Prediction and compensation of machining geometric errors of five-axis machining centers with kinematic errors

Abstract

Abstract:Kinematic errors due to geometric inaccuracies in five-axis machining centers cause deviations in tool positions and orientation from commanded values, which consequently affect geometric accuracy of the machined surface. As is well known in the machine tool industry, machining of a cone frustum as specified in NAS979 standard is a widely accepted final perforance test for five-axis machining centers. A critical issue with this machining test is, however, that the influence of the machine's error sources on the geometric accuracy of the machined cone frustum is not fully understood by machine tool builders and thus it is difficult to find causes of machining errors. To address this issue, this paper presents a simulator of machining geometric errors in fiveaxis machining by considering the effect of kinematic errors on the three-dimensional interference of the tool and the workpiece. Kinematic errors of a five-axis machining center with tilting rotary table type are first identified by a DBB method. Using an error model of the machining center with identified kinematic errors and considering location and geometry of the workpiece, machining geometric error with respect to the nominal geometry of the workpiece is predicted and evaluated.In an aim to improve geometric accuracy of the machined surface, an error compensation for tool position and orientation is also presented. Finally, as an example, the machining of a cone frustum by using a straight end mill, as described in the standard NAS979, is considered in case studies to experimentally verify the prediction and the compensation of machining geometric errors in fiveaxis machining.

Thermal Error Compensation Method Based on Floyd Algorithm

“…Adjacency matrix (0) D stands for the distance between every two nodes, such as i w and j w . First, (1) D is calculated. One of all possible paths is figured out between i w and j w .…”

“…By comparison, the best path can be identified. The new iteration adjacency matrix (1) D is replaced the initial one. The elements in (1) D represent the better path every two points by one iteration.…”

“…As for machine tool, the machining accuracy is an important index to evaluate its performance and characteristics [1], and it is influenced by many factors. Among them, thermal errors account for about 40% of the total machining errors [2].…”

Modelling of Computer-Assisted Machine Tool Volumetric Verification Process

“…While systematic errors can be measured and modelled to reduce their influence using compensation methods, random errors are measured in order to avoid their influence but without compensating them [1][2][3]. The sources of errors can be classified in relation to their origin as dynamic effects [4], static load and motion control effects [5], thermal effects [6,7] and kinematic/geometric errors [8][9][10]. The combination of all these sources of error provides the machining accuracy of the machine tool.…”

Automatic planning for machine tool calibration: A case study

“…There has been great research effort into the classification of machine tool geometric errors (Bohez et al, 2007;Ramesh et al, 2000;Schwenke et al, 2008;Uddin et al, 2009;Wan et al, 2008;Srivastava et al, 1995;Seng Khim and Chin Keong, 2010) and there is a wealth of literature and guidance to aid with error measurement (ISO230, 1996(ISO230, , 2006a(ISO230, , 2007(ISO230, , 2006b), but there is an absence of literature indicating that effective strategies have been developed to improve machine tool calibration planning, aiming to significantly reduce machine down-time. This is surprising because it is still challenging for machine tool manufacturers, owners and calibration companies to determine the most efficient calibration plan because of the wealth of different machine configurations, available instrumentation, time and physical constraints.…”