Optimizing the performance of serial robots for milling tasks: A review

IF 9.1 1区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Robotics and Computer-integrated Manufacturing Pub Date : 2025-02-14 DOI:10.1016/j.rcim.2025.102977

Yuhang Gao, Tianyang Qiu, Ci Song, Senjie Ma, Zhibing Liu, Zhiqiang Liang, Xibin Wang

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引用次数: 0

Abstract

Serial industrial robots, as a great potential alternative to computer numerical control (CNC) machine tools, have attracted numerous attention, relying on their large workspace and low cost. However, a detailed and specific guidance is still missed to solve the problem of poor milling performance caused by their weak stiffness when facing milling tasks with high material removal rates (MRR). Combined with the status information, this paper systematically and comprehensively reviews the potential issues and their corresponding solutions from the aspects of posture and milling process, thus achieving better machining quality, ensuring machining stability, continuity in path, and preventing the occurrence of failures. Furthermore, future research hotspots and directions are proposed by considering the current research findings and the increasingly intelligent trends exhibited by the continuous development of the manufacturing industry.

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来源期刊

Robotics and Computer-integrated Manufacturing 工程技术-工程：制造

CiteScore

24.10

自引率

13.50%

发文量

160

审稿时长

50 days

期刊介绍： The journal, Robotics and Computer-Integrated Manufacturing, focuses on sharing research applications that contribute to the development of new or enhanced robotics, manufacturing technologies, and innovative manufacturing strategies that are relevant to industry. Papers that combine theory and experimental validation are preferred, while review papers on current robotics and manufacturing issues are also considered. However, papers on traditional machining processes, modeling and simulation, supply chain management, and resource optimization are generally not within the scope of the journal, as there are more appropriate journals for these topics. Similarly, papers that are overly theoretical or mathematical will be directed to other suitable journals. The journal welcomes original papers in areas such as industrial robotics, human-robot collaboration in manufacturing, cloud-based manufacturing, cyber-physical production systems, big data analytics in manufacturing, smart mechatronics, machine learning, adaptive and sustainable manufacturing, and other fields involving unique manufacturing technologies.