Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.2
3.3
Journals
JMMP
Special Issues
Advances in Robotic-Assisted Manufacturing Systems
share announcement

Advances in Robotic-Assisted Manufacturing Systems

A special issue of Journal of Manufacturing and Materials Processing (ISSN 2504-4494).

Deadline for manuscript submissions: 31 March 2026 | Viewed by 1258

Special Issue Editor

Dr. Zhanxi Wang

E-Mail Website
Guest Editor
School of Mechanical Engineering, Northwestern Polytechnical University, Xi’an 710072, China
Interests: bionic robotics; intelligent manufacturing technology; industry robotics

Special Issue Information

Dear Colleagues,

Robots have typical advantages such as easy installation, flexible use, high degrees of freedom, strong load capacity, and the ability to operate in hazardous environments. Robots can serve as industrial platforms, paired with different end effectors, to complete various manufacturing processes, such as processing, assembly, laying, welding, handling, and measurement. Moreover, in different manufacturing processes, it can replace humans in order to achieve digital and intelligent manufacturing. In recent years, with the advancement of high-precision execution capabilities, multifunctional end effectors, human–machine interaction, rapid programming, multi-machine collaboration, sensors, and other technologies, robots are receiving significant attention in the manufacturing field, and more and more robot-assisted manufacturing systems are being applied in industrial production sites.

In this Special Issue of JMMP, we are looking for recent findings which focus on Robotic-Assisted Manufacturing Systems, including research on their application and associated research fields. Papers will be considered that show significant advancements according to human–machine integration, digital twins, human–machine collaboration, reconfigurable robots, autonomous mobile robots, intelligent robots, and typical applications of robots in various manufacturing processes.

Dr. Zhanxi Wang
Guest Editor

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 100 words) can be sent to the Editorial Office for announcement on this website.

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. Journal of Manufacturing and Materials Processing 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 1800 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

  • collaborative robots
  • industrial robots
  • biomimetic robots
  • auxiliary assembly
  • intelligent measurement
  • polishing
  • hole making
  • welding
  • composite material laying
  • human–machine interaction
  • machine vision

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

13 pages, 958 KiB  
Article
Efficient Manufacturing of Steerable Eversion Robots with Integrated Pneumatic Artificial Muscles
by Thomas Mack, Cem Suulker, Abu Bakar Dawood and Kaspar Althoefer
J. Manuf. Mater. Process. 2025, 9(7), 223; https://doi.org/10.3390/jmmp9070223 - 1 Jul 2025
Viewed by 261
Abstract
Soft-growing robots based on the eversion principle are renowned for their ability to rapidly extend along their longitudinal axis, allowing them to access remote, confined, or otherwise inaccessible spaces. Their inherently compliant structure enables safe interaction with delicate environments, while their simple actuation [...] Read more.
Soft-growing robots based on the eversion principle are renowned for their ability to rapidly extend along their longitudinal axis, allowing them to access remote, confined, or otherwise inaccessible spaces. Their inherently compliant structure enables safe interaction with delicate environments, while their simple actuation mechanisms support lightweight and low-cost designs. Despite these benefits, implementing effective navigation mechanisms remains a significant challenge. Previous research has explored the use of pneumatic artificial muscles mounted externally on the robot’s body, which, when contracting, induce directional bending. However, this method only offers limited bending performance. To enhance maneuverability, pneumatic artificial muscles embedded in between the walls of double-walled eversion robots have also been considered and shown to offer superior bending performance and force output as compared to externally attached muscle. However, their adoption has been hindered by the complexity of the current manufacturing techniques, which require individually sealing the artificial muscles. To overcome this multi-stage fabrication approach in which muscles are embedded one by one, we propose a novel single-step method. The key to our approach is the use of non-heat-sealable inserts to form air channels during the sealing process. This significantly simplifies the process, reducing production time and effort and improving scalability for manufacturing, potentially enabling mass production. We evaluate the fabrication speed and bending performance of robots produced in this manner and benchmark them against those described in the literature. The results demonstrate that our technique offers high bending performance and significantly improves the manufacturing efficiency. Full article
(This article belongs to the Special Issue Advances in Robotic-Assisted Manufacturing Systems)
►▼ Show Figures

Figure 1

15 pages, 3625 KiB  
Article
Research on Robot Cleaning Path Planning of Vertical Mixing Paddle Surface
by Zhouzheng Shi, Leiyang Guo, Jingde Li, Ni Cao, Xiansheng Qin and Zhanxi Wang
J. Manuf. Mater. Process. 2025, 9(6), 198; https://doi.org/10.3390/jmmp9060198 - 12 Jun 2025
Viewed by 430
Abstract
The safe removal of residual flammable contaminants from vertical mixer blades is a crucial challenge in aerospace propellant production. While robotic cleaning has become the preferred solution due to its precision and operational safety, the complex helical geometry of mixer blades presents significant [...] Read more.
The safe removal of residual flammable contaminants from vertical mixer blades is a crucial challenge in aerospace propellant production. While robotic cleaning has become the preferred solution due to its precision and operational safety, the complex helical geometry of mixer blades presents significant challenges for robotic systems, primarily in three aspects: (1) dynamic sub-region division, requiring simultaneous consideration of functional zones and residue distribution, (2) ensuring path continuity across surfaces with varying curvature, and (3) balancing time–energy efficiency in discontinuous cleaning sequences. To address these challenges, this paper proposes a novel robotic cleaning path planning method for complex curved surfaces. Firstly, we introduce a blade surface segmentation approach based on the k-means++ clustering algorithm, along with a sub-surface patch boundary determination method using parameterized curves, to achieve precise surface partitioning. Subsequently, robot cleaning paths are planned for each sub-surface according to cleaning requirements and tool constraints. Finally, with total cleaning time as the optimization objective, a genetic algorithm is employed to optimize the path combination across sub-facets. Extensive experimental results validate the effectiveness of the proposed method in robotic cleaning path planning. Full article
(This article belongs to the Special Issue Advances in Robotic-Assisted Manufacturing Systems)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop