数字孪生驱动的机械加工工艺评价方法
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摘要
在动态变化的加工条件下,机械加工工艺评价已成为智能制造模式下提高工艺可执行度和缩短产品研发周期必须要解决的关键问题,为此提出了数字孪生数据驱动的机械加工工艺评价方法。以加工过程感知数据为研究对象,创建加工过程实时数据的表达模型和获取流程,为工艺评价孪生数据提供了数据源泉;创建了加工工艺评价孪生模型框架体系,提出加工过程感知数据与工艺设计数据的映射机制,实现了工艺评价孪生数据的创建;将孪生数据反馈到工艺设计系统,实现评价数据的流通性、实时性与有效性;提出了孪生数据驱动的工艺评价方法;并创建了孪生数据驱动的机械加工工艺动态评价模块。并以船用柴油机关重件为例,验证了所提方法的有效性。
Under the dynamic processing conditions,the machining process evaluation has become a key for improving process'executable and shortening development cycle in intelligent manufacturing mode.Therefore,a twin datadriven evaluation methodology of machining process was proposed.By taking the perceptual data of machining process as the research object,the representation model and acquisition process of real-time data of processing process were created to provide the data source for twin data of process evaluation.The framework system of process evaluation's twin model was established,and the mapping mechanism between perceptual data of processing process and process design data was put forward to realize the establishment of twin data that was the basis of process evaluation.The twin data was fed back to the process design system to realize the circulation,real-time and validity of the process evaluation data.Finally,the twin data-driven process evaluation method was established for the key parts of marine diesel engine.According the developed module of twin data-driven dynamic evaluation,the validity of the proposed method was verified by some examples.
Under the dynamic processing conditions,the machining process evaluation has become a key for improving process'executable and shortening development cycle in intelligent manufacturing mode.Therefore,a twin datadriven evaluation methodology of machining process was proposed.By taking the perceptual data of machining process as the research object,the representation model and acquisition process of real-time data of processing process were created to provide the data source for twin data of process evaluation.The framework system of process evaluation's twin model was established,and the mapping mechanism between perceptual data of processing process and process design data was put forward to realize the establishment of twin data that was the basis of process evaluation.The twin data was fed back to the process design system to realize the circulation,real-time and validity of the process evaluation data.Finally,the twin data-driven process evaluation method was established for the key parts of marine diesel engine.According the developed module of twin data-driven dynamic evaluation,the validity of the proposed method was verified by some examples.
引文
[1]WANG Qiulian,LI Congbo,LIU Fei.General method for energy efficiency evaluation in mechanical machining system[J].Computer Integrated Manufacturing Systems,2017,23(6):1320-1325(in Chinese).[王秋莲,李聪波,刘飞.一种通用的机械加工系统能量效率评价方法[J].计算机集成制造系统,2017,23(6):1320-1325.]
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[3]WU Yingxue.The multi-class fuzzy comprehensive appraisement of mechanical process plans[J].Journal of Central South Forestry College,2004,24(5):98-103(in Chinese).[吴迎学.机械加工工艺方案的多级模糊综合评价[J].中南林学院学报,2004,24(5):98-103.]
[4]JIAO Aisheng,YI Xiangbin,YAN Huiping.Machining program evaluation based on extension theory[J].Mechanical Science and Technology for Aerospace Engineering,2009,28(11):1482-1485(in Chinese).[焦爱胜,易湘斌,严慧萍.机械加工工艺方案的可拓评价研究[J].机械科学与技术,2009,28(11):1482-1485.]
[5]BAI Feixian,WANG Yongchao,WEI Yu,et al.Evaluation of machining process based on grey relation analysis and analytic hierarchy process[J].Modular Machine Tool&Automatic Manufacturing Technique,2018,60(8):174-176,180(in Chinese).[白飞先,汪永超,魏宇,等.基于灰色关联分析-层次分析法的机械加工工艺评价[J].组合机床与自动化加工技术,2018,60(8):174-176,180.]
[6]ZHAO Xiaoyan,SHEN Min,WANG Jingbao.Machine processing manufacturing evaluation model and its application based on low carbon manufacturing[J].Machinery Design&Manufacture,2013,51(1):81-83(in Chinese).[赵晓雁,沈敏,王静宝.基于低碳制造的机械加工工艺评价模型及应用[J].机械设计与制造,2013,51(1):81-83.]
[7]WANG Qiulian,LI Congbo,et al.General method for energy efficiency evaluation in mechanical machining system[J].Computer Integrated Manufacturing Systems,2017,23(6):1320-1325(in Chinese).[王秋莲,李聪波,刘飞.一种通用的机械加工系统能量效率评价方法[J].计算机集成制造系统,2017,23(6):1320-1325.]
[8]ZHOU Yujing,JIN Youdao.Neural network analysis on evaluating the mechanical technological parameters[J].Journal of Wuhan University of Technology,1996,18(3):89-92(in Chinese).[周毓菁,金有道.用神经网络分析法评价机械加工工艺参数[J].武汉工业大学学报,1996,18(3):89-92.]
[9]LIU Yarong.Study on the evaluation of mechanical machining process plan based on interval-based analytic hierarchy process[J].Machinery Design&Manufacture,2015,53(12):258-264(in Chinese).[刘雅荣.基于区间层次分析法的机械加工工艺方案评价研究[J].机械设计与制造,2015,53(12):258-264.]
[10]HUANG Jie,DU Pingan,LIAO Weizhi.Genetic algorithm for assembly sequences planning based on assembly constraint[J].Computer Integrated Manufacturing Systems,2007,13(4):756-761(in Chinese).[黄洁,杜平安,廖伟智.基于配合约束的装配序列规划的遗传算法研究[J].计算机集成制造系统,2007,13(4):756-761.]
[11]ZHANG Dan,ZUO Dunwen,JIAO Guangming,et al.Assembly sequence planning for aerospace products based on particle swarm optimization and genetic algorithm[J].Acta Armamentarii,2010,31(9):1228-1234(in Chinese).[张丹,左敦稳,焦光明,等.基于粒子群遗传算法的航天产品装配顺序优化方法[J].兵工学报,2010,31(9):1228-1234.]
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[14]MALIK A A,BILBERG A.Digital twins of human robot collaboration in a production setting[J].Procedia Manufacturing,2018,17:278-285.
[15]BEREQI R,SZALLER A,KADAR B.Synergy of multimodelling for process control[J].IFAC-PapersOnLine,2018,51(11):1023-1028.
[16]LOHTANDER M,AHONEN A,LANZ M,et al.Micro manufacturing unit and the corresponding 3D-model for the digital twin[J].Procedia Manufacturing,2018,25:55-61.
[17]YU Yong,HU Deyu,DAI Sheng,et al.Study on application of digital twin in process planning[J].Aeronautical Manufacturing Technology,2018,61(18):26-33(in Chinese).[于勇,胡德雨,戴晟,等.数字孪生在工艺设计中的应用探讨[J].航空制造技术,2018,61(18):26-33].
[18]TUEGEL E,INGRAFFEA A,EASON T,et al.Reengineering aircraft structural life prediction using a digital twin[J].International Journal of Aerospace Engineering,2011.DOI:10.1155/2011/154798.
[19]TAO Fei,CHENG Ying,et al.Theories and technologies for cyber-physical fusion in digital twin shop-floor[J].Computer Integrated Manufacturing Systems,2017,23(8):1603-1611(in Chinese).[陶飞,程颖,等.数字孪生车间信息物理融合理论与技术[J].计算机集成制造系统,2017,23(8):1603-1611].
[20]TAO Fei,LIU Weiran,LIU Jianhua,et al.Digital twin and its potential exploration[J].Computer Integrated Manufacturing Systems,2018,24(1):1-18(in Chinese).[陶飞,刘蔚然,刘检华,等.数字孪生及其应用探索[J].计算机集成制造系统,2018,24(1):1-18].
[21]TAO Fei,LIU Weiran,et al.Five-dimension digital twin model and its ten applications[J].Computer Integrated Manufacturing Systems,2019,25(1):1-18(in Chinese).[陶飞,刘蔚然,等.数字孪生五维模型及十大领域应用[J].计算机集成制造系统,2019,25(1):1-18.]
[22]CHEN Zhen,DING Xiao,TANG Jianjun,et al.Digital twinbased production management and control mode for aircraft assembly shop-floor[J].Aeronautical Manufacturing Technology,2018,61(12):46-50,58(in Chinese).[陈振,丁晓,唐健钧,等.基于数字孪生的飞机装配车间生产管控模式探索[J].航空制造技术,2018,61(12):46-50,58.]
[23]MACCHI M,RODA I,NEQRI E,et al.Exploring the role of digital twin for asset lifecycle management[J].IFAC-PapersOnLine,2018,51(11):790-795.
[24]LIU Jinfeng,NI Zhonghua,LIU Xiaojun,et al.Process information expression and management technology based on3Dprocess model[J].Computer Integrated Manufacturing Systems,2015,21(7):1756-1763(in Chinese).[刘金锋,倪中华,刘晓军,等.基于工艺模型的工艺信息表达与管理技术研究[J].计算机集成制造系统,2015,21(7):1756-1763.]
[25]LIU Jinfeng,LIU Xiaojun,CHENG Yalong,et al.A systematic method for the automatic update and propagation of the machining process models in the process modification[J].The International Journal of Advanced Manufacturing Technology,2016,82(1/2/3/4):473-487.
[26]LIU J,LIU X,NI Z,et al.A new method of reusing the manufacturing information for the slightly changed 3DCADmodel[J].Journal of Intelligent Manufacturing,2018,29(8):1827-1844.
[2]PUSAVEC F,KRAMAR D,KRAJNIK P,et al.Transitioning to sustainable production-PartⅡ:evaluation of sustainable machining technologies[J].Journal of Cleaner Production,2010,18(12):1211-1221.
[3]WU Yingxue.The multi-class fuzzy comprehensive appraisement of mechanical process plans[J].Journal of Central South Forestry College,2004,24(5):98-103(in Chinese).[吴迎学.机械加工工艺方案的多级模糊综合评价[J].中南林学院学报,2004,24(5):98-103.]
[4]JIAO Aisheng,YI Xiangbin,YAN Huiping.Machining program evaluation based on extension theory[J].Mechanical Science and Technology for Aerospace Engineering,2009,28(11):1482-1485(in Chinese).[焦爱胜,易湘斌,严慧萍.机械加工工艺方案的可拓评价研究[J].机械科学与技术,2009,28(11):1482-1485.]
[5]BAI Feixian,WANG Yongchao,WEI Yu,et al.Evaluation of machining process based on grey relation analysis and analytic hierarchy process[J].Modular Machine Tool&Automatic Manufacturing Technique,2018,60(8):174-176,180(in Chinese).[白飞先,汪永超,魏宇,等.基于灰色关联分析-层次分析法的机械加工工艺评价[J].组合机床与自动化加工技术,2018,60(8):174-176,180.]
[6]ZHAO Xiaoyan,SHEN Min,WANG Jingbao.Machine processing manufacturing evaluation model and its application based on low carbon manufacturing[J].Machinery Design&Manufacture,2013,51(1):81-83(in Chinese).[赵晓雁,沈敏,王静宝.基于低碳制造的机械加工工艺评价模型及应用[J].机械设计与制造,2013,51(1):81-83.]
[7]WANG Qiulian,LI Congbo,et al.General method for energy efficiency evaluation in mechanical machining system[J].Computer Integrated Manufacturing Systems,2017,23(6):1320-1325(in Chinese).[王秋莲,李聪波,刘飞.一种通用的机械加工系统能量效率评价方法[J].计算机集成制造系统,2017,23(6):1320-1325.]
[8]ZHOU Yujing,JIN Youdao.Neural network analysis on evaluating the mechanical technological parameters[J].Journal of Wuhan University of Technology,1996,18(3):89-92(in Chinese).[周毓菁,金有道.用神经网络分析法评价机械加工工艺参数[J].武汉工业大学学报,1996,18(3):89-92.]
[9]LIU Yarong.Study on the evaluation of mechanical machining process plan based on interval-based analytic hierarchy process[J].Machinery Design&Manufacture,2015,53(12):258-264(in Chinese).[刘雅荣.基于区间层次分析法的机械加工工艺方案评价研究[J].机械设计与制造,2015,53(12):258-264.]
[10]HUANG Jie,DU Pingan,LIAO Weizhi.Genetic algorithm for assembly sequences planning based on assembly constraint[J].Computer Integrated Manufacturing Systems,2007,13(4):756-761(in Chinese).[黄洁,杜平安,廖伟智.基于配合约束的装配序列规划的遗传算法研究[J].计算机集成制造系统,2007,13(4):756-761.]
[11]ZHANG Dan,ZUO Dunwen,JIAO Guangming,et al.Assembly sequence planning for aerospace products based on particle swarm optimization and genetic algorithm[J].Acta Armamentarii,2010,31(9):1228-1234(in Chinese).[张丹,左敦稳,焦光明,等.基于粒子群遗传算法的航天产品装配顺序优化方法[J].兵工学报,2010,31(9):1228-1234.]
[12]TIAN Ying,JIANG Pingyu,ZHOU Guanghui,et al.Research on part multiple process routes decision-making based on ant colony algorithm[J].Computer Integrated Manufacturing Systems,2006,12(6):882-887(in Chinese).[田颖,江平宇,周光辉,等.基于蚁群算法的零件多工艺路线决策方法研究[J].计算机集成制造系统,2006,12(6):882-887.]
[13]RABAH S,ASSILA A,KHOURI E,et al.Towards improving the future of manufacturing through digital twin and augmented reality technologies[J].Procedia Manufacturing,2018,17:460-467.
[14]MALIK A A,BILBERG A.Digital twins of human robot collaboration in a production setting[J].Procedia Manufacturing,2018,17:278-285.
[15]BEREQI R,SZALLER A,KADAR B.Synergy of multimodelling for process control[J].IFAC-PapersOnLine,2018,51(11):1023-1028.
[16]LOHTANDER M,AHONEN A,LANZ M,et al.Micro manufacturing unit and the corresponding 3D-model for the digital twin[J].Procedia Manufacturing,2018,25:55-61.
[17]YU Yong,HU Deyu,DAI Sheng,et al.Study on application of digital twin in process planning[J].Aeronautical Manufacturing Technology,2018,61(18):26-33(in Chinese).[于勇,胡德雨,戴晟,等.数字孪生在工艺设计中的应用探讨[J].航空制造技术,2018,61(18):26-33].
[18]TUEGEL E,INGRAFFEA A,EASON T,et al.Reengineering aircraft structural life prediction using a digital twin[J].International Journal of Aerospace Engineering,2011.DOI:10.1155/2011/154798.
[19]TAO Fei,CHENG Ying,et al.Theories and technologies for cyber-physical fusion in digital twin shop-floor[J].Computer Integrated Manufacturing Systems,2017,23(8):1603-1611(in Chinese).[陶飞,程颖,等.数字孪生车间信息物理融合理论与技术[J].计算机集成制造系统,2017,23(8):1603-1611].
[20]TAO Fei,LIU Weiran,LIU Jianhua,et al.Digital twin and its potential exploration[J].Computer Integrated Manufacturing Systems,2018,24(1):1-18(in Chinese).[陶飞,刘蔚然,刘检华,等.数字孪生及其应用探索[J].计算机集成制造系统,2018,24(1):1-18].
[21]TAO Fei,LIU Weiran,et al.Five-dimension digital twin model and its ten applications[J].Computer Integrated Manufacturing Systems,2019,25(1):1-18(in Chinese).[陶飞,刘蔚然,等.数字孪生五维模型及十大领域应用[J].计算机集成制造系统,2019,25(1):1-18.]
[22]CHEN Zhen,DING Xiao,TANG Jianjun,et al.Digital twinbased production management and control mode for aircraft assembly shop-floor[J].Aeronautical Manufacturing Technology,2018,61(12):46-50,58(in Chinese).[陈振,丁晓,唐健钧,等.基于数字孪生的飞机装配车间生产管控模式探索[J].航空制造技术,2018,61(12):46-50,58.]
[23]MACCHI M,RODA I,NEQRI E,et al.Exploring the role of digital twin for asset lifecycle management[J].IFAC-PapersOnLine,2018,51(11):790-795.
[24]LIU Jinfeng,NI Zhonghua,LIU Xiaojun,et al.Process information expression and management technology based on3Dprocess model[J].Computer Integrated Manufacturing Systems,2015,21(7):1756-1763(in Chinese).[刘金锋,倪中华,刘晓军,等.基于工艺模型的工艺信息表达与管理技术研究[J].计算机集成制造系统,2015,21(7):1756-1763.]
[25]LIU Jinfeng,LIU Xiaojun,CHENG Yalong,et al.A systematic method for the automatic update and propagation of the machining process models in the process modification[J].The International Journal of Advanced Manufacturing Technology,2016,82(1/2/3/4):473-487.
[26]LIU J,LIU X,NI Z,et al.A new method of reusing the manufacturing information for the slightly changed 3DCADmodel[J].Journal of Intelligent Manufacturing,2018,29(8):1827-1844.