计算机科学
机械加工
机床
运动学
透视图(图形)
光学(聚焦)
领域(数学)
工业工程
控制工程
人工智能
工程类
机械工程
物理
数学
光学
经典力学
纯数学
作者
Matteo Russo,Dan Zhang,Xin-Jun Liu,Zenghui Xie
标识
DOI:10.1016/j.ijmachtools.2024.104118
摘要
Parallel manipulators are generally associated with high speed, stiffness, and repeatability. Nonetheless, after decades of development, their industrial uptake is still limited when compared to serial architectures. In this paper, we investigate the reasons behind this gap between parallel machine tool potential and real-case applications with a critical analysis of the state of the art. This paper aims to provide machine tool users with the understanding of the functional and technological characteristics of parallel manipulators, as well as to help roboticists approach machining applications with an in-depth perspective and a curated collection of references. We outline fundamental modeling tools for parallel mechanisms and then explain how they can be applied to the development, optimization, and performance evaluation of machine tools, with a focus on kinematic and dynamic metrics, error analysis, and calibration. We then discuss the evolution of parallel machine tools in industry, highlighting successful designs and commercial applications. Finally, we provide our perspective of the field, summarizing the main characteristics, advantages, and disadvantages of parallel machine tools, highlighting the barriers preventing a more widespread implementation of these systems, outlining current research trends, and identifying potential future developments.
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