An overview of robot applications in automotive industry

Bartoš, Michal; Bulej, Vladimír; Bohušík, Martin; Stanček, Ján; Іванов, Віталій Олександрович; Macek, Peter

doi:10.1016/j.trpro.2021.07.052

Cited by 35 publications

(12 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Duong et al [55] reviewed industry 4.0 and robotic implements in the food industry supply chains. Bartos et al [56] presented an interesting review of robotics in automotive manufacturing and assembly units. Unhelkar et al [57] reviewed literature published on industry 4.0-led enhancement of supply chains, particularly in RFID technology.…”

Section: A Related Reviewsmentioning

confidence: 99%

Robotics in Industry 4.0: A Bibliometric Analysis (2011-2022)

Sekhar

Shah²,

Iswanto

2022

Journal of Robotics and Control

View full text Add to dashboard Cite

Robotics forms an integral part of industry 4.0, the industrial revolution of the 21st century. This paper presents a bibliometric analysis of Web of Science (WoS) indexed publications addressing this emerging field from 2011 till June 2022. WoS research publications were firstly analysed along multiple verticals such as annual counts, types, publishing sources, research directions, researchers, organizations, and countries. Next, co-authorship collaborations among authors, organizations, and countries were discovered. This was followed by an analysis of co-occurring keywords related to robotics in industry 4.0. Finally, a detailed citation analysis was carried out to unearth citation linkages among authors, institutions, documents, nations, and journals. Latest trends, under-investigated topics, and future directions are also discussed. Primary results indicate that more than 3000 articles are being published annually in this emerging field, with a total of 18,893 documents published in WoS during the last decade. The 'IEEE Access', Chinese Academy of Science, Wang Y. (USA), and the USA emerged as the topmost productive journal, institution, author, and nation. Porpiglia Francesco (Italy), Chinese Academy Science and USA obtained the highest co-authorship total link strength (TLS); whereas Lee Chengkuo (Singapore), China, Chinese Academy Science, and the IEEE Access scored the highest citation TLS among authors, countries, organizations, and sources respectively. Machine learning (ML) emerged as the highest co-occurring keyword, followed by artificial intelligence (AI). Computer Science emerged as the most trending research domain, followed by general applications. In the future, ML and AI will advance more sophisticated robots in industry 4.0 systems.

show abstract

Section: A Related Reviewsmentioning

confidence: 99%

Robotics in Industry 4.0: A Bibliometric Analysis (2011-2022)

Sekhar

Shah²,

Iswanto

2022

Journal of Robotics and Control

View full text Add to dashboard Cite

show abstract

“…The development scale and technological level of automobile manufacturing industry is an important symbol of a comprehensive national strength for a country. This industry involves cross amalgamation of several fields like machinery, materials, logistics, management etc., as one of the first industries that introduce robotics into the manufacturing process [3][4][5][6][7]. In the field of automobile manufacturing, traditional labor-intensive industries are being replaced by technology-intensive industries gradually.…”

Section: Introductionmentioning

confidence: 99%

“…In the field of automobile manufacturing, traditional labor-intensive industries are being replaced by technology-intensive industries gradually. Thus, the construction of intelligent manufacturing factories relying on automated production will become the mainstream, and the robots will become more and more important in relevant production activities [2][3][4]7], meaning that optimization of robot's performance is the key to improvement of production efficiency.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Reconfigurability in Automobiles—Structure, Manufacturing and Algorithm for Automobiles

Zhuang¹,

Guan²,

Xu³

et al. 2022

IJAMM

View full text Add to dashboard Cite

Review Reconfigurability in Automobiles—Structure, Manufacturing and Algorithm for Automobiles Zheming Zhuang 1, Yuntao Guan 1, Shuangjia Xu 2,4, and Jian S. Dai 3,4, * 1 Key Laboratory of Mechanism Theory and Equipment Design of the Ministry of Education, Centre for Advanced Mechanisms and Robotics, Tianjin University, Tianjin, 300072, China zhuangzheming@tju.edu.cn (Z.Z.); guanyuntao_018@tju.edu.cn (Y.G.) 2 DH Robotics Ltd, Shenzhen, China; Shuangjia.xu@dh-robotics.com 3 Institute for Robotics, Southern University of Science and Technology, Shenzhen, China 4 Centre for Robotics Research, King’s College London, London, UK * Correspondence: jian.dai@kcl.ac.uk Received: 9 November 2022 Accepted: 10 November 2022 Published: 18 December 2022 Abstract: For the automobile design and manufacturing, as a typical representative of the industry, the development and upgrading represent the application of the state-of-the-art technology in the industry. With a period of development, the related technology of traditional manufacturing factories for automobiles are found with some common issues while improving. As such, the reconfigurable intelligent manufacturing factory of the automobiles is fast developed with focus on reconfigurability in structures, manufactures and algorithms, thus advancing the level of the reconfigurable intelligent manufacturing continuously. With a sufficient reconfigurable manufacturing technology as the basis, reconfigurability can be better introduced to the structure design and the driving algorithms of the automobiles. Reconfigurability provides a new bridge for transforming the traditional automobile to the reconfigurable automobile, and a new driving force for the upgrading of the reconfigurable driving algorithms.

show abstract

“…The measuring system for sensing flexural motions of compliant mechanism based on the distance laser sensor and the camera vision is presented in [ 4 ]. Basic calibration processes use camera vision for object recognition implementing an IRVision (FANUC company) system based on a two-dimensional dot grid with the definition of the calibration points described in [ 5 ]. This method is a commercial system dedicated to camera vision in industrial robotic applications.…”

Section: Introductionmentioning

confidence: 99%

Design of the Automated Calibration Process for an Experimental Laser Inspection Stand

Klarák

Andok

Hricko

et al. 2022

Sensors

View full text Add to dashboard Cite

This paper deals with the concept of the automated calibration design for inspection systems using laser sensors. The conceptual solution is based on using a laser sensor and its ability to scan 3D surfaces of inspected objects in order to create a representative point cloud. Problems of scanning are briefly discussed. The automated calibration procedure for solving problems of errors due to non-precise adjustment of the mechanical arrangement, possible tolerances in assembly, and their following elimination is proposed. The main goal is to develop a system able to measure and quantify the quality of produced objects in the environment of Industry 4.0. Laboratory measurements on the experimental stand, including the principal software solution for automated calibration of laser sensors suitable for gear wheel inspection systems are presented. There is described design of compensation eccentricity by Fourier transform and sinusoidal fitting to identify and suppress the first harmonic component in the data with high precision measuring.

show abstract

An overview of robot applications in automotive industry

Cited by 35 publications

References 9 publications

Robotics in Industry 4.0: A Bibliometric Analysis (2011-2022)

Robotics in Industry 4.0: A Bibliometric Analysis (2011-2022)

Reconfigurability in Automobiles—Structure, Manufacturing and Algorithm for Automobiles

Design of the Automated Calibration Process for an Experimental Laser Inspection Stand

Contact Info

Product

Resources

About