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Machines
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Recent Developments in Machine Design, Automation and Robotics
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Recent Developments in Machine Design, Automation and Robotics

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Machine Design and Theory".

Deadline for manuscript submissions: 30 April 2025 | Viewed by 6104

Special Issue Editor

Dr. Raul D. S. G. Campilho

E-Mail Website
Guest Editor
Departamento de Engenharia Mecânica, Instituto Superior de Engenharia do Porto, 4200-072 Porto, Portugal
Interests: advanced manufacturing systems; automation and robotics; industrial design
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The competitiveness of companies in the global market highly depends on the efficiency of industrial processes, which rely on technologically advanced machines and equipment. Moreover, through the extensive use of automation and robotics, it is possible to attain the required product quality, production flexibility to adapt to new product references, production rate, and low fabrication costs. Throughout time, automation and robotics became the best way to achieve the goals of the market. Therefore, these technologies are subject to continuous evolution, constantly presenting new solutions. Major advances and developments were recently experienced, both academically and industrially, with emphasis on the following:

  • Collaborative robotics (cobots): human–robot collaboration in industrial settings, safety protocols and advancements in cobot technology, and cobots in small and medium-sized enterprises.
  • Advanced control systems in automation: adaptive and predictive control algorithms, real-time control strategies for industrial processes, and integration of AI and machine learning in control systems.
  • Additive manufacturing for machine design: 3D printing applications in machine parts and design, and optimization and material advancements in additive manufacturing.
  • Smart factory and Industry 4.0: Internet of Things (IoT) applications in manufacturing, cyber–physical systems and their role in modern factories, and digital twins for predictive maintenance and optimization.
  • Sustainable manufacturing and green design: energy-efficient design and automation, recycling and eco-friendly materials in machine design, and sustainable practices in industrial robotics and automation.
  • Machine learning in robotics: reinforcement learning for robotic applications, vision-based learning and object recognition in robotics, and autonomous decision-making in robotic systems.

This Special Issue intends to bring together a significant number of contributions in this area through the publication of high-quality original works in the field, subsequently promoting its dissemination through the Open Access system.

Dr. Raul D. S. G. Campilho
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. 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.

Keywords

  • machine design
  • industrial automation
  • industrial robotics
  • collaborative robotics
  • advanced control systems
  • additive manufacturing
  • smart factory
  • Industry 4.0
  • Internet of Things (IoT)
  • sustainable manufacturing
  • green design
  • machine learning in robotics
  • automation technologies
  • robotics integration
  • adaptive control systems

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  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
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Further information on MDPI's Special Issue polices can be found here.

Published Papers (6 papers)

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20 pages, 7994 KiB  
Article
Design of Connector Assembly Equipment for the Automotive Industry
by Pedro M. P. Curralo, Raul D. S. G. Campilho, Joaquim A. P. Pereira and Francisco J. G. Silva
Machines 2024, 12(10), 731; https://doi.org/10.3390/machines12100731 - 16 Oct 2024
Viewed by 216
Abstract
The automotive industry is one of the most demanding sectors of all manufacturing industries due to its competitiveness. It is necessary to innovate through the implementation of automated and robotic equipment, leading to cycle time and labor cost reduction. This work aims to [...] Read more.
The automotive industry is one of the most demanding sectors of all manufacturing industries due to its competitiveness. It is necessary to innovate through the implementation of automated and robotic equipment, leading to cycle time and labor cost reduction. This work aims to design semi-automatic equipment to assemble cabling connectors used in the automotive sector, replacing a manual process currently taking place in an automotive components company. In the proposed equipment, the operator places a connector in the equipment, and the components (pins and seals) are automatically inserted. A vision sensor with artificial intelligence then confirms the correct application. The equipment operation defined as Finite Element Method (FEM) was applied for structural verification; the materials and fabrication processes were detailed; the associated costs were calculated, and the equipment subsets were validated. The design was successfully accomplished, and the imposed requirements were fulfilled, with significant advantages over the current process, providing new knowledge on how semi-automatic systems can be deployed to enhance the productivity and quality of manufacturing processes. The design principles and insights gained from this work can be applied to other automation challenges, particularly where manual processes need to be replaced by more efficient semi-automatic or automatic systems. The modularity of the overall solution and the design concepts of the component inserter, component feeder, and assembly process allow for its use in different assembly scenarios beyond the automotive sector, such as electronics or aerospace, providing a contribution to increased competitiveness and survival in the global market. Full article
(This article belongs to the Special Issue Recent Developments in Machine Design, Automation and Robotics)
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34 pages, 39851 KiB  
Article
Supporting Human–Robot Interaction in Manufacturing with Augmented Reality and Effective Human–Computer Interaction: A Review and Framework
by Karthik Subramanian, Liya Thomas, Melis Sahin and Ferat Sahin
Machines 2024, 12(10), 706; https://doi.org/10.3390/machines12100706 - 4 Oct 2024
Viewed by 425
Abstract
The integration of Augmented Reality (AR) into Human–Robot Interaction (HRI) represents a significant advancement in collaborative technologies. This paper provides a comprehensive review of AR applications within HRI with a focus on manufacturing, emphasizing their role in enhancing collaboration, trust, and safety. By [...] Read more.
The integration of Augmented Reality (AR) into Human–Robot Interaction (HRI) represents a significant advancement in collaborative technologies. This paper provides a comprehensive review of AR applications within HRI with a focus on manufacturing, emphasizing their role in enhancing collaboration, trust, and safety. By aggregating findings from numerous studies, this research highlights key challenges, including the need for improved Situational Awareness, enhanced safety, and more effective communication between humans and robots. A framework developed from the literature is presented, detailing the critical elements of AR necessary for advancing HRI. The framework outlines effective methods for continuously evaluating AR systems for HRI. The framework is supported with the help of two case studies and another ongoing research endeavor presented in this paper. This structured approach focuses on enhancing collaboration and safety, with a strong emphasis on integrating best practices from Human–Computer Interaction (HCI) centered around user experience and design. Full article
(This article belongs to the Special Issue Recent Developments in Machine Design, Automation and Robotics)
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16 pages, 11219 KiB  
Article
Design and Experimental Research of a Non-Destructive Detection Device for High-Precision Cylindrical Roller Dynamic Unbalance
by Zhuangya Zhang, Baorun Yang, Mingde Duan, Ruijie Gu, Shijie Liang and Yang Chen
Machines 2024, 12(10), 684; https://doi.org/10.3390/machines12100684 - 29 Sep 2024
Viewed by 289
Abstract
Due to their small size and light mass, small precision cylindrical rollers present challenges in dynamic unbalance detection, including difficulties in measurement and the risk of surface damage. This paper proposes a non-destructive detection device for assessing the dynamic unbalance of small precision [...] Read more.
Due to their small size and light mass, small precision cylindrical rollers present challenges in dynamic unbalance detection, including difficulties in measurement and the risk of surface damage. This paper proposes a non-destructive detection device for assessing the dynamic unbalance of small precision cylindrical rollers. The device utilizes an air flotation support method combined with resonance amplification to indirectly measure the dynamic unbalance. A dynamic model of the air flotation tooling-cylindrical roller vibration system was developed to explore the relationship between the vibration parameters of the air flotation tooling and the dynamic unbalance of the cylindrical roller. Modal analysis and harmonic response analysis were performed, revealing that the amplitude of the vibration system at resonance could be detected using the sensor. Additionally, modal testing was conducted to determine the natural frequency of the system. A non-destructive detection platform was constructed for testing the dynamic unbalance of cylindrical rollers. Microscopic observation of the roller surface before and after testing confirmed that the device successfully performs non-destructive detection of dynamic unbalance. Full article
(This article belongs to the Special Issue Recent Developments in Machine Design, Automation and Robotics)
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21 pages, 4249 KiB  
Article
Design and Development of a Flexible Manufacturing Cell Controller Using an Open-Source Communication Protocol for Interoperability
by Evangelos Tzimas, George Papazetis, Panorios Benardos and George-Christopher Vosniakos
Machines 2024, 12(8), 519; https://doi.org/10.3390/machines12080519 - 30 Jul 2024
Viewed by 1939
Abstract
Flexible manufacturing cells provide significant advantages in low-volume mass-customization production but also induce added complexity and technical challenges in terms of integration, control, and extensibility. The variety of closed-source industrial protocols, the heterogeneous equipment, and the product’s manufacturing specifications are main points of [...] Read more.
Flexible manufacturing cells provide significant advantages in low-volume mass-customization production but also induce added complexity and technical challenges in terms of integration, control, and extensibility. The variety of closed-source industrial protocols, the heterogeneous equipment, and the product’s manufacturing specifications are main points of consideration in the development of such a system. This study aims to describe the approach, from concept to implementation, for the development of the controller for a flexible manufacturing cell consisting of heterogeneous equipment in terms of functions and communication interfaces. Emphasis is put on the considerations and challenges for effective integration, extensibility, and interoperability. Scheduling and monitoring performed by the developed controller are demonstrated for a manufacturing cell producing microfluidic devices (bioMEMS) that consists of six workstations and a robot-based handling system. Communication between the system controller and the workstations was based on open-source technologies instead of proprietary software and protocols, to support interoperability and, to a considerable extent, code reusability. Full article
(This article belongs to the Special Issue Recent Developments in Machine Design, Automation and Robotics)
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20 pages, 7730 KiB  
Article
Accuracy Analysis of Complex Transmission System with Distributed Tooth Profile Errors
by Min Zhang, Zhijing Zhang, Jian Xiong and Xiao Chen
Machines 2024, 12(7), 459; https://doi.org/10.3390/machines12070459 - 6 Jul 2024
Cited by 1 | Viewed by 509
Abstract
Tooth profile errors are the internal excitations that cause gear meshing errors, which are critical error factors affecting gear transmission accuracy. In existing studies, it is usually regarded as a constant or random distribution function. However, the actual machined tooth profile error is [...] Read more.
Tooth profile errors are the internal excitations that cause gear meshing errors, which are critical error factors affecting gear transmission accuracy. In existing studies, it is usually regarded as a constant or random distribution function. However, the actual machined tooth profile error is not a constant, so this estimation is inconsistent with the actual situation, resulting in an inaccurate evaluation of transmission accuracy. This paper proposes a method for representing tooth profile errors using distribution errors (including systematic and random errors), and a mathematical model of distributed tooth profile errors is presented. The contact stresses of the complex transmission system were compared with those obtained by formulas, proving that tooth profile errors increase contact stress. A method for calculating gear meshing error is proposed to evaluate the actual output accuracy of the complex transmission system. Compared with the test, the output accuracy is reduced by 13.8% under the temperature environment and distributed tooth profile errors. The proposed methods can accurately predict the transmission accuracy of precision transmission systems at the design stage and provide theoretical support for reducing systematic and random errors at the gear machining stage. Full article
(This article belongs to the Special Issue Recent Developments in Machine Design, Automation and Robotics)
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15 pages, 1589 KiB  
Article
AI-Driven Virtual Sensors for Real-Time Dynamic Analysis of Mechanisms: A Feasibility Study
by Davide Fabiocchi, Nicola Giulietti, Marco Carnevale and Hermes Giberti
Machines 2024, 12(4), 257; https://doi.org/10.3390/machines12040257 - 12 Apr 2024
Viewed by 1369
Abstract
The measurement of the ground forces on a real structure or mechanism in operation can be time-consuming and expensive, particularly when production cannot be halted to install sensors. In cases in which disassembling the parts of the system to accommodate sensor installation is [...] Read more.
The measurement of the ground forces on a real structure or mechanism in operation can be time-consuming and expensive, particularly when production cannot be halted to install sensors. In cases in which disassembling the parts of the system to accommodate sensor installation is neither feasible nor desirable, observing the structure or mechanism in operation and quickly deducing its force trends would facilitate monitoring activities in industrial processes. This opportunity is gradually becoming a reality thanks to the coupling of artificial intelligence (AI) with design techniques such as the finite element and multi-body methods. Properly trained inferential models could make it possible to study the dynamic behavior of real systems and mechanisms in operation simply by observing them in real time through a camera, and they could become valuable tools for investigation during the operation of machinery and devices without the use of additional sensors, which are difficult to use and install. In this paper, the idea presented is developed and applied to a simple mechanism for which the reaction forces during operating conditions are to be determined. This paper explores the implementation of an innovative vision-based virtual sensor that, through data-driven training, is able to emulate traditional sensing solutions for the estimation of reaction forces. The virtual sensor and relative inferential model is validated in a scenario as close to the real world as possible, taking into account interfering inputs that add to the measurement uncertainty, as in a real-world measurement scenario. The results indicate that the proposed model has great robustness and accuracy, as evidenced by the low RMSE values in predicting the reaction forces. This demonstrates the model’s effectiveness in reproducing real-world scenarios, highlighting its potential in the real-time estimation of ground reaction forces in industrial settings. The success of this vision-based virtual sensor model opens new avenues for more robust, accurate, and cost-effective solutions for force estimation, addressing the challenges of uncertainty and the limitations of physical sensor deployment. Full article
(This article belongs to the Special Issue Recent Developments in Machine Design, Automation and Robotics)
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