Hai-Long Xie , Qing-Hui Wang , Yue-Feng Li , Jing-Rong Li , A.Y.C. Nee , S.K. Ong
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引用次数: 0
Abstract
Isotropic polished surface topography (PST) and uniform material removal (MR) are the keys to achieving good polished surface quality and favorable surface functional properties. However, few methods reported thus far can ensure obtaining uniform MR, isotropic PST, and high polishing efficiency simultaneously for freeform surfaces. Therefore, this paper presents a novel trochoidal toolpath enabling simultaneous optimization of polishing efficiency, PST isotropy, and MR uniformity for freeform surfaces. With this approach, a new polishing toolpath model is proposed by combining an adaptive trochoid and an improved Hilbert curve, which has more adjustable parameters, better multi-directionality, higher randomness, and smoothness. Then, a polishing performance index, namely “PSD (Power Spectral Density) roundness”, is proposed to quantitatively characterize the PST isotropy. Based on this, a toolpath optimization algorithm with the comprehensive consideration of polishing efficiency, MR uniformity, and PST isotropy is further proposed. Finally, the proposed method was compared with existing toolpath planning methods through simulation and physic polishing experiments to demonstrate its effectiveness and superiority. The result shows that the polishing efficiency, MR uniformity, and PST isotropy are comprehensively improved by nearly 30 %, 49 %, and 20 times respectively when compared to the existing methods, which is of great significance in improving the polished surface quality for freeform surfaces.
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.