruiz Ríos, Dail Naded; Nieves Castro, Rafael A.
Amyotrophic lateral sclerosis (ALS) is a rare, progressive neurodegenerative disorder characterized by the degeneration of upper and lower motor neurons. Due to the clinical heterogeneity of the disease, early diagnosis remains a critical challenge. This study presents a systematic literature review aimed at identifying diagnostic methods that facilitate early ALS detection. Relevant peer-reviewed studies published between 2020 and 2026 were analyzed using a thematic approach, focusing on clinical evaluation, neuroimaging, electrophysiological techniques, biomarker-based methods, and emerging artificial intelligence applications. Findings indicate that while electromyography and neuroimaging are currently the most widely used diagnostic methods, the integration of biomarker research and AI-assisted decision-making holds promise for improving early detection. The review highlights existing gaps in diagnostic sensitivity and accessibility, emphasizing the need for multimodal approaches to reduce diagnostic delays. These insights aim to guide clinicians, researchers, and healthcare professionals in implementing strategies that improve early identification of ALS and patient outcomes. Keywords ⎯ Amyotrophic Lateral Sclerosis, Diagnosis, Neurodegenerative Disorder, Neuroimaging.