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As a final evaluation specification, optical performance is important for applications of optical surfaces. However, the traditional evaluation criteria in manufacturing have been the form error and surface roughness, which are compensated to control optical performance indirectly. Previous studies have found that optical performance can differ significantly despite a similar value of form error due to different underlying error distributions. This paper, therefore, proposes a novel approach to directly achieve compensation of optical performance. Manufacturing and optical performance are linked by their primary performance parameters, machining errors and wavefront aberration, respectively. The relationship between these parameters is obtained according to an optical performance evaluation model established using optical ray tracing. The evaluation criterion for manufacturing can, therefore, be linked to wavefront aberration, which can be measured and then compensated after fabrication by an optical performance improvement model. Our experimental results demonstrate the effectiveness of the proposed method, which provides an innovative assistance to directly improve the optical performance and machining accuracy of optical mirrors.

Engineering parts usually deviate from their intended shapes during their manufacturing due to the inaccuracies of machine tools, deformation of various elements of machine tool, cutting tools and workpiece. Resulting geometric errors affect the functionality and assembly of the parts significantly. This demands a reliable strategy to accurately assess the errors during the final part quality inspection. Among all the geometric features, circular feature is very common on the majority of the engineering parts. Hence, the measurement and evaluation of circularity with a high degree of accuracy are of utmost importance. In the present work, a hybrid approach is proposed to accurately evaluate the circularity error. This approach comprises a least squares method (LSM) and a novel probabilistic global search Lausanne (PGSL) technique. The LSM is used to reduce the search space initially. Within the reduced search space, the PGSL performs efficient, fine and global search. In the process of establishing minimum zone circles to the measured data of the circular features, the proposed approach dynamically updates the probability distribution function of the circularity parameters continuously. The update procedure ensures that the probability of moving towards the potential optimal solutions is increased. The algorithm has been tested using several benchmark datasets for its generalization capability and robustness. The proposed strategy is found to be efficient in yielding accurate results. Therefore, the algorithm can be implemented in computer-aided circularity measuring instruments in order to minimize acceptance of bad parts and rejection of good parts.

This paper presents a flexible model for estimating the form error in three-axis ball-end milling of sculptured surface with z-level contouring tool path. At an interval of feed per tooth, the whole process of sculptured surface machining is treated as a combination of sequential small inclined surface milling. For ball-end milling of the inclined surface with z-level contouring tool path, at surface generation position, an analytical model is proposed to identify the feedback effect of tool deflection on cutting edge engagement. The deflection-dependent cutting edge engagement is determined by using an iterative procedure. And ultimately, the form error is obtained from the balanced tool deflection and associated surface inclination angle. In a validation experiment, the estimated form errors are compared with both the measurements and the predictions of a rigid model. It is shown that the proposed flexible model gives significant better predictions of the form error than rigid model. Good agreement between the predicted and measured form errors is demonstrated for the ball-end milling of sculptured surface with z-level contouring tool path.

An accurate spiral tool path generation method of ultraprecision three-axis turning free form surface is proposed based on symbolic computation in this paper. Many analytic optical free form surfaces often need to be machined to submicron in form error, such as optical nonaxisymmetric aspheric surfaces, but current mainstream CAM systems usually use nonuniform rational basis spline (NURBS) to describe the designed surface and generate tool path. If we want to use these systems, the analytical optical surfaces must be approximated using NURBS surfaces, but it will introduce approximation error and may be difficult to achieve the approximation error less than submicron. More importantly, there is no effective tool path generation method for the special three-axis turning machine tool in current mainstream CAM systems. In this context, we propose to calculate the tool path directly from these analytic surfaces by using symbolic math. The proposed method can be used to generate accurate spiral tool paths for zero/negative/positive rake angle in a unified way. Finally, several examples are given to prove its effectiveness.

Due to inherent variability in even the so-called “high-precision” machines, the need for accurate, quick and economical inspection of tolerances of machined features has become very important. Coordinate measuring machines (CMMs) are very popular in industry for inspection of components. In addition to hardware capabilities, some of the critical factors that affect the accuracy and precision of inspection using CMMs have been identified as sample size, sampling technique and form evaluation method. Selecting an optimal inspection plan for the CMM is vital to improve the quality of measurements while simultaneously minimizing inspection costs and time. The motivation behind this paper is to provide the user flexibility and control in choosing an optimal inspection plan for evaluation of form error in cylindrical features according to his/her specific needs in a practical manufacturing scenario. In view of this objective, a two-way relationship between the inspection strategy used and inspection performance metrics achieved has been established using multiple regression. The forward model is a plan evaluator that computes numerical estimates of the expected accuracy and precision for different inspection plans. The reverse model is a strategy designer that recommends the most economical inspection plan that can meet the acceptable quality criteria considering the user’s constraints and available resources. Both the models have been incorporated into a user-friendly inspection advisor with a graphical interface.