ABC-polishing

Abstract

In the past, steadily increasing demands on the imaging properties of optics have led more and more precise spherical apertures. For a long time, these optical components have been produced in a satisfying quality using classic polishing methods such as pitch polishing. The advance of computer-controlled subaperture (SA) polishing techniques improved the accuracy of spheres. However, this new machine technology also made it possible to produce new lens geometries, such as aspheres. In contrast to classic polishing methods, the high determinism of SA polishing allows a very specific correction of the surface defect. The methods of magneto-rheological finishing (MRF) [1], [2] and ion beam figuring (IBF) [3], [4] stand out in particular because of the achievable shape accuracy. However, this leads to the fact that a principle of manufacturing "As exact as possible, as precise as necessary" [5] is often ignored. The optical surfaces often produced with unnecessary precision, result at least in increased processing times. The increasing interconnection of the production machines and the linking with databases already enables a consistent database to be established. It is possible to store measurements, process characteristics or tolerances for the individual production steps in a structured way. The difficulty, however, lies in the reasonable evaluation of the measurement data. This is where this publication comes in. The smart evaluation of the measurement data with the widespread Zernike polynomials should result in a classification, depending on the required manufacturing tolerance. In combination with the so-called ABC analysis, all surface defects can be categorized. In this way, an analytic breakdown of a - initially confusing - overall problem is made. With the aid of cost functions [6] an evaluation and consequently a deduction of actions is made possible. Thus, for example, the isolated processing of rotationally symmetrical errors in spiral mode, setup times and machining times can be reduced while avoiding mid spatial frequency errors (MSFE) at the same time.