P. Georgi , M. Richter , T. Reeber , K. Güzel , H.-C. Möhring
{"title":"Methodologies for connecting an external signal-processing unit for adaptive control in machining systems","authors":"P. Georgi , M. Richter , T. Reeber , K. Güzel , H.-C. Möhring","doi":"10.1016/j.procir.2025.01.010","DOIUrl":null,"url":null,"abstract":"<div><div>Modern machine tools compensate for various thermal and mechanical disturbances using data such as temperature, motor currents, and spindle vibrations. This data is analyzed in real time for control loops involving only the machine and its control. In some cases, edge-PCs transmit data to higher-level systems like databases, MQTT, or OPC-UA, enabling offline analysis but lacking real-time feedback capability due to data transmission and limited computing power in machine controls. Consequently, complex disturbance compensation solutions remain theoretical. This paper presents a new approach to expand data handling within the machine tool environment by connecting machine tool controls with external signal processing units, allowing easy read and write access to machine parameters like speed and feed rate. This approach is also applicable to brownfield machines with limited custom control options. The paper demonstrates how this data can model machine tool behavior and outlines its use for sensor-integrated tools and self-optimizing milling.</div></div>","PeriodicalId":20535,"journal":{"name":"Procedia CIRP","volume":"132 ","pages":"Pages 56-61"},"PeriodicalIF":0.0000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Procedia CIRP","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2212827125000101","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Modern machine tools compensate for various thermal and mechanical disturbances using data such as temperature, motor currents, and spindle vibrations. This data is analyzed in real time for control loops involving only the machine and its control. In some cases, edge-PCs transmit data to higher-level systems like databases, MQTT, or OPC-UA, enabling offline analysis but lacking real-time feedback capability due to data transmission and limited computing power in machine controls. Consequently, complex disturbance compensation solutions remain theoretical. This paper presents a new approach to expand data handling within the machine tool environment by connecting machine tool controls with external signal processing units, allowing easy read and write access to machine parameters like speed and feed rate. This approach is also applicable to brownfield machines with limited custom control options. The paper demonstrates how this data can model machine tool behavior and outlines its use for sensor-integrated tools and self-optimizing milling.