多参数耦合制造过程质量控制方法的研究
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摘要
本文以多工序制造过程为研究对象,针对多工序制造过程工序多、工艺复杂、制造成本高、质量影响因素多和误差源识别困难等特点,进行面向制造过程的质量控制方法的研究。
首先阐述了质量控制研究的背景及国内外发展现状,针对传统过程质量控制方法的局限性,提出面向制造过程的质量控制方法研究将成为未来研究的重点。
然后对多工序制造过程的结构和特点进行研究,分析制造过程质量波动的规律及过程误差的来源与特点。多工序制造过程属于离散时变动态系统,首先采用状态空间方程建立误差传递的基本模型,其次利用齐次变换将制造过程误差的影响关系映射到基本模型中,分别建立加工和装配过程的三维误差传递模型。
为适应质量控制对象由产品转向过程的趋势。以误差传递模型为基础,对多工序制造过程中的可控性、可观测性和稳定性进行了研究,得到制造过程是否处于可控、可观测和稳定的判定条件,并为模型的最优控制和最优估计打下基础。
在制造过程中,夹具定位点的设计位置导致产品产生误差和质量损失。为了保证产品的质量、提高生产率、降低生产成本,本文又以误差传递模型为基础对多工序制造过程中的夹具进行优化设计,并对面向制造过程的公差进行优化分配。最后,对制造过程进行误差溯源,利用虚拟工序的方法判断制造过程中产生误差的根源,进一步确保了产品的质量。
文中提出的理论和方法在发动机缸盖的制造过程中得到应用,验证了理论研究的正确性,并取得了良好的效果。
Allusion to multi-stage, complicated processes, high manufacturing cost, many influencing quality factors and difficulty varriation diagnosis et al, this thesis takes multi-stage manufacturing process for objects to research on process quality control method.
Fistly, this thesis introduces the background and development of quality cotrol in the world, which indicates the limitations of traditional quality control method, Meanwhile, which also shows the importance of process quality cotrol in the future.
Secondly, this paper analyses the structure and feature of multi-stage manufacturing process and the manufacturing process qaulity fluctuation rule. Due to multi-stage manufacturing process belonging to discrete time-varying dynamic system, this thesis establishs the basic variation transfer model using the state space equation, once more, which maps manufacturing process variation’s influencing relation to the basic variation model in oder to establish the variation transfer model using homogeneous transformation.
The qulity stability, controllability and observability of multi-stage manufacturing process was investigated for transformation from production to process in qulity control, and the condition of judgement of which were calculated based on the variation transfer model.
According to fixture locating variation directily impacting the quality in multi-stage manufacturing process, this reseach aims to get a systematic method for fixture adjustment to minimize total production costs, which also establishs a mathematic model for the tolerance optimal allocation. finally, the source of quality variation was solved by the concept of using virtual process to further making sure the quality of the products.
Two cases study were provided to illustrate the availability of the method in this thesis. The results show that the proposed model has a good performance for quality control in the multi-processes manufacturing process.
首先阐述了质量控制研究的背景及国内外发展现状,针对传统过程质量控制方法的局限性,提出面向制造过程的质量控制方法研究将成为未来研究的重点。
然后对多工序制造过程的结构和特点进行研究,分析制造过程质量波动的规律及过程误差的来源与特点。多工序制造过程属于离散时变动态系统,首先采用状态空间方程建立误差传递的基本模型,其次利用齐次变换将制造过程误差的影响关系映射到基本模型中,分别建立加工和装配过程的三维误差传递模型。
为适应质量控制对象由产品转向过程的趋势。以误差传递模型为基础,对多工序制造过程中的可控性、可观测性和稳定性进行了研究,得到制造过程是否处于可控、可观测和稳定的判定条件,并为模型的最优控制和最优估计打下基础。
在制造过程中,夹具定位点的设计位置导致产品产生误差和质量损失。为了保证产品的质量、提高生产率、降低生产成本,本文又以误差传递模型为基础对多工序制造过程中的夹具进行优化设计,并对面向制造过程的公差进行优化分配。最后,对制造过程进行误差溯源,利用虚拟工序的方法判断制造过程中产生误差的根源,进一步确保了产品的质量。
文中提出的理论和方法在发动机缸盖的制造过程中得到应用,验证了理论研究的正确性,并取得了良好的效果。
Allusion to multi-stage, complicated processes, high manufacturing cost, many influencing quality factors and difficulty varriation diagnosis et al, this thesis takes multi-stage manufacturing process for objects to research on process quality control method.
Fistly, this thesis introduces the background and development of quality cotrol in the world, which indicates the limitations of traditional quality control method, Meanwhile, which also shows the importance of process quality cotrol in the future.
Secondly, this paper analyses the structure and feature of multi-stage manufacturing process and the manufacturing process qaulity fluctuation rule. Due to multi-stage manufacturing process belonging to discrete time-varying dynamic system, this thesis establishs the basic variation transfer model using the state space equation, once more, which maps manufacturing process variation’s influencing relation to the basic variation model in oder to establish the variation transfer model using homogeneous transformation.
The qulity stability, controllability and observability of multi-stage manufacturing process was investigated for transformation from production to process in qulity control, and the condition of judgement of which were calculated based on the variation transfer model.
According to fixture locating variation directily impacting the quality in multi-stage manufacturing process, this reseach aims to get a systematic method for fixture adjustment to minimize total production costs, which also establishs a mathematic model for the tolerance optimal allocation. finally, the source of quality variation was solved by the concept of using virtual process to further making sure the quality of the products.
Two cases study were provided to illustrate the availability of the method in this thesis. The results show that the proposed model has a good performance for quality control in the multi-processes manufacturing process.
引文
[1]赵妙霞,蒋钧钧,胡立志等.机械精度设计与质量控制[M].兰州:兰州大学出版社,2004
[2]于涛.工序质量控制系统研究[M].北京:经济管理出版社,2002
[3] Page E. S. Continuous inspection schemes, biometrics[J]. Mathematics & Physical Sciences,1954, 41(2):100-115
[4] S. W. Roberts. Comtrol chart tests based on geometric moving average. Technometrics[J],1959,1(3):83-85
[5] Holmes D. S, A. E. Mergen. Process acceptance charts for short runs[J]. Quality Engineering,1997,10(1):149-153
[6] Steiner S. H. Pre-control and some simple alternatives[J]. Quality Engineering,1997,10(1):65-74
[7]张公绪.两种质量诊断理论与应用[M].北京:科学出版社,2001
[8]殷纯永.质量工程导论[M].北京:中国计量出版社,1998
[9]赵家黎,郭伟,于鸿彬.制造过程中误差传播问题研究的进展分析[J].中国机械工程,2006,增刊,445-449
[10]罗振壁,汪劲松,贾岿等.制造过程加工误差流及其模型的研究[J].机械工程学报,1994,30(1):112-118
[11]罗振壁,汪劲松,杨世明等.制造过程质量控制中误差流理论的研究[J].机械工程学报,1995,31(4):62-69
[12] Hu S. J. Stream of variation theory for automotive body assembly[J]. Annals of 111e CIRP,1997,46(1):1-6
[13] Cai W, Hu S. J, Yuan J. X. Deformable sheet metal fixturing: principles, algorithms, and simulations[J]. journal of manufacturing science and engineering,1999,121:771-777
[14] Liu S. C, Hu S.J. Sheet metal joint configurations and their variation characteristics[J]. Journal of Manufacturing Science and Engineering,1998,120:461.467
[15] Liu S. C, Hu S. J. Tolerance analysis for sheet metal assemblies[J]. Journal of Mechanical Design,1996,l18:62-67
[16] Ceglarek D, Shi J, Wu S. M. A knowledge-based diagnosis approach for the launch of the auto-body assembly process[J]. ASME Journal of Engineering forIndustry,1994,116(4):491-499
[17] Ceglarek D, Hu S. J. Fixture failure diagnosis for auto-body assembly using pattern recognition[J]. Journal of Engineering for Industry,1996,l18:55-66
[18] Daniel Y, Fong T, Lawless J. F. The analysis of process variation tranmission with multivariate measurements[J]. Statistica Sinica,1998,46(8):151-164
[19] Lawless J. F, Mackay R. J, Robinson J A. Analysis of variation transmission in manufacturing processes-part I[J]. Journal of Quality Technology,1999,31(2):131–142
[20] Mantripragada. R, Whitney D. E. Modeling and controlling variation propagation in mechanical assemblies using state transition models[J]. IEEE Transactions On Robotics AndAutomation,1999,15(1):124-140
[21] Lee Don J, Thornton Anna C, The identification and use of key characteristics in the product development process[J]. Proceedings of The 1996 ASME Design Engineering Technical Conferencesand Computers in Engineering Conference,August 18-22,1996,Irvine,California
[22] Thornton A. C, Quantitative selection of variation reduction plans[J]. Joumal of Mechanical Design,2000,122:185-193
[23]林忠钦,胡敏,来新民等.轿车白车身点焊装配过程有限元分析[J].焊接学报,2001,22(1):36-40
[24]杜世昌,奚立峰,潘尔顺.串并联混合式多阶段制造系统产品质量建模与控制[J].计算机集成制造系统,2006,12(7):1068.1073
[25]赵家黎,郭伟,牛占文等.基于误差流理论的多工位装配过程质量稳定性[J].机械工程学报,2006,42(11):88-92
[26] Ran Jin, Jing Li, Jianjun Shi. Quality prediction and control in rolling processes using logistic regression[J]. Transactions of NAMRI/SME,2007,vol.35,pp.113-120
[27]吴少雄,徐伟.基于规则的统计质量控制专家系统构建[J] .福建电脑,2005,11:104105
[28]胡兴才.基于小批量的统计过程控制研究与系统开发[D].南京:南京航空航天大学机电学院,2006,1-4
[29]杨鸿鹏,林志航.基于集成诊断模型加工质量的智能诊断系统研究[J].西安交通大学学报,1997,31(9):23.29
[30]张琳娜.加工误差及其预报建模研究[J].计量学报,1998,19(3):183,189
[31]曲兴华等.制造质量控制溯源技术研究的新进展[J].中国机械工程,1999,10(9):93-101
[32] L. P. Khoo, C. L. Ang, J. Zhang. A fuzzy-based genetic approach to the diagnosis of manufacturing systems[J]. Ttansaction of the ASME, Journal of Engineering for industry,1999,5(2):1014-1021
[33] [王波.机械加工偏差的神经网络预测方法[J].华东船舶工业学院学报,1997,12:44.48
[34]陈康宁,林志航,杨鸿鹏.基于神经网络和模糊逻辑的加工误差源诊断系统[J].西安交通大学学报,1995,29(7):60-65
[35]郑唯唯,安会刚,杜涛.过程质量控制的BP神经网络预测方法研究[J].数字设计与数字制造,2007,(9):8.10
[36]陈立周.稳健设计[M].北京:机械工业出版社,2000
[37]奚立峰,杜世昌.多工序制造过程的误差分析方法与应用[J].学术与创新,2006,42(11):35-38
[38]戴敏.多工序制造过程质量分析方法与信息集成技术研究[D].南京:东南大学,2005:11
[39]廖永平.机械工业企业质量管理[M].北京:机械工业出版社,1987
[40]王福保,李炳钊.概率论及数理统计[M].上海:同济大学出版社,1994
[41] Richard B.Chase等著,宋国防等译.生产与运作管理制造与服务,北京:机械工业出版社,1999,192-204
[42]廖春良,陈敬东,林筠.现代制造企业竞争重点分析[J].生产力研究,2004,135(3):129-130
[43]张公绪,孙静.现代质量控制与诊断工程[M].北京:经济科学出版社,1999
[44] Francisco Aparisi. Sampling Plans for Multivariate T~2 Control Chart[J], Quality Engineering, 1997-98, 10(1): 141-147
[45]蔡自兴.机器人学[M].北京:清华大学出版社,2000
[46]杜世昌.多源多工序加工系统偏差流建模、诊断和控制系统研究[D].上海:上海交通大学,2008:6
[47]龚德恩.离散控制系统理论引论[M].北京:中国铁道工业出版社,2004
[48]肖扬.动态系统分析[M].北京:北方交通大学出版社,2002
[49] Chaipradabgiat, Thavanrath, Jin, et al. Optimal fixture locator adjustment strategies for multi-station assembly processes[J]. IIE Transactions,2009,41:9,843-852
[50]周世学.机械制造工艺与夹具[M].北京:北京理工大学出版社,2006
[51]汤湘中.机床夹具设计[M].北京:国防工业出版社,1988
[52]吴文,张伟社.基于制造一质量损失成本的公差优化分配法[J].长安大学学报,2005,25(3):89-93
[2]于涛.工序质量控制系统研究[M].北京:经济管理出版社,2002
[3] Page E. S. Continuous inspection schemes, biometrics[J]. Mathematics & Physical Sciences,1954, 41(2):100-115
[4] S. W. Roberts. Comtrol chart tests based on geometric moving average. Technometrics[J],1959,1(3):83-85
[5] Holmes D. S, A. E. Mergen. Process acceptance charts for short runs[J]. Quality Engineering,1997,10(1):149-153
[6] Steiner S. H. Pre-control and some simple alternatives[J]. Quality Engineering,1997,10(1):65-74
[7]张公绪.两种质量诊断理论与应用[M].北京:科学出版社,2001
[8]殷纯永.质量工程导论[M].北京:中国计量出版社,1998
[9]赵家黎,郭伟,于鸿彬.制造过程中误差传播问题研究的进展分析[J].中国机械工程,2006,增刊,445-449
[10]罗振壁,汪劲松,贾岿等.制造过程加工误差流及其模型的研究[J].机械工程学报,1994,30(1):112-118
[11]罗振壁,汪劲松,杨世明等.制造过程质量控制中误差流理论的研究[J].机械工程学报,1995,31(4):62-69
[12] Hu S. J. Stream of variation theory for automotive body assembly[J]. Annals of 111e CIRP,1997,46(1):1-6
[13] Cai W, Hu S. J, Yuan J. X. Deformable sheet metal fixturing: principles, algorithms, and simulations[J]. journal of manufacturing science and engineering,1999,121:771-777
[14] Liu S. C, Hu S.J. Sheet metal joint configurations and their variation characteristics[J]. Journal of Manufacturing Science and Engineering,1998,120:461.467
[15] Liu S. C, Hu S. J. Tolerance analysis for sheet metal assemblies[J]. Journal of Mechanical Design,1996,l18:62-67
[16] Ceglarek D, Shi J, Wu S. M. A knowledge-based diagnosis approach for the launch of the auto-body assembly process[J]. ASME Journal of Engineering forIndustry,1994,116(4):491-499
[17] Ceglarek D, Hu S. J. Fixture failure diagnosis for auto-body assembly using pattern recognition[J]. Journal of Engineering for Industry,1996,l18:55-66
[18] Daniel Y, Fong T, Lawless J. F. The analysis of process variation tranmission with multivariate measurements[J]. Statistica Sinica,1998,46(8):151-164
[19] Lawless J. F, Mackay R. J, Robinson J A. Analysis of variation transmission in manufacturing processes-part I[J]. Journal of Quality Technology,1999,31(2):131–142
[20] Mantripragada. R, Whitney D. E. Modeling and controlling variation propagation in mechanical assemblies using state transition models[J]. IEEE Transactions On Robotics AndAutomation,1999,15(1):124-140
[21] Lee Don J, Thornton Anna C, The identification and use of key characteristics in the product development process[J]. Proceedings of The 1996 ASME Design Engineering Technical Conferencesand Computers in Engineering Conference,August 18-22,1996,Irvine,California
[22] Thornton A. C, Quantitative selection of variation reduction plans[J]. Joumal of Mechanical Design,2000,122:185-193
[23]林忠钦,胡敏,来新民等.轿车白车身点焊装配过程有限元分析[J].焊接学报,2001,22(1):36-40
[24]杜世昌,奚立峰,潘尔顺.串并联混合式多阶段制造系统产品质量建模与控制[J].计算机集成制造系统,2006,12(7):1068.1073
[25]赵家黎,郭伟,牛占文等.基于误差流理论的多工位装配过程质量稳定性[J].机械工程学报,2006,42(11):88-92
[26] Ran Jin, Jing Li, Jianjun Shi. Quality prediction and control in rolling processes using logistic regression[J]. Transactions of NAMRI/SME,2007,vol.35,pp.113-120
[27]吴少雄,徐伟.基于规则的统计质量控制专家系统构建[J] .福建电脑,2005,11:104105
[28]胡兴才.基于小批量的统计过程控制研究与系统开发[D].南京:南京航空航天大学机电学院,2006,1-4
[29]杨鸿鹏,林志航.基于集成诊断模型加工质量的智能诊断系统研究[J].西安交通大学学报,1997,31(9):23.29
[30]张琳娜.加工误差及其预报建模研究[J].计量学报,1998,19(3):183,189
[31]曲兴华等.制造质量控制溯源技术研究的新进展[J].中国机械工程,1999,10(9):93-101
[32] L. P. Khoo, C. L. Ang, J. Zhang. A fuzzy-based genetic approach to the diagnosis of manufacturing systems[J]. Ttansaction of the ASME, Journal of Engineering for industry,1999,5(2):1014-1021
[33] [王波.机械加工偏差的神经网络预测方法[J].华东船舶工业学院学报,1997,12:44.48
[34]陈康宁,林志航,杨鸿鹏.基于神经网络和模糊逻辑的加工误差源诊断系统[J].西安交通大学学报,1995,29(7):60-65
[35]郑唯唯,安会刚,杜涛.过程质量控制的BP神经网络预测方法研究[J].数字设计与数字制造,2007,(9):8.10
[36]陈立周.稳健设计[M].北京:机械工业出版社,2000
[37]奚立峰,杜世昌.多工序制造过程的误差分析方法与应用[J].学术与创新,2006,42(11):35-38
[38]戴敏.多工序制造过程质量分析方法与信息集成技术研究[D].南京:东南大学,2005:11
[39]廖永平.机械工业企业质量管理[M].北京:机械工业出版社,1987
[40]王福保,李炳钊.概率论及数理统计[M].上海:同济大学出版社,1994
[41] Richard B.Chase等著,宋国防等译.生产与运作管理制造与服务,北京:机械工业出版社,1999,192-204
[42]廖春良,陈敬东,林筠.现代制造企业竞争重点分析[J].生产力研究,2004,135(3):129-130
[43]张公绪,孙静.现代质量控制与诊断工程[M].北京:经济科学出版社,1999
[44] Francisco Aparisi. Sampling Plans for Multivariate T~2 Control Chart[J], Quality Engineering, 1997-98, 10(1): 141-147
[45]蔡自兴.机器人学[M].北京:清华大学出版社,2000
[46]杜世昌.多源多工序加工系统偏差流建模、诊断和控制系统研究[D].上海:上海交通大学,2008:6
[47]龚德恩.离散控制系统理论引论[M].北京:中国铁道工业出版社,2004
[48]肖扬.动态系统分析[M].北京:北方交通大学出版社,2002
[49] Chaipradabgiat, Thavanrath, Jin, et al. Optimal fixture locator adjustment strategies for multi-station assembly processes[J]. IIE Transactions,2009,41:9,843-852
[50]周世学.机械制造工艺与夹具[M].北京:北京理工大学出版社,2006
[51]汤湘中.机床夹具设计[M].北京:国防工业出版社,1988
[52]吴文,张伟社.基于制造一质量损失成本的公差优化分配法[J].长安大学学报,2005,25(3):89-93