{"title":"钢淬火工艺中材料性能和能源效率的同步优化","authors":"Harish Ganesh, E. Taleff, T. Edgar, M. Baldea","doi":"10.23919/ACC.2017.7963282","DOIUrl":null,"url":null,"abstract":"Quench hardening is a mechanical process in which steel workpieces are hardened and strengthened. It consists of heating the workpieces to a high temperature in order to transform the metal to austenite, followed by quenching in oil, water or brine. In this work, we report on potential improvements for the energy efficiency of a steel quench hardening process, currently in operation at an industrial partner, which can be achieved via model-based optimal control. To obtain a defect-free and structurally sound product, both the macroscopic temperature and microstructural properties of the workpieces need to be controlled. The novelty of this work lies in the modeling approach considered to solve the furnace energy consumption minimization problem. A previously-developed radiation-based model is used to evaluate the energy consumption and part temperature distribution as a function of the time of processing. Simultaneously, we predict the effects of process variables on microstructural evolution of the parts and their consequences on the hardness and toughness of the quenched product. A response surface method is used to find the optimal set points of the feedback controllers that minimize the furnace energy consumption without violating the heating requirements and the desired grain size. Furnace operation under optimal set points results in a significant energy efficiency gain of 3.5% when compared with the heuristic operation currently in place.","PeriodicalId":422926,"journal":{"name":"2017 American Control Conference (ACC)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Simultaneous optimization of material properties and energy efficiency of a steel quench hardening process\",\"authors\":\"Harish Ganesh, E. Taleff, T. Edgar, M. Baldea\",\"doi\":\"10.23919/ACC.2017.7963282\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Quench hardening is a mechanical process in which steel workpieces are hardened and strengthened. It consists of heating the workpieces to a high temperature in order to transform the metal to austenite, followed by quenching in oil, water or brine. In this work, we report on potential improvements for the energy efficiency of a steel quench hardening process, currently in operation at an industrial partner, which can be achieved via model-based optimal control. To obtain a defect-free and structurally sound product, both the macroscopic temperature and microstructural properties of the workpieces need to be controlled. The novelty of this work lies in the modeling approach considered to solve the furnace energy consumption minimization problem. A previously-developed radiation-based model is used to evaluate the energy consumption and part temperature distribution as a function of the time of processing. Simultaneously, we predict the effects of process variables on microstructural evolution of the parts and their consequences on the hardness and toughness of the quenched product. A response surface method is used to find the optimal set points of the feedback controllers that minimize the furnace energy consumption without violating the heating requirements and the desired grain size. Furnace operation under optimal set points results in a significant energy efficiency gain of 3.5% when compared with the heuristic operation currently in place.\",\"PeriodicalId\":422926,\"journal\":{\"name\":\"2017 American Control Conference (ACC)\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-06-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 American Control Conference (ACC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/ACC.2017.7963282\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 American Control Conference (ACC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/ACC.2017.7963282","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Simultaneous optimization of material properties and energy efficiency of a steel quench hardening process
Quench hardening is a mechanical process in which steel workpieces are hardened and strengthened. It consists of heating the workpieces to a high temperature in order to transform the metal to austenite, followed by quenching in oil, water or brine. In this work, we report on potential improvements for the energy efficiency of a steel quench hardening process, currently in operation at an industrial partner, which can be achieved via model-based optimal control. To obtain a defect-free and structurally sound product, both the macroscopic temperature and microstructural properties of the workpieces need to be controlled. The novelty of this work lies in the modeling approach considered to solve the furnace energy consumption minimization problem. A previously-developed radiation-based model is used to evaluate the energy consumption and part temperature distribution as a function of the time of processing. Simultaneously, we predict the effects of process variables on microstructural evolution of the parts and their consequences on the hardness and toughness of the quenched product. A response surface method is used to find the optimal set points of the feedback controllers that minimize the furnace energy consumption without violating the heating requirements and the desired grain size. Furnace operation under optimal set points results in a significant energy efficiency gain of 3.5% when compared with the heuristic operation currently in place.