Journal of Mechanical Engineering - JMechE, Faculty of Mechanical Engineering, Universiti Teknologi MARA, Shah Alam (2025)

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Faculty Of Mechanical Engineering, Universiti Teknologi MARA

14/11/2025

📢 Featured Research from JMechE Vol. 22(3) | September 2025 Issue

🧤 AI-Powered Visual Detection System for Latex Glove Manufacturing 🤖

A team from Universiti Tenaga Nasional presents an intelligent Latex Mark Visual Detection System that combines deep learning and mechanical design to enhance glove defect inspection accuracy.

Using the YOLO v5 model, the system detects latex mark defects with 99.3% accuracy, significantly reducing false detections and inspection time. The integration of SolidWorks mode shape analysis further optimizes vibration stability and structural performance.

Highlights:

✅ AI-based visual detection achieves real-time precision
✅ Validation under AQL 2.5 standard (315 sample inspections)
✅ Demonstrates the synergy between AI algorithms and mechanical design innovation

📄 Read full article:https://ir.uitm.edu.my/id/eprint/122917/1/122917.pdf

07/11/2025

📢 Featured Research from JMechE Vol. 22(3) | September 2025 Issue

🌞 Boosting Solar PVT Efficiency with Hybrid Nanofluids ☀️

This study explores the use of Al₂O₃–SiO₂ hybrid nanofluids to enhance the thermal and electrical performance of solar photovoltaic-thermal (PVT) systems using CFD simulation.

🔍 Key Findings:

✅ Three hybrid ratios tested: 10:90, 30:70, and 50:50 (Al₂O₃:SiO₂)
✅ 10:90 ratio achieved the best overall performance
✅ Thermal efficiency increased by 4.75%, electrical efficiency by 1.42% compared to water
✅ Improved cooling leads to higher energy output and better temperature stability

This study demonstrates that hybrid nanofluids are a promising solution for sustainable solar energy systems, offering better heat transfer and improved panel efficiency.

📖 Full article:https://ir.uitm.edu.my/id/eprint/122916/1/122916.pdf

31/10/2025

📢 Featured Research from JMechE Vol. 22(3) | September 2025 Issue

🧪 Simulation-Based Evaluation of Ozonated Mist for Medical Disinfection

This study used Computational Fluid Dynamics (CFD) to analyze the dispersion and decay of ozone mist inside an ambulance environment. The research provides critical insights into optimizing ozone-based sanitization for emergency transport vehicles.

🔍 Key Highlights:

✅Transient CFD simulation tracks ozone mist buildup and dissipation over 300 seconds
✅ Ozone concentration peaked at 217 ppm within 60 seconds before gradual decline
✅ Results reveal how leakage and air exchange impact retention and decay
✅ Findings align with OSHA safety limits and real-world disinfection standards

This research provides a foundation for developing safer and more effective ozone disinfection systems for mobile healthcare environments.

📖 Full article:https://ir.uitm.edu.my/id/eprint/122919/1/122919.pdf

24/10/2025

📢 Featured Research from JMechE Vol. 22(3) | September 2025 Issue

🧩 Enhancing Jute/Epoxy Composites with Silane Modification 🌿

This study explores how varying silane coupling agent concentrations in the hardener affect the mechanical performance and moisture absorption of woven jute/epoxy composites.

🔍 Key Findings:

✅ Increased silane concentration lowers diffusion coefficient but raises moisture absorption
✅ Flexural strength decreased up to 39% due to weak interfacial bonding
✅ Fracture toughness improved by 52% at 1.5 wt.% silane modification
✅ Provides critical insight into the trade-off between strength and ductility in bio-composites

This research offers valuable knowledge for optimizing surface chemistry in natural fibre composites to improve their structural reliability and sustainability.

📖 Read the full article:
https://ir.uitm.edu.my/id/eprint/122920/1/122920.pdf

16/10/2025

📢 Featured Research from JMechE Vol. 22(3) | September 2025 Issue

🎧 Optimizing Magnetorheological Elastomers for Better Sound Absorption 🎵

This research developed an optimized magnetorheological elastomer (MRE) composition to enhance sound absorption and vibration damping performance.

🔍 Key Highlights:

✅ Optimal composition: 15 g carbonyl iron particles, 9 g RTV silicone rubber, and 0.45 g hardener
✅ Smallest ferrous particles (0.005 mm) provided the best noise absorption capability (33.07 dB)
✅ Improved uniformity and magnetic responsiveness within the elastomer matrix
✅ Suitable for use in vibration isolators, noise control devices, and adaptive damping systems

This research demonstrates how optimizing MRE microstructure enhances sound absorption, offering a new approach to acoustic and vibration engineering.

📖 Full article:https://ir.uitm.edu.my/id/eprint/122910/1/122910.pdf

10/10/2025

📢 Featured Research from JMechE Vol. 22(3) | September 2025 Issue

🔧 Reducing Warranty Costs Through Smarter Product Design 🚘

This new paper presents a comprehensive approach to improving product design quality and minimizing warranty costs in the automotive aftermarket for OEM customers.

🔍 Key Highlights:

✅ Three-phase methodology integrating warranty data analysis, diagnostic studies, and component-level repairs
✅ Focused on alternator component repair, achieving 73% reduction in warranty claims
✅ Delivered RM68,000 cost savings through improved repair strategies
✅ Strengthens product reliability, customer trust, and sustainability in the automotive supply chain

This research offers a strategic framework for OEMs and suppliers to enhance product quality and operational efficiency through data-driven warranty analysis and targeted component redesign.

📖 Read the full article:
https://ir.uitm.edu.my/id/eprint/122907/1/122907.pdf

06/10/2025

📢 [NEW ISSUE RELEASE] – Volume 22 Issue 3 (September 2025)

The Journal of Mechanical Engineering (JMechE) is pleased to announce the release of its September 2025 Issue (Vol. 22, No. 3) — now available online!

This issue features a diverse range of research across mechanical, materials, thermal, manufacturing, and energy engineering, including studies on:

⚙️ Product design optimization
🔩 CNC machining and surface roughness
💨 Aerodynamic modelling
🔥 Nanofluids and heat transfer
🌞 Solar energy systems
🌍 Sustainable materials and manufacturing

Discover fresh insights and pioneering research shaping the future of mechanical engineering, contributed by experts from across the globe! 🌍✨

📖 Read the full issue here:
👉 https://jmeche.uitm.edu.my/browse-journals/regular-issue/regular-issue-2025-vol-22-3/

01/10/2025

📌 This is the final article highlight from JMechE May Issue - Vol. 22(2). Stay tuned for our upcoming September Issue - Vol. 22(3) where we’ll continue sharing the latest research in mechanical engineering. 🚀

🌀 Optimizing Fluid Flow in Triply Periodic Minimal Surface (TPMS) Lattice Structures for Carbon Capture

This paper explores the Split P lattice TPMS design and its effect on fluid flow distribution and pressure drop under laminar flow conditions.

🔍 Key Insights:

✅ Split P lattice boosts surface area by 35%, improving sorbent contact
✅ Higher wall thickness increases pressure drops and localized velocity peaks
✅ 0.8 mm design achieves the best trade-off between permeability and uniform flow
✅ Application: Direct Air Capture reactors for CO₂ mitigation

This research identifies the Split P lattice as a superior structured packing for Direct Air Capture (DAC) systems, advancing the efficiency of CO₂ adsorption technologies.

📖 Full article:https://ir.uitm.edu.my/id/eprint/116655/1/116655.pdf

19/09/2025

🔥 Boosting Heat Transfer with Ternary Nanofluids (TNF)

This work investigates how a ternary nanofluid (TiO₂–Al₂O₃–SiO₂ in water) improves heat transmission in mixed convection flow with convective boundary conditions.

🔍 Key Insights:

✅ TNF achieved better thermal conductivity than hybrid nanofluids
✅ Increasing Biot number (Bi) enhanced temperature distribution but lowered velocity
✅ Higher λ (mixed convection parameter) increased temperature fields
✅ Results verified with strong agreement against existing models

The findings highlight TNF as a promising coolant for applications in automotive engines, solar collectors, and electronic cooling.

📖 Full article:https://ir.uitm.edu.my/id/eprint/116652/1/116652.pdf

11/09/2025

⚡ Cleaner Engines with Electric Turbocompounding ⚡

This study explores the use of electric turbocompounding (ETC) in a 1.6L CamPro turbocharged engine to reduce greenhouse gas emissions and recover exhaust energy.

🔍 Key Insights:

✅ Dual-stage electric turbocompounding (ETC) lowers brake-specific emissions across NOx, CO₂, CO, and HC
✅ Maximum reductions: 28.8% NOx, 6.9% CO₂, 7.2% CO, 9.9% HC
✅ Best performance seen in mid-range engine speeds (3000–5000 rpm)
✅ Confirms electric turbocompounding (ETC) as a practical short- to mid-term solution for global greenhouse gas (GHG) reduction

This research highlights electric turbocompounding (ETC) as a promising waste heat recovery strategy, paving the way for greener and more fuel-efficient vehicles.

📖 Full article:https://ir.uitm.edu.my/id/eprint/116653/1/116653.pdf

04/09/2025

🚘 Optimizing Sedan Front-End Design for Better Aerodynamics 🌬️

This research uses central composite design (CCD) and mathematical modelling to assess how different vehicle front-end profiles influence aerodynamic drag coefficient (Cd).

🔍 Key Insights:

✅Windshield angle and hood edge height strongly affect aerodynamic efficiency
✅Hood length and bumper centre height also influence drag reduction
✅Response surfaces guide design for fuel economy and stability

The findings provide automakers with predictive tools to refine front-end geometry, enabling vehicles with improved aerodynamic efficiency and lower fuel consumption.

📖 Full article:https://ir.uitm.edu.my/id/eprint/116654/1/116654.pdf

29/08/2025

⚙️ Smarter CNC Machining with Artificial Neural Networks 🤖

This study applies Artificial Neural Networks (ANNs) to optimize CNC machining parameters, addressing one of the core challenges of modern manufacturing: consistent surface finish quality.

📌 Highlights:

✅ANN model predicts surface roughness from machining inputs (cutting speed, feed rate, depth of cut)
✅Achieved correlation coefficient R = 0.992 and NRMSE = 3.79%
✅Significantly reduces reliance on costly experimental trials
✅Demonstrates ANN as a robust, accurate tool for intelligent manufacturing

The research proves that ANN models can serve as a powerful tool in Industry 4.0 manufacturing, ensuring better surface quality and productivity.

📖 Full article:https://jmeche.uitm.edu.my/wp-content/uploads/2025/05/2.JMECHE-2024-OJS-4981.pdf

Journal of Mechanical Engineering - JMechE

14/11/2025

07/11/2025

31/10/2025

24/10/2025

16/10/2025

10/10/2025

06/10/2025

01/10/2025

19/09/2025

11/09/2025

04/09/2025

29/08/2025

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