Engineering Reports

We introduce the entropy-transformed inverse Weibull distribution (ETIWL), a novel model that enhances data modeling capabilities. Through extensive simulations and real dataset applications, ETIWL demonstrates superior performance compared with benchmark distributions, offering improved reliability in survival analysis and other critical areas.

Flow chart highlighting the service mechanism of MRP with impatience and working breakdown of the server.

This study explores the integration of digitalization and lean production to enhance Overall Equipment Effectiveness (OEE) in the apparel industry. Findings indicate that targeted interventions, including process monitoring devices and digital line balancing, can increase OEE from 40% to 60% to a sustainable 75%, improving efficiency, reducing downtime, and optimizing production performance.

Approach for reduced cooling loads and kg eq-CO₂ emissions.

The thermal performance of flat plate collectors (FPCs) was enhanced using nanofluids. A hybrid MWCNT/Fe₃O₄/water nanofluid achieved 71.9% thermal efficiency, outperforming conventional fluids. Improved Nusselt number, friction factor, and convective heat transfer highlight its effectiveness in optimizing FPC systems.

This study presents an AI-driven MPPT strategy integrating an artificial neural network and nonlinear backstepping control for grid-connected PV systems. The proposed method ensures optimal energy harvesting and seamless grid synchronization, achieving superior performance with a remarkable THD reduction to 0.2148, significantly enhancing PV system efficiency under fluctuating environmental conditions.

This study presents reliability assessments and load flow computations for the electricity grid in Rwanda at the distribution level on Gatumba and Ntongwe feeders by integrating the PV system and BESS. The power characteristics were established by utilizing the PV*SOL simulation, and quasi-dynamic and reliability simulations are conducted in DigSILENT PowerFactory.

The HPLIRF model reveals fungal disease dynamics in onion crops, identifying spore deposition and infection rates as key drivers. Optimal control combining fungicide and plant removal minimizes disease spread cost-effectively, enhancing crop resilience.

An optimized energy management system using Particle Swarm Optimization significantly improves cost-efficiency and battery stability in grid-connected PV-BESS smart grids. The proposed method outperforms linear programming and demonstrates robust performance under variable weather conditions, supporting reliable renewable integration and demand response strategies in smart energy systems.

Modeling Lymphatic Filariasis by incorporating disease awareness through fractional derivative operators.

TUK and Nomex-910 papers were impregnated with monoester of palm kernel oil and aged at 130°C during 400 h. Nomex's AC BDV exceeded TUK. The reverse behavior was observed for acidity. An Arrhenius plot was applied to the viscosity of monoester. 2-FAL concentration and degree of polymerization were estimated from measured UV absorbance.

This research examines the heat and mass transfer rates in magnetohydrodynamic (MHD) tangent hyperbolic ternary hybrid nanofluid flow over a stretching plate, considering factors such as variable thermal conductivity, Joule heating, viscous dissipation, chemical reactions, Darcy–Forchheimer flow, Cattaneo–Christov heat and mass fluxes, and nonlinear thermal radiation, by using the RK6 method in MATLAB.

This study demonstrates the development of flexible, freestanding GaAs solar cells with a power conversion efficiency of 19.62%, achieved through optimized layer thickness and doping concentrations. Experimental characterization and numerical simulations reveal key mechanisms, including I–V characteristics and carrier recombination, underscoring the potential of GaAs solar cells for high-efficiency energy solutions in both terrestrial and space applications.

A deep eutectic solvent (DES) comprising menthol (MEN) as a hydrogen bond donor (HBD) and thymol (THY) as a hydrogen bond acceptor (HBA) is comprehensively investigated through COSMO-RS and molecular dynamics (MD) simulations. COSMO-RS is employed to predict the solid–liquid equilibrium, along with σ-profiles and σ-surfaces, to elucidate intermolecular interaction characteristics. Complementary MD simulations provide molecular-level insights into structural and dynamic behavior via mean square displacement (MSD), radial and angular distribution functions (RDFs/ADFs), spatial distribution functions (SDF), and vector reorientation dynamics. Together, these approaches offer a detailed understanding of the structural organization and interaction landscape of the MEN–THY DES.

Pulsed CO₂ laser causes uneven burr, while fiber laser is uniform. Compare fiber and CO₂ laser techniques for cutting AISI 316L.

This study proposes a hybrid machine learning approach combining active learning, Random Forest, and CatBoost to predict and optimize HVAC energy consumption in office buildings. It improves prediction accuracy with limited data, reduces outlier impact, and uses SHAP analysis for more effective energy-saving optimizations.

The Real-Climatic Microcontroller-in-the-Loop (RCMIL) Framework provides a novel, rapid, and cost-effective platform for verifying photovoltaic (PV) control systems under real-world climatic conditions. By integrating real climatic data with Microcontroller-in-the-Loop execution, this approach bridges the gap between simulations and practical deployment, enhancing the reliability and accessibility of MPPT controller validation.

This study explores Borassus husk fiber/epoxy composites treated with 5% NaOH, showing enhanced thermal stability, mechanical strength, and damping properties. The 0.75-h treated fiber achieved the highest thermal stability (IPDT: 525°C). Despite a slight drop in Tg, the composites outperformed other natural fiber counterparts. With improved energy dissipation and acceptable outgassing, these sustainable materials are promising for aerospace applications, supporting both performance and environmental goals.

This study optimizes the combustion characteristics of rice husk briquettes enriched with Croton megalocarpus oil, identifying key parameters for efficient burning. It contributes a predictive model enhancing briquette technology, significantly advancing sustainable biofuel applications with improved combustion efficiency and reduced emissions.