A. Suslov, D. Petreshin, M. Shalygin, Viktor Khandozhko
{"title":"Automated technological support and improvement of the operational properties of machine parts","authors":"A. Suslov, D. Petreshin, M. Shalygin, Viktor Khandozhko","doi":"10.30987/2223-4608-2024-24-33","DOIUrl":null,"url":null,"abstract":"The article outlines two directions of automated engineering support for the operational properties of machine parts (wear resistance, contact stiffness, etc.). The first direction is a traditional one. It's a two-stage provision of the operational properties of machine parts: in the first stage it is the dimensioning of working surfaces quality of the part that determines the required values of operational properties; in the second stage it is technological provision of quality parameters for the working surfaces of machine parts. The second new direction is a single – stage automated engineering support for the current operational properties of machine parts, which has been actively developed over the past 25 years at the Bryansk State Technical University. It is based on the theoretical and experimental dependences of the relationship between the operational properties of machine parts directly with the processing modes of their working surfaces. Various automated systems of scientific research have been developed to obtain experimental dependencies. An example of such an automated system for studying contact stiffness is given. Adaptive control systems used on various machines for high-performance engineering support aimed at obtaining the required quality parameters of the treated surfaces and their operational properties have been developed. When processing new materials and taking into account the absence of theoretical and experimental data, it is possible to use self-learning technological systems. An example of such a system used for a lathe, is given. All these developments contribute to the creation of the machines with artificial intelligence.","PeriodicalId":21570,"journal":{"name":"Science intensive technologies in mechanical engineering","volume":"8 41","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Science intensive technologies in mechanical engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.30987/2223-4608-2024-24-33","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 article outlines two directions of automated engineering support for the operational properties of machine parts (wear resistance, contact stiffness, etc.). The first direction is a traditional one. It's a two-stage provision of the operational properties of machine parts: in the first stage it is the dimensioning of working surfaces quality of the part that determines the required values of operational properties; in the second stage it is technological provision of quality parameters for the working surfaces of machine parts. The second new direction is a single – stage automated engineering support for the current operational properties of machine parts, which has been actively developed over the past 25 years at the Bryansk State Technical University. It is based on the theoretical and experimental dependences of the relationship between the operational properties of machine parts directly with the processing modes of their working surfaces. Various automated systems of scientific research have been developed to obtain experimental dependencies. An example of such an automated system for studying contact stiffness is given. Adaptive control systems used on various machines for high-performance engineering support aimed at obtaining the required quality parameters of the treated surfaces and their operational properties have been developed. When processing new materials and taking into account the absence of theoretical and experimental data, it is possible to use self-learning technological systems. An example of such a system used for a lathe, is given. All these developments contribute to the creation of the machines with artificial intelligence.