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Trends in Machine Design

E-ISSN: 2455-3352 | Peer-Reviewed Journal (Refereed Journal) | Hybrid Open Access

About the Journal

Trends in Machine design

Trends in Machine design [2455-3352(e)] is a peer-reviewed hybrid open-access journal launched in 2014 focused on the rapid publication of fundamental research papers on all areas of Machine Design.

Focus & Scope

    • Kinematics of Machines: Kinematic analysis, mechanism simulation and animation, theory of machines, design engineering of mechanisms, history of mechanism and machine science.
    • CAD/CAM/CAE Technology: Integrated CAD-CAE technologies, virtual prototyping, rapid prototyping and manufacturing, concurrent engineering, technology integration, automated design systems.
    • Mechatronic Design: Integration of sensors, actuators, controllers, and mechanical components, servo controllers, fuzzy logic and intelligent control, control system synthesis under uncertainty, product data management, hybrid electric vehicle design and fuel economy.
    • Robotic Machine Design: Humanoid robot design, robot kinematics, pelvis mechanisms for bipedal robots, DC motor and brush design, infrared sensors in robotic machines.
    • Brakes, Clutches, Gears, and Springs: Brake design and failure analysis, emergency braking, regenerative braking in electric vehicles, heat cracks and thermal stress in brakes, coil spring design, clutch and gear design, energy-saving drive components.
    • Screws, Rivets, Pins, and Mechanical Fasteners: Mechanical fastener design, joining processes, ecodesign, life cycle assessment (LCA) of fastened assemblies, design for disassembly and aluminum recovery.
    • Fatigue and Failure Analysis: Local and global fatigue approaches, fatigue in metallic alloys, multistage fatigue, environment–microstructure interaction, oxidation, intergranular cracking, thermo-mechanical fatigue of superalloys.
    • Belts, Pulleys, Sheaves, and Flywheels: Belt and pulley drive design, sheave design, flywheel energy storage, velocity and acceleration control, drive safety, induction motor–driven transmissions.
    • Machine Learning in Machine Design: Machine learning and artificial intelligence for design optimization, fuzzy inference systems, wavelet-based signal analysis, rotation forest and other ensemble methods for fault diagnosis, reliability prediction.

    The journal publishes original research articles, review articles, case studies, and short communications. Medical diagnosis, power electronics, and general software studies with no machine design application are out of scope. The journal serves mechanical and design engineers, researchers in mechanisms and machine elements, product developers, and graduate students.

Keywords

Mechanism kinematics, CAD/CAM/CAE, Virtual prototyping, Mechatronic systems, Brake design, Regenerative braking, Mechanical fasteners, Thermo-mechanical fatigue, Flywheels, Fault diagnosis

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