## 1 Introduction  
With the advancement of modern precision optical fabrication technologies, freeform optical components can be manufactured with a sufficiently high accuracy [1; 2]. Under this condition, a spherical surface is not anymore the only choice in current optical design. Due to their enlarged degrees of freedom and strong possibilities of aberration correction, optical freeform surfaces are increasingly used in different fields of application, including vehicle lighting [3; 4] or ophthalmic applications [5; 6; 7; 8] as well as beam expanders [9]. From the geometrical viewpoint, an optical freeform surface has non-rotationally symmetric features, while from the aspect of fabrication and design, an optical freeform surface is regarded as an optical surface that leverages a third independent axis during the fabrication process to form the optical surface with as-designed non-symmetric features [10]. Both viewpoints reveal the basic feature of the non-rotational symmetry of optical freeform surfaces, which is a challenge for the optical community. Surface shapes of freeform optics range from weak deviations from spherical surface to surface shapes without any symmetries [10], e.g., Alvarez-optics [11] or optics using mutual rotation of two helically formed surfaces for tuning of the focal length [12; 13; 14; 15; 16; 17; 18; 19]. Since deviations in position and shape of freeform surfaces cannot be expressed by traditional classification of rotational symmetric surfaces, the classical tolerancing procedures cannot be used in designing and manufacturing freeform optics [20], hence a performance estimation of real manufactured optical subsystems is not possible using the conventional approach of a tolerance analysis [21]. Standardization bodies address these problems by adapting the existing standards to freeform optics [22]. In [23], the option to use a fit of the surface form deviation to determine surface form errors of real manufactured surfaces is explicitly mentioned. Quality of optical surfaces can be evaluated and characterized using a variety of measures: Root mean square (RMS) errors as well as peak to valley (PV) errors are used to describe low-spatial frequency (LSF) errors, power-spectra density analysis can be used to analyze mid-spatial frequency (MSF) errors like spokes or ripples [24; 25]. Based on these figures the manufacturing accuracy can be characterized but no conclusions can be drawn regarding the optical performance in the case where freeform optics are used in a manufactured subsystem. To be able to use optical simulation for performance prediction of a manufactured system, the optical simulation model has to be enhanced by means of measurement data of the manufactured freeform surfaces [26; 27]. In addition, the performance prediction based on a model enhancement by means of metrology data can be used to optimize manufacturing parameters. In particular, this might be useful to improve the performance of freeform optics designed-for-manufacture by low-cost mass fabrication methods such as replication technologies (like \(\upmu\)IM) [28]. As a result, mass fabrication methods can compete with highly precise and more expensive single-part manufacturing processes, such as ultraprecision diamond machining. We propose the use of measured surface data of fabricated freeform optics in the modeling environment to make the modeling approach as accurate as possible. Due to the non-symmetric shape of optical freeform surfaces, the manufacturing tolerances are usually not isotropic as it is assumed for spherical optics. For this reason, the analyzation of the measured surface data of the real, manufactured optics is of great interest. This approach allows predicting the optical performance of the real manufactured freeform surfaces. In this paper, a method is demonstrated to use metrology data to enhance the model to be able to predict the optical performance of the manufactured system. The article is organized as follows: Section 2 describes the manufacture of the freeform optics by \(\upmu\)IM.