Although Markov chain Monte Carlo（MCMC） algorithms are accurate, many factors may cause instability when they are utilized in reliability analysis; such instability makes these algorithms unsuitable for widespread e...Although Markov chain Monte Carlo（MCMC） algorithms are accurate, many factors may cause instability when they are utilized in reliability analysis; such instability makes these algorithms unsuitable for widespread engineering applications. Thus, a reliability modeling and assessment solution aimed at small-sample data of numerical control（NC） machine tools is proposed on the basis of Bayes theories. An expert-judgment process of fusing multi-source prior information is developed to obtain the Weibull parameters＇ prior distributions and reduce the subjective bias of usual expert-judgment methods. The grid approximation method is applied to two-parameter Weibull distribution to derive the formulas for the parameters＇ posterior distributions and solve the calculation difficulty of high-dimensional integration. The method is then applied to the real data of a type of NC machine tool to implement a reliability assessment and obtain the mean time between failures（MTBF）. The relative error of the proposed method is 5.8020×10-4 compared with the MTBF obtained by the MCMC algorithm. This result indicates that the proposed method is as accurate as MCMC. The newly developed solution for reliability modeling and assessment of NC machine tools under small-sample data is easy, practical, and highly suitable for widespread application in the engineering field; in addition, the solution does not reduce accuracy.展开更多
A new problem that classical statistical methods are incapable of solving is reliability modeling and assessment when multiple numerical control machine tools(NCMTs) reveal zero failures after a reliability test. Thus...A new problem that classical statistical methods are incapable of solving is reliability modeling and assessment when multiple numerical control machine tools(NCMTs) reveal zero failures after a reliability test. Thus, the zero-failure data form and corresponding Bayesian model are developed to solve the zero-failure problem of NCMTs, for which no previous suitable statistical model has been developed. An expert-judgment process that incorporates prior information is presented to solve the difficulty in obtaining reliable prior distributions of Weibull parameters. The equations for the posterior distribution of the parameter vector and the Markov chain Monte Carlo(MCMC) algorithm are derived to solve the difficulty of calculating high-dimensional integration and to obtain parameter estimators. The proposed method is applied to a real case; a corresponding programming code and trick are developed to implement an MCMC simulation in Win BUGS, and a mean time between failures(MTBF) of 1057.9 h is obtained. Given its ability to combine expert judgment, prior information, and data, the proposed reliability modeling and assessment method under the zero failure of NCMTs is validated.展开更多
It is difficult to collect the prior information for small-sample machinery products when their reliability is assessed by using Bayes method. In this study, an improved Bayes method with gradient reliability(GR) resu...It is difficult to collect the prior information for small-sample machinery products when their reliability is assessed by using Bayes method. In this study, an improved Bayes method with gradient reliability(GR) results as prior information was proposed to solve the problem. A certain type of heavy NC boring and milling machine was considered as the research subject, and its reliability model was established on the basis of its functional and structural characteristics and working principle. According to the stress-intensity interference theory and the reliability model theory, the GR results of the host machine and its key components were obtained. Then the GR results were deemed as prior information to estimate the probabilistic reliability(PR) of the spindle box, the column and the host machine in the present method. The comparative studies demonstrated that the improved Bayes method was applicable in the reliability assessment of heavy NC machine tools.展开更多
Virtual dynamic optimization design can avoid the repeated process from de-sign to trial-manufacture and test.The designer can analyze and optimize the productstructures in virtual visualization environment.The design...Virtual dynamic optimization design can avoid the repeated process from de-sign to trial-manufacture and test.The designer can analyze and optimize the productstructures in virtual visualization environment.The design cycle is shortened and the costis reduced.The paper analyzed the peculiarity of virtual optimization design,and put for-wards the thought and flow to implement virtual optimization design.The example to opti-mize the internal grinder was studied via establishing precise finite element model,modi-fying the layout of Stiffened Plates and designing parameters of the worktable,and usingthe technology of modal frequency revision and the technology of multiple tuned damper.The result of optimization design compared the new grinder with the original grinder showsthat the entire machine's first orders natural frequency is enhanced by 17%,and the re-sponse displacement of the grinding-head has dropped by 28% under the first order natu-ral frequency and by 41% under second order natural frequency.Finally,the dynamic per-formance of the internal grinder was optimized.展开更多
Product system design is a mature concept in western developed countries. It has been applied in war industry during the last century. However,up until now,functional combination is still the main method for product s...Product system design is a mature concept in western developed countries. It has been applied in war industry during the last century. However,up until now,functional combination is still the main method for product system de-sign in China. Therefore,in terms of a concept of product generation and product interaction we are in a weak position compared with the requirements of global markets. Today,the idea of serial product design has attracted much attention in the design field and the definition of product generation as well as its parameters has already become the standard in serial product designs. Although the design of a large-scale NC machine tool is complicated,it can be further optimized by the precise exercise of object design by placing the concept of platform establishment firmly into serial product de-sign. The essence of a serial product design has been demonstrated by the design process of a large-scale NC machine tool.展开更多
In order to deal with the issue of huge computational cost very well in direct numerical simulation, the traditional response surface method (RSM) as a classical regression algorithm is used to approximate a functiona...In order to deal with the issue of huge computational cost very well in direct numerical simulation, the traditional response surface method (RSM) as a classical regression algorithm is used to approximate a functional relationship between the state variable and basic variables in reliability design. The algorithm has treated successfully some problems of implicit performance function in reliability analysis. However, its theoretical basis of empirical risk minimization narrows its range of applications for...展开更多
This paper reviews several recently-developed techniques for the minimum-cost optimal design of water-retaining structures (WRSs), which integrate the effects of seepage. These include the incorporation of uncertainty...This paper reviews several recently-developed techniques for the minimum-cost optimal design of water-retaining structures (WRSs), which integrate the effects of seepage. These include the incorporation of uncertainty in heterogeneous soil parameter estimates and quantification of reliability. This review is limited to methods based on coupled simulation-optimization (S-O) models. In this context, the design of WRSs is mainly affected by hydraulic design variables such as seepage quantities, which are difficult to determine from closed-form solutions or approximation theories. An S-O model is built by integrating numerical seepage modeling responses to an optimization algorithm based on efficient surrogate models. The surrogate models (meta-models) are trained on simulated data obtained from finite element numerical code solutions. The proposed methodology is applied using several machine learning techniques and optimization solvers to optimize the design of WRS by incorporating different design variables and boundary conditions. Additionally, the effects of several scenarios of flow domain hydraulic conductivity are integrated into the S-O model. Also, reliability based optimum design concepts are incorporated in the S-O model to quantify uncertainty in seepage quantities due to uncertainty in hydraulic conductivity estimates. We can conclude that the S-O model can efficiently optimize WRS designs. The ANN, SVM, and GPR machine learning technique-based surrogate models are efficiently and expeditiously incorporated into the S-O models to imitate the numerical responses of simulations of various problems.展开更多
The fundamental ideas on building the collaborative design platform of virtual visualization for NC machine tools are introduced.The platform is based on the globally shared product model conforming to the STEP Standa...The fundamental ideas on building the collaborative design platform of virtual visualization for NC machine tools are introduced.The platform is based on the globally shared product model conforming to the STEP Standard,and used PDM system to integrate and encapsulate CAD/CAE and other application software for the product development.The platform also integrated the expert system of NC machine tools design,analysis and estimation.This expert system utilized fuzzy estimation principle to evaluate the design and simulation analysis results and make decisions.The platform provides the collaborative intelligent environment for the design of virtual NC machine tools prototype aiming at integrated product design team.It also supports the customized development of NC machine tools.展开更多
The key techniques of modular design of heavy duty NC mathine tools are described. Amodule definition modelfor modular design and manufacturing of heavy duty NC machine tools isbulit and the essential composition of t...The key techniques of modular design of heavy duty NC mathine tools are described. Amodule definition modelfor modular design and manufacturing of heavy duty NC machine tools isbulit and the essential composition of the module definition model (MDM) is discussed in detail. Itis composed of two models: the part definition model (PDM) and the module assembly model(MAM). The PDM and MAM are built and their structures are given. Using object-oriented know-ledge representation and based on these models, an intelligent support system of modular design forheavy duty NC machine tools is developed and implemented This system has been applied to thepractical use of Wuhan Heavy Duty Machine Tool Works展开更多
基金Supported by Research on Reliability Assessment and Test Methods of Heavy Machine Tools,China(State Key Science&Technology Project High-grade NC Machine Tools and Basic Manufacturing Equipment,Grant No.2014ZX04014-011)Reliability Modeling of Machining Centers Considering the Cutting Loads,China(Science&Technology Development Plan for Jilin Province,Grant No.3D513S292414)Graduate Innovation Fund of Jilin University,China(Grant No.2014053)
文摘Although Markov chain Monte Carlo（MCMC） algorithms are accurate, many factors may cause instability when they are utilized in reliability analysis; such instability makes these algorithms unsuitable for widespread engineering applications. Thus, a reliability modeling and assessment solution aimed at small-sample data of numerical control（NC） machine tools is proposed on the basis of Bayes theories. An expert-judgment process of fusing multi-source prior information is developed to obtain the Weibull parameters＇ prior distributions and reduce the subjective bias of usual expert-judgment methods. The grid approximation method is applied to two-parameter Weibull distribution to derive the formulas for the parameters＇ posterior distributions and solve the calculation difficulty of high-dimensional integration. The method is then applied to the real data of a type of NC machine tool to implement a reliability assessment and obtain the mean time between failures（MTBF）. The relative error of the proposed method is 5.8020×10-4 compared with the MTBF obtained by the MCMC algorithm. This result indicates that the proposed method is as accurate as MCMC. The newly developed solution for reliability modeling and assessment of NC machine tools under small-sample data is easy, practical, and highly suitable for widespread application in the engineering field; in addition, the solution does not reduce accuracy.
基金Project(2014ZX04014-011)supported by State Key Science&Technology Program of ChinaProject([2016]414)supported by the 13th Five-year Program of Education Department of Jilin Province,China
文摘A new problem that classical statistical methods are incapable of solving is reliability modeling and assessment when multiple numerical control machine tools(NCMTs) reveal zero failures after a reliability test. Thus, the zero-failure data form and corresponding Bayesian model are developed to solve the zero-failure problem of NCMTs, for which no previous suitable statistical model has been developed. An expert-judgment process that incorporates prior information is presented to solve the difficulty in obtaining reliable prior distributions of Weibull parameters. The equations for the posterior distribution of the parameter vector and the Markov chain Monte Carlo(MCMC) algorithm are derived to solve the difficulty of calculating high-dimensional integration and to obtain parameter estimators. The proposed method is applied to a real case; a corresponding programming code and trick are developed to implement an MCMC simulation in Win BUGS, and a mean time between failures(MTBF) of 1057.9 h is obtained. Given its ability to combine expert judgment, prior information, and data, the proposed reliability modeling and assessment method under the zero failure of NCMTs is validated.
基金Supported by the National Science and Technology Major Project of China(No.2009ZX04002-061)the National Science and Technology Support Program(No.2013BAF06B00)the Natural Science Foundation of Tianjin(No.13JCZDJC34000)
文摘It is difficult to collect the prior information for small-sample machinery products when their reliability is assessed by using Bayes method. In this study, an improved Bayes method with gradient reliability(GR) results as prior information was proposed to solve the problem. A certain type of heavy NC boring and milling machine was considered as the research subject, and its reliability model was established on the basis of its functional and structural characteristics and working principle. According to the stress-intensity interference theory and the reliability model theory, the GR results of the host machine and its key components were obtained. Then the GR results were deemed as prior information to estimate the probabilistic reliability(PR) of the spindle box, the column and the host machine in the present method. The comparative studies demonstrated that the improved Bayes method was applicable in the reliability assessment of heavy NC machine tools.
基金Supported by the National Natural Science Foundation of China(50375026)
文摘Virtual dynamic optimization design can avoid the repeated process from de-sign to trial-manufacture and test.The designer can analyze and optimize the productstructures in virtual visualization environment.The design cycle is shortened and the costis reduced.The paper analyzed the peculiarity of virtual optimization design,and put for-wards the thought and flow to implement virtual optimization design.The example to opti-mize the internal grinder was studied via establishing precise finite element model,modi-fying the layout of Stiffened Plates and designing parameters of the worktable,and usingthe technology of modal frequency revision and the technology of multiple tuned damper.The result of optimization design compared the new grinder with the original grinder showsthat the entire machine's first orders natural frequency is enhanced by 17%,and the re-sponse displacement of the grinding-head has dropped by 28% under the first order natu-ral frequency and by 41% under second order natural frequency.Finally,the dynamic per-formance of the internal grinder was optimized.
文摘Product system design is a mature concept in western developed countries. It has been applied in war industry during the last century. However,up until now,functional combination is still the main method for product system de-sign in China. Therefore,in terms of a concept of product generation and product interaction we are in a weak position compared with the requirements of global markets. Today,the idea of serial product design has attracted much attention in the design field and the definition of product generation as well as its parameters has already become the standard in serial product designs. Although the design of a large-scale NC machine tool is complicated,it can be further optimized by the precise exercise of object design by placing the concept of platform establishment firmly into serial product de-sign. The essence of a serial product design has been demonstrated by the design process of a large-scale NC machine tool.
基金National High-tech Research and Development Pro-gram (2006AA04Z405)
文摘In order to deal with the issue of huge computational cost very well in direct numerical simulation, the traditional response surface method (RSM) as a classical regression algorithm is used to approximate a functional relationship between the state variable and basic variables in reliability design. The algorithm has treated successfully some problems of implicit performance function in reliability analysis. However, its theoretical basis of empirical risk minimization narrows its range of applications for...
文摘This paper reviews several recently-developed techniques for the minimum-cost optimal design of water-retaining structures (WRSs), which integrate the effects of seepage. These include the incorporation of uncertainty in heterogeneous soil parameter estimates and quantification of reliability. This review is limited to methods based on coupled simulation-optimization (S-O) models. In this context, the design of WRSs is mainly affected by hydraulic design variables such as seepage quantities, which are difficult to determine from closed-form solutions or approximation theories. An S-O model is built by integrating numerical seepage modeling responses to an optimization algorithm based on efficient surrogate models. The surrogate models (meta-models) are trained on simulated data obtained from finite element numerical code solutions. The proposed methodology is applied using several machine learning techniques and optimization solvers to optimize the design of WRS by incorporating different design variables and boundary conditions. Additionally, the effects of several scenarios of flow domain hydraulic conductivity are integrated into the S-O model. Also, reliability based optimum design concepts are incorporated in the S-O model to quantify uncertainty in seepage quantities due to uncertainty in hydraulic conductivity estimates. We can conclude that the S-O model can efficiently optimize WRS designs. The ANN, SVM, and GPR machine learning technique-based surrogate models are efficiently and expeditiously incorporated into the S-O models to imitate the numerical responses of simulations of various problems.
基金Funded by National Natural Science foundation of China(50375026)
文摘The fundamental ideas on building the collaborative design platform of virtual visualization for NC machine tools are introduced.The platform is based on the globally shared product model conforming to the STEP Standard,and used PDM system to integrate and encapsulate CAD/CAE and other application software for the product development.The platform also integrated the expert system of NC machine tools design,analysis and estimation.This expert system utilized fuzzy estimation principle to evaluate the design and simulation analysis results and make decisions.The platform provides the collaborative intelligent environment for the design of virtual NC machine tools prototype aiming at integrated product design team.It also supports the customized development of NC machine tools.
文摘The key techniques of modular design of heavy duty NC mathine tools are described. Amodule definition modelfor modular design and manufacturing of heavy duty NC machine tools isbulit and the essential composition of the module definition model (MDM) is discussed in detail. Itis composed of two models: the part definition model (PDM) and the module assembly model(MAM). The PDM and MAM are built and their structures are given. Using object-oriented know-ledge representation and based on these models, an intelligent support system of modular design forheavy duty NC machine tools is developed and implemented This system has been applied to thepractical use of Wuhan Heavy Duty Machine Tool Works
