Robotization of Machining Processes: Theory and Industrial Applications

A special issue of Robotics (ISSN 2218-6581). This special issue belongs to the section "Industrial Robots and Automation".

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 3136

Special Issue Editors


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Guest Editor
Machine Design and Production Engineering Lab, University of Mons, Place du Parc 20, B-7000 Mons, Belgium
Interests: robotic machining; stability of machining operations; cutting force modeling and measurement; model identification; additive manufacturing
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Applied Mechanics and Robotics, Rzeszów University of Technology, 35-959 Rzeszów, Poland
Interests: mechanical systems modelling; non-linear robot control; adaptive and robust control; hybrid position/force control; fuzzy logic; artificial neural networks; underactuated systems; stability of control systems; vibration measurement; vibration analysis; vibrodiagnostics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The robotization of mechanical machining processes is an area of robot application that has been developed for many years. The use of robots mainly concerns processes that require high maneuverability and the control of interaction forces during machining. Although there are robot control strategies and algorithms dedicated to mechanical processing, many processes require a non-standard approach, e.g., in the aerospace industry. At the same time, there are many theoretical solutions for the robotization of machining that unfortunately require very strict conditions.

The purpose of this Special Issue is to present the latest developments in robotic machining that have both theoretical background and utilitarian value confirmed by real applications or even preliminary laboratory tests. New ideas on all aspects of robotic machining, such as modeling, control, vibration reduction, soft computing, process monitoring, or economic aspects, are welcome.

You may choose our Joint Special Issue in Machines.

Prof. Dr. Edouard Rivière-Lorphèvre
Prof. Dr. Piotr Gierlak
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 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. Robotics 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

  • robotization of machining
  • modeling of robot&ndash
  • workpiece systems
  • robot control strategies
  • process modeling and monitoring
  • vibration prevention
  • machining quality control
  • sensors and data acquisition
  • special tools
  • artificial intelligence applications
  • economic issues of process robotization

Published Papers (1 paper)

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Research

22 pages, 10087 KiB  
Article
Multi-Fidelity Information Fusion to Model the Position-Dependent Modal Properties of Milling Robots
by Maximilian Busch and Michael F. Zaeh
Robotics 2022, 11(1), 17; https://doi.org/10.3390/robotics11010017 - 21 Jan 2022
Cited by 6 | Viewed by 2589
Abstract
Robotic machining is a promising technology for post-processing large additively manufactured parts. However, the applicability and efficiency of robot-based machining processes are restricted by dynamic instabilities (e.g., due to external excitation or regenerative chatter). To prevent such instabilities, the pose-dependent structural dynamics of [...] Read more.
Robotic machining is a promising technology for post-processing large additively manufactured parts. However, the applicability and efficiency of robot-based machining processes are restricted by dynamic instabilities (e.g., due to external excitation or regenerative chatter). To prevent such instabilities, the pose-dependent structural dynamics of the robot must be accurately modeled. To do so, a novel data-driven information fusion approach is proposed: the spatial behavior of the robot’s modal parameters is modeled in a horizontal plane using probabilistic machine learning techniques. A probabilistic formulation allows an estimation of the model uncertainties as well, which increases the model reliability and robustness. To increase the predictive performance, an information fusion scheme is leveraged: information from a rigid body model of the fundamental behavior of the robot’s structural dynamics is fused with a limited number of estimated modal properties from experimental modal analysis. The results indicate that such an approach enables a user-friendly and efficient modeling method and provides reliable predictions of the directional robot dynamics within a large modeling domain. Full article
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