Recent Advances in Materials Forming, Machining and Tribology

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

Deadline for manuscript submissions: 30 June 2026 | Viewed by 1167

Special Issue Editors


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Guest Editor
National Research Council Canada, Montreal, QC H3T2B2, Canada
Interests: sustainable manufacturing; additive subtractive manufacturing; high performance and hybrid machining processes; tribology; milling

E-Mail Website
Guest Editor
National Research Council Canada, Montreal, QC H3T2B2, Canada
Interests: robotized machining; hybird additive/subtractive; machining of composites; intelligent monitoring and adaptive control; modelling; tribology
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Special Issue Information

Dear Colleagues,

New trends in manufacturing techlogies have includeds development of sustainable and intelligent manufacturing processes, towards the implementation of Industry 4.0.

In recent years, significant advances in material forming, machining, and tribology have revolutionized the manufacturing industry. These fields have seen the development of innovative techniques and technologies aimed at enhancing precision, efficiency, and sustainability. In material forming, new techniques and materials are being developed to enhance the strength, durability, and complexity of components. Innovation in machining has led to smarter, greener and more adaptive technologies to improve product quality and productivity. Simultaneously, tribology, the study of friction, wear, and lubrication, has progressed to boost the performance and lifespan of tools and components, leading to reduced maintenance costs and lower energy consumption. Collectively, these innovations are driving the future towards more sustainable , cost-effective, and intelligent manufacturing processes.

This Special Issue seeks to publish the fundamental and applied research in topics including, but not limited to, the following:  

      - Advanced machining processes.
      - Sustainable manufacturing and life cycle analysis.
      - Tribological aspects in mancufacturing processes (lubricants, friction, wear, etc.)
      - Artificial intelligent and machinine learning.
      - Simulation-based process optimization.
      - New trends in forming processes and novel materials.
      - Additive subtractive manufacturing.

Dr. Ahmed Damir
Dr. Ahmad Sadek
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Lubricants is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • tribology
  • sustainability
  • advanced machining
  • productivity
  • forming
  • simulation and modeling
  • digital twins
  • smart manufacturing
  • additive subtractive manufacturing

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Published Papers (1 paper)

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Research

22 pages, 5340 KB  
Article
Experimental Investigation and Modelling of High-Speed Turn-Milling of H13 Tool Steel: Surface Roughness and Tool Wear
by Hamid Ghorbani, Bin Shi and Helmi Attia
Lubricants 2025, 13(10), 444; https://doi.org/10.3390/lubricants13100444 - 10 Oct 2025
Viewed by 793
Abstract
Turn-milling is a relatively new process which combines turning and milling operations, offering a number of advantages such as chip breaking and interrupted cutting, which improves tool life. In addition to providing the capability of producing eccentric forms or shapes, it increases productivity [...] Read more.
Turn-milling is a relatively new process which combines turning and milling operations, offering a number of advantages such as chip breaking and interrupted cutting, which improves tool life. In addition to providing the capability of producing eccentric forms or shapes, it increases productivity for difficult-to-machine material at lower cost. This study investigates the influence of cutting speed and feed on surface roughness and tool wear in conventional turning and turn-milling of H13 tool steel. The tests were conducted for longitudinal and face machining strategies. It was found that the range of surface roughness in turning is lower than in turn-milling. In longitudinal turning, face-turning, and face turn-milling operations, surface roughness is elevated in the higher feeds. However, the surface roughness in longitudinal turn-milling operations can be reduced by increasing the feed. Although the simultaneous rotation of the tool and workpiece in turn-milling could negatively affect the surface quality, this operation provides the advantage of an interrupted cutting mechanism that produces discontinuous chips. Also, the wear of the endmill in longitudinal and face turn-milling operations is lower than the wear of the inserts used in conventional longitudinal and face turning. Using Response Surface Methodology (RSM), mathematical models were developed for surface roughness and tool wear in each operation. The RSM models developed in this study achieved coefficients of determination (R2) above 90%, with prediction errors below 7% for surface roughness and below 3% for tool wear. The analysis of variance (ANOVA) revealed that the feed and cutting speed are the most influential parameters on the surface roughness and tool wear, respectively, with p-value < 0.05. The experimental results demonstrated that tool wear in turn-milling was reduced by up to 50% compared to conventional turning. Full article
(This article belongs to the Special Issue Recent Advances in Materials Forming, Machining and Tribology)
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