Research On Machining Accuracy Prediction And Compensation Technique For Five-Axis Milling Of Complex Parts

Machining accuracy is a key indicator to estimate whether the machined part is qualified or not. It plays an important role in metal cutting. In the modern manufacturing industry, there are more and more complex parts with curved surfaces. And therefore, five-axis NC milling is widely adopted and playing an important role in many industries such as aerospace, automobiles, ships, energy and so on. The machining error and productiveness of five-axis milling reflect a country’s level of CNC machining.In the NC machining process, there are lots of error factors making the actual tool pathes deviate from the given ones, and resulting in machining errors. In the traditional machining processes, the process planning is based on experiences and the "trial and error" method, which can ensure the machining accuracy of machined parts. However, this method is time-consuming and costly. If the machining accuracy can be predicted precisely, the trial cut can be replaced to shorten the production cycle and reduce the costs; then, the prediction results can be used to guide process optimization, maximize the use of the manufacturing resources as well as ensure the machining accuracy of the machined parts, consequently improve the production efficiency. Moreover, compensating the machining error according to the prediction result can improve the machining accuracy of machined parts, enhance the processing capacity of enterprises and reduce the equipment investment.To achieve above targets, based on analyzing and summarizing previous research works and achievements, and combining with the actual machining process, this thesis focus on the machining accuracy prediction and compensation technology for five-axis NC milling of complex parts. The main research works and results are as follows.(1) The machining error modeling method for five-axis machine tools was studied. On the basis of the theory of MBS kinematics, a general composite error model of five-axis NC machining including machine tool geometric error, workpiece locating error, tool geometric error and setup error was established. Taking cutting a distorted S-type specimen (referred to "S part" later) on a PM20five-axis NC milling machine for example, the validity of the composite error model was tested and verified.(2) The geometric error parameter measurement and identification method for the ranslational axes of five-axis milling machines was studied. The laser interferometer based "twelve-line" identification method, which was proposed by Su et al. come from National University of Defense Technology, was adopted on three five-axis milling machines:a PM20five-axis NC milling machine, a VMC650m five-axis machining center and a GMC820u five-axis milling machine.(3) The geometric error parameter measurement and identification method for the revolution axes of five-axis milling machines was studied. A ball-bar based geometric error parameter measurement and identifination method was proposed to independently identify the six geometric error parameters of each revolution axis by three times measurements in three directions respectively using a ball-bar. Using a Renishaw QC10ball-bar, the practicability of this method was validated by practical application on a VMC650m five-axis machine center.(4) The measurement and identification method of workpiece pose error was studied. For the "one plan and two pins" locating mode, a complete workpiece pose error measurement and prediction method was proposed. This method adds the measurement and calculation of fixture setup errors and locating plan tilt errors to the conventional design calculation where only the pin-hole fit are considered. An experiment was designed to test and verify the correctness of this method.(5) The maching accuracy prediction method was studied. On the basis of the error model, the normal error was obtained by projecting the spatial error onto the normal of the contour; then the parts is divided into several typical features according to its geometry, and the dimension errors and form errors of each feature were predicted respectively. Based on VS2010and Oracle10g, prototype software was developed. By cutting a "S part" on a GMC820u five-axis milling machine, the correctness and feasibility of this method were tested and verified.(6) The machining error compensation method was studied. Software error compensation method was adopted and an improved two-step compensation algorithm is proposed. The algorithm compensates the revolution axes firstly, and then compensates the ranslational axes, which makes the computing converges quickly. Considerling machine tool geometric error, prototype software was developed based on VC++6.0. Taking cutting a "S part" on a PM20five-axis milling machine and a cone part on a VMC650m five-axis machine center for example, the correctness and feasibility of this algorithm were tested and verified.Basd on above research works, a set of machining accuracy prediction and compensation scheme from error modeling, identification to prediction and compensation for five-axis NC milling method is formed. And a series of cases shows that the scheme and the key technologies are correct and feasible.