Sensitivity analysis of machining accuracy reliability considering partial correlation of geometric errors for Horizontal Machining Center

Abstract

With the increase in working time, the geometric errors of a Horizontal Machining Center (HMC) will also increase under load, temperature, and wear conditions, decreasing the machining accuracy. As HMC is a high-accuracy machine tool with a high nonlinear system, there is a complex coupling relationship between errors. Therefore, how to thoroughly evaluate the ability of a machine tool to maintain its machining accuracy with the extension of working time is an important way for HMC to control its machining quality. In this paper, this ability is defined as machining accuracy reliability, that is, under specified conditions, the machine tool can work normally to achieve the corresponding machining accuracy ability. To solve this problem, a new analysis method is proposed for evaluating machining accuracy reliability based on the nonlinear correlation between errors. The nonlinear relationship between machining accuracy and errors was determined using multibody modeling technology. The effect of interaction between errors on machining accuracy reliability was analyzed by introducing and calculating partial correlation coefficients. Finally, the method was validated using a four-axis machine tool.

Concurrent optimization of dimensions and tolerances on structures and mechanisms

“…Both experimental and optimization methods have been attempted for specific types of mechanisms such as robotic manipulators [105,106]. A related problem has also been addressed for machine tools through the statistical analysis of multibody models [107].…”

Enhancing machining accuracy reliability of multi-axis CNC Indexed by: machine tools using an advanced importance sampling method

“…Machining accuracy is critical to the quality and performance of machine tools and it is the first consideration of any manufacturer [20]. Machining accuracy reliability is the ability for machine tools can work normally to achieve the corresponding machining accuracy under specified conditions [14]. Its main influencing factors include geometric errors, thermal errors and cutting force errors, etc.…”

A Method for Mill Monitoring Based on Inter-insert Periodic Correlation Using Singular Value Decomposition (SVD)

“…The inserts will gradually show different degrees of wear from their similar initial state over the typical tool life curve stages, and the correlation between them will continuously decrease. A literature review shows that most current research emphasizes the correlation between the proposed indicator and the mechanical state [20][21][22], or compares the real-time signal with a known template [23][24][25]. As far as the authors know, periodic segmentation of signals for correlation analysis is innovative and original.…”