Haiming Zhang , Jianzhong Yang , Song Gao , Xiumei Gong , Wanqiang Zhu
{"title":"Feedrate scheduling method for 3-PRS hybrid machine tools considering kinematic constraints","authors":"Haiming Zhang , Jianzhong Yang , Song Gao , Xiumei Gong , Wanqiang Zhu","doi":"10.1016/j.rcim.2025.102988","DOIUrl":null,"url":null,"abstract":"<div><div>Hybrid machine tools (HMTs), known for their fast response speed, high stiffness, and accuracy, have found wide applications in aerospace and other industries. However, maintaining stability and durability during high-speed machining necessitates careful feedrate scheduling. This study introduces a novel feedrate scheduling method for 3-prismatic-revolute-spherical (3-PRS) HMTs, ensuring that the velocities and accelerations of the drive axes remain within predefined ranges. Initially, the velocity and acceleration dynamics of the 3-PRS mechanism were scrutinized using the screw theory. Subsequently, a virtual axis programming method was introduced, transforming the HMT into a virtual double-pendulum five-axis serial machine tool. In addition, the space of the master–slave movement (SMM) concept is proposed to define the toolpath. Moreover, a strategy for constraining the tool center point rate and acceleration was devised based on the kinematic relationships between the drive axes, virtual axes, and tool center points. Simulation and experiment validated the efficacy of the feedrate scheduling method, demonstrating compliance with the kinematic constraints of the drive axes and enhanced machining efficiency.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"95 ","pages":"Article 102988"},"PeriodicalIF":9.1000,"publicationDate":"2025-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Robotics and Computer-integrated Manufacturing","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0736584525000420","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Hybrid machine tools (HMTs), known for their fast response speed, high stiffness, and accuracy, have found wide applications in aerospace and other industries. However, maintaining stability and durability during high-speed machining necessitates careful feedrate scheduling. This study introduces a novel feedrate scheduling method for 3-prismatic-revolute-spherical (3-PRS) HMTs, ensuring that the velocities and accelerations of the drive axes remain within predefined ranges. Initially, the velocity and acceleration dynamics of the 3-PRS mechanism were scrutinized using the screw theory. Subsequently, a virtual axis programming method was introduced, transforming the HMT into a virtual double-pendulum five-axis serial machine tool. In addition, the space of the master–slave movement (SMM) concept is proposed to define the toolpath. Moreover, a strategy for constraining the tool center point rate and acceleration was devised based on the kinematic relationships between the drive axes, virtual axes, and tool center points. Simulation and experiment validated the efficacy of the feedrate scheduling method, demonstrating compliance with the kinematic constraints of the drive axes and enhanced machining efficiency.
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.