Machine Design and Tribology

A special issue of Lubricants (ISSN 2075-4442).

Deadline for manuscript submissions: 20 June 2026 | Viewed by 860

Special Issue Editors


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Guest Editor
Faculty of Mechanical Engineering, Department of Machine Design, University of Belgrade, Belgrade, Serbia
Interests: machine design; machine elements; rolling bearings (load distribution, load carrying capacity, service life, and abrasive wear); journal bearings; gears; shafts; bolted joints; cavitation erosion wear; standardization: technical drawing, tolerances, bearings, gears, fasteners, additive manufacturing, and machinery safety

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Guest Editor
Department of Applied Mechanics and Machine Design, Faculty of Mechanical and Civil Engineering in Kraljevo, University of Kragujevac, 36000 Kraljevo, Serbia
Interests: machine design; additive manufacturing (AM); design for AM; standardization in AM; numerical simulations and analysis; material durability testing; cavitation erosion wear

Special Issue Information

Dear Colleagues,

Machine design and tribology are closely related disciplines that significantly impact the performance, efficiency, durability, and service life of mechanical systems, as well as their environmental sustainability, material resource management, and, ultimately, the global economy. The operation of machine elements is directly influenced by the development and optimization of their design based on tribological criteria.

This Special Issue invites contributions presenting results from mathematical modeling, numerical simulations, and experimental research in the tribology of machine elements and systems. We aim to highlight advances in the tribological analysis of machine elements made from new materials and the application of emerging manufacturing technologies, such as additive manufacturing. Additionally, studies utilizing artificial intelligence, machine learning, and neural networks for failure prediction and optimization are highly encouraged.

Dr. Tatjana M. Lazovic
Dr. Snežana M. Ćirić Kostić
Guest Editors

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Keywords

  • machine design
  • machine elements
  • tribology
  • wear
  • abrasive wear
  • cavitation erosion wear
  • lubrication
  • additive manufacturing
  • machine learning
  • optimization

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Published Papers (1 paper)

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Research

21 pages, 4230 KB  
Article
Dynamic Analysis and Control Compensation of the Large Optical Mirror Processing Parallel Robot Considering Motion Pair Friction
by Hao Liu, Zujin Jin and Zixin Yin
Lubricants 2025, 13(11), 504; https://doi.org/10.3390/lubricants13110504 - 18 Nov 2025
Viewed by 434
Abstract
The dynamic performance of parallel robots directly determines the machining accuracy in large optical mirror processing (LOMP). However, limitations in traditional dynamic modeling methods hinder their application in real-time control, constraining further improvements in robotic precision. This paper aims to establish a high-precision [...] Read more.
The dynamic performance of parallel robots directly determines the machining accuracy in large optical mirror processing (LOMP). However, limitations in traditional dynamic modeling methods hinder their application in real-time control, constraining further improvements in robotic precision. This paper aims to establish a high-precision and practical dynamic model that considers joint friction for parallel robots used in LOMP, and to design an efficient real-time friction compensation control strategy to effectively enhance trajectory tracking and repetitive positioning accuracy. The novelty of this work lies in proposing a dynamic modeling approach that integrates the static mechanics-based “Disassembly Method” with a “Coulomb + Viscous” friction model. First, static analysis of the mechanism is conducted using the “Disassembly Method” to accurately compute the joint constraint reactions in any pose, providing critical input for friction calculation. Subsequently, a complete dynamic model incorporating friction in joints such as Hooke joints, composite spherical hinges, and ball screws is developed based on the Newton–Euler formulation. This method overcomes the shortcomings of traditional approaches in solving joint reactions and managing model complexity. Numerical simulations demonstrate that, compared to conventional friction-neglected models, the proposed model reveals a maximum increase of approximately 350 N in driving chain joint reaction forces and significant peaks in driving forces at motion reversal instants (e.g., 0.28 s, 0.45 s), quantitatively proving that neglecting friction severely underestimates the actual system loads. Experimental validation shows that the feedforward PD friction compensator designed based on this model reduces the rotational tracking errors of the moving platform around the X- and Y-axis from 0.295° and 0.286° to 0.134° and 0.128°, respectively, achieving an error reduction of about 55% and effectively improving motion control accuracy. This study provides a reliable dynamic modeling foundation and an effective real-time control compensation solution to address force output errors and trajectory deviations caused by joint friction in high-precision LOMP. Full article
(This article belongs to the Special Issue Machine Design and Tribology)
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