An Universal Modeling Method for Enhancing the Volumetric Accuracy of CNC Machine Tools

Volumetric error modeling method is an important te ch nique for enhancement the accuracy of CNC machine tools by error compensation. I n the research field, the main question is how to find an universal kinematics m odeling method for different kinds of NC machine tools. Multi-body system theor y is always used to solve the dynamics problem of complex physical system. But t ill now, the error factors that always exist in practice system is still not con sidered. In this paper, the accuracy kinematics of MBS (multi-body system) are developed by adding the movement error items and the positioning error items for every couple of adjacent bodies. After make an analysis for different kinds of NC machine tools we can find that NC machine tools can be looked as a kind of sp ecial MBS. It’s main construction only contains two movement branch. the one is from base part to workpiece and the other is from base part to cutter. So an u niversal volumetric error modeling method and the error analysis method for NC m achine tools can be built in this paper based on MBS theory. The essential condi tion for precision machining is derived through mathematics equations and the co ncept of ICCP (inverse changed cutter path ) and ICNI (inverse changed NC instru ction ) are presented in this paper. The numerical solution methods for ICCP and ICNI are also given in this paper which can be directly used to enhance the mac hining accuracy of NC machine tools. In order to verifying the above works, the double frequency laser interface detecting instrument of RENISHAW is used to mea sure the error parameters of the MAKINO 3-axis NC machine tools and the softwar es are developed using C++ developing language to simulate the cutte r trail under different kind conditions in the computer. Latterly the standard w ork parts are selected to be machined on the MAKINO 3-axis NC machine tools bef ore and after use the above mentioned error compensation method respectively. Th e simulation and experiment results show that the volumetric error modeling meth od is effective and the machining accuracy of CNC machine tools can be improved more than 60% after using the compensation method presented in this paper.

Bayesian zero-failure reliability modeling and assessment method for multiple numerical control(NC) machine tools

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.

YKJ3180H Economy NC Gear Hobbing Machine

The YKJ3180H Economy NC GearHobbing Machine is a new variety,developed recently by the ChongqingMachine Tools Works to meet clients’demands. Its most prominent feature is its highproduction efficiency ( able to complete awork cycle automatically), high processingprecision (Grade 7 or higher according to theGB 10095) and its cost competitiveness. This product is used in the machinetool and machinery industries at automobiles,tractors, gears and gear box factories. It canbe used for processing spur gears and helicalgears, automatic radial feed wormwheels,tapered gears and crowning gears; so it isespecially applicable in factories usingcrowning gear couplings, such as metallurgy,mining, lifting transport and the chemicalmachinery.

A review of recent advances in machining techniques of complex surfaces

Complex surfaces are widely used in aerospace,energy,and national defense industries.As one of the major means of manufacturing such as complex surfaces,the multi-axis numerical control(NC)machining technique makes much contribution.When the size of complex surfaces is large or the machining space is narrow,the multi-axis NC machining may not be a good choice because of its high cost and low dexterity.Robotic machining is a beneficial supplement to the NC machining.Since it has the advantages of large operating space,good dexterity,and easy to realize parallel machining,it is a promising technique to enhance the capability of traditional NC machining.However,whether it is the multi-axis NC machining or the robotic machining,owing to the complex geometric properties and strict machining requirements,high-efficiency and high-accuracy machining of complex surfaces has always been a great challenge and remains a cutting-edge problem in the current manufacturing field.In this paper,by surveying the machining of complex parts and large complex surfaces,the theory and technology of high-efficiency and high-accuracy machining of complex surfaces are reviewed thoroughly.Then,a series of typical applications are introduced to show the state-of-the-art on the machining of complex surfaces,especially the recently developed industrial software and equipment.Finally,the summary and prospect of the machining of complex surfaces are addressed.To the best of our knowledge,this may be the first attempt to systematically review the machining of complex surfaces by the multiaxis NC and robotic machining techniques,in order to promote the further research in related fields.

Identification of the key thermal points on machine tools by grouping and optimizing variables

The grouping and optimization approach to identify the key thermal points on machine tools is studied.To solve the difficulty in grouping because of the high correlated variables from distinct groups,the variables grouping technique is improved.Temperature variables are sorted according to their relativities with the thermal errors.The representative temperature variables are determined by analyzing the variable correlation in sort order and removing the other variables in the same group.Considering the diverse effect of importing the different variables on thermal error model,the method of variable combination optimization is improved.Regression models made up of different combination of representative temperature variables are evaluated by the index of both the determined coefficient and the average residual squares to select the combination of the temperature variables.For the machine tools with complicated structures which need more initial temperature measuring points the improvement is demanded.The improved approach is applied to a precision horizontal machining center to identify the key thermal points.Experimental results show that the proposed approach is capable of avoiding the high correlation among the different groups' variables,effectively reducing the number of the key thermal points without depressing the prediction accuracy of the thermal error model for machine tools.

Immune Clone Maximum Likelihood Estimation of Improved Non-homogeneous Poisson Process Model Parameters

Aiming at the solving problem of improved nonhomogeneous Poisson process( NHPP) model in engineering application,the immune clone maximum likelihood estimation( MLE)method for solving model parameters was proposed. The minimum negative log-likelihood function was used as the objective function to optimize instead of using iterative method to solve complex system of equations,and the problem of parameter estimation of improved NHPP model was solved by immune clone algorithm. And the interval estimation of reliability indices was given by using fisher information matrix method and delta method. An example of failure truncated data from multiple numerical control( NC) machine tools was taken to prove the method. and the results show that the algorithm has a higher convergence rate and computational accuracy, which demonstrates the feasibility of the method.

Carbon Emission Modeling and Analysis in Manufacturing Process for Numerical Control Machine Tools

Reducing carbon emissions( CEs) is the urgent demand all over the world. In order to realize the low-carbon numerical control( NC) machining, the evaluation model of a part's manufacturing carbon emission with NC machine tools was built by considering the influences of the cutting tool geometrical parameters.The manufacturing CEs were produced by electric power,cutting tools,and cutting fluid consumed in manufacturing process. The parameters of cutting tools affected not only the CEs,but also the machining quality. Then the actual constraint models of the machine performance,machining quality were given in order to optimize the cutting parameters and achieve the low-CEs. Finally,a case was given to analyze the influences of the cutting tool angles on the manufacturing CEs. The results show that the CEs decrease as the rake angle and edge angle increase under the constraints of the machine specifications and machining quality.