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Machines
Special Issues
AI-Integrated Advanced Robotics towards Industry 5.0
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AI-Integrated Advanced Robotics towards Industry 5.0

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Advanced Manufacturing".

Deadline for manuscript submissions: 30 August 2024 | Viewed by 1170

Special Issue Editors

Dr. Bugra Alkan

E-Mail Website
Guest Editor
School of Engineering, London South Bank University, 103 Borough Rd., London SE1 0AA, UK
Interests: smart manufacturing; IoT; robotics; manufacturing systems; industry 4.0; operations research; optimization; assembly systems
Special Issues, Collections and Topics in MDPI journals
Dr. Malarvizhi Kaniappan Chinnathai

E-Mail Website
Guest Editor Assistant
School of Computer Science and Engineering, University of Westminster, 115 New Cavendish St, London W1W 6UW, UK
Interests: industrial automation and robotics; zero defect manufacturing; applied artificial intelligence; simulation-based optimisation; industry 4.0; digital twin
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The utilisation of robotic systems is prevalent in various industries such as construction, automotive, aerospace and semiconductors. The advancements in artificial intelligence, such as machine learning, deep learning and optimisation techniques have enhanced the operational capabilities of robotic-based manufacturing and assembly systems. The integration of novel concepts including big data analytics, process mining, collaborative robotics, cyber-physical systems, swarm intelligence, reinforcement learning and digital transformation holds the potential to enhance and optimise current production systems. Moreover, they can play a crucial role in proactive policy formulation, evaluation of health and safety, mitigation of risks and examination of the ethical ramifications associated with smart manufacturing systems. Hence, the primary objective of this Special Issue is to provide a comprehensive compilation of cutting-edge strategies and emerging trends/technologies within the domain of robotic-integrated smart manufacturing systems. It further aims to examine the various challenges and opportunities that arise from the integration of artificial intelligence into the domain of industrial robotics systems towards realising the goals of the concept of Industry 5.0, where robots and smart machines work alongside people to add resilience and sustainability to the manufacturing systems.

Topics of interest include, but are not limited to, the following:

  • Collaborative robots in smart manufacturing and assembly;
  • Simulation and modeling of robotic systems;
  • Energy monitoring and optimisation of robotic systems;
  • Data-driven cyber-physical robotic manufacturing and assembly;
  • Decision-support systems for robotic applications;
  • Intelligent robot-enabled material handling solutions;
  • Path planning for automated guided vehicles and mobile robots for shop-floor logistics;
  • Intelligent and adaptive gripper systems.

Dr. Bugra Alkan
Guest Editor

Dr. Malarvizhi Kaniappan Chinnathai
Guest Editor Assistant

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. Machines 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 2400 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.

Published Papers (1 paper)

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Research

23 pages, 7079 KiB  
Article
An Integrated Architecture for Robotic Assembly and Inspection of a Composite Fuselage Panel with an Industry 5.0 Perspective
by Gaetano Lettera and Ciro Natale
Machines 2024, 12(2), 103; https://0-doi-org.brum.beds.ac.uk/10.3390/machines12020103 - 01 Feb 2024
Viewed by 898
Abstract
Aeronautical robotic applications use quite large, heavy robots with huge end effectors that are frequently multifunctional. An assembly jig to hold a fuselage panel and two medium-sized six-axis robots fixed on linear axes, referred to as the internal and the external robot with [...] Read more.
Aeronautical robotic applications use quite large, heavy robots with huge end effectors that are frequently multifunctional. An assembly jig to hold a fuselage panel and two medium-sized six-axis robots fixed on linear axes, referred to as the internal and the external robot with respect to the curvature of the panel, make up the Lean robotized AssemBly and cOntrol of composite aeRostructures (LABOR) work cell. A distributed software architecture is proposed in which individual modules are developed to execute specific subprocesses, each implementing innovative algorithms that solve the main drawbacks of state-of-the-art solutions. Real-time referencing adopts a point-cloud-based strategy to reconstruct and process the part before drilling, avoiding hole positioning errors. Accurate concentric countersink diameters are made possible through the automatic adjustment of the drilling tool with respect to the skin panel, which guarantees its orthogonality, as well as the implementation of process parameter optimization algorithms based on historical results that compensate for the wear of the drilling bits. Automatic sealing and fastening strategies that involve the measurement of the main fastener quality parameters allow for the complete verification of the entire assembly process of each part. Additionally, an advanced multimodal perception system continuously monitors the collaborative workspace to ensure safe human–robot collaboration (HRC) tasks. Through this integrated architecture, LABOR substantially reduces expenses and facilitates maintenance and programming. Full article
(This article belongs to the Special Issue AI-Integrated Advanced Robotics towards Industry 5.0)
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