Markus Meurer , Tobias Kelliger , Nicklas Gerhard , Adrian Karl Rüppel , Adina Grimmert , Thomas Bergs
{"title":"ManuSafeNextGen: Model-Based Manufacturing of Safety-Critical Components for Next Generation Engines – Part I: Methodology","authors":"Markus Meurer , Tobias Kelliger , Nicklas Gerhard , Adrian Karl Rüppel , Adina Grimmert , Thomas Bergs","doi":"10.1016/j.procir.2025.02.064","DOIUrl":null,"url":null,"abstract":"<div><div>The manufacturing of safety-critical engine components for aerospace applications involves extensive development and testing throughout the entire process chain. The numerous necessary experimental investigations and destructive metallographic analyses result in significant costs and high levels of scrap material. A key quality characteristic in the safety-critical low-pressure region of the engine is Surface Integrity (SI). This characteristic is primarily influenced by the thermo-mechanical loads induced during the manufacturing process, along with the manufacturing history of the semi-finished product. Currently, SI can only be characterized through destructive testing methods after production. This paper presents an approach currently developed by the Manufacturing Technology Institute MTI of RWTH Aachen University, the Fraunhofer Institute for Production Technology IPT, and MTU Aero Engines AG for the model-based prediction, monitoring, control, and evaluation of machining processes concerning process-induced SI characteristics. Using a multiscale approach, SI is predicted with spatial resolution along a complex component contour, based on the machining conditions. The focus of model development is on the operations of turning, broaching, and grinding the blade-disc combination. The developed models are coupled with a soft sensor installed in the machine environment, enabling SI monitoring during machining. The digital twin of the component, derived from the data, aims to enable quality assessment without the need for destructive testing of the component. This paper marks the beginning of a publication series presenting the project results obtained throughout the next years.</div></div>","PeriodicalId":20535,"journal":{"name":"Procedia CIRP","volume":"133 ","pages":"Pages 370-375"},"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/S2212827125001039","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
The manufacturing of safety-critical engine components for aerospace applications involves extensive development and testing throughout the entire process chain. The numerous necessary experimental investigations and destructive metallographic analyses result in significant costs and high levels of scrap material. A key quality characteristic in the safety-critical low-pressure region of the engine is Surface Integrity (SI). This characteristic is primarily influenced by the thermo-mechanical loads induced during the manufacturing process, along with the manufacturing history of the semi-finished product. Currently, SI can only be characterized through destructive testing methods after production. This paper presents an approach currently developed by the Manufacturing Technology Institute MTI of RWTH Aachen University, the Fraunhofer Institute for Production Technology IPT, and MTU Aero Engines AG for the model-based prediction, monitoring, control, and evaluation of machining processes concerning process-induced SI characteristics. Using a multiscale approach, SI is predicted with spatial resolution along a complex component contour, based on the machining conditions. The focus of model development is on the operations of turning, broaching, and grinding the blade-disc combination. The developed models are coupled with a soft sensor installed in the machine environment, enabling SI monitoring during machining. The digital twin of the component, derived from the data, aims to enable quality assessment without the need for destructive testing of the component. This paper marks the beginning of a publication series presenting the project results obtained throughout the next years.