Assembly quality evaluation for linear axis of machine tool using data-driven modeling approach
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Assembly quality evaluation for linear axis of machine tool using data-driven modeling approach Yang Hui1,2,3
· Xuesong Mei1,2,3 · Gedong Jiang1,2,3 · Fei Zhao1,2,3 · Ziwei Ma3 · Tao Tao1,2,3
Received: 25 May 2020 / Accepted: 12 September 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract During the batch assembly analysis of linear axis of machine tool, assembly quality evaluation is crucial to reduce assembly quality fluctuations and improve efficiency. This study presented a data-driven modeling approach for evaluating assembly quality of linear axis based on normalized mutual information and random sampling with replacement (NMI-RSWR) variable selection method, synthetic minority over-sampling technique (SMOTE), and genetic algorithm (GA)-optimized multi-class support vector machine (SVM). First, a variable selection method named NMI-RSWR was proposed to select key assembly parameters which affected assembly quality of linear axis. Then, a hybrid method based on SMOTE and GA-optimized multi-class SVM was presented to construct assembly quality evaluation model. In this method, Class imbalance problem was solved by using SMOTE, and parameters optimization problem was solved by using GA. Finally, the assembly-related data from the batch assembly of x-axis of a three-axis vertical machining center were collected to validate the proposed method. The results indicate that the proposed NMI-RSWR approach has capacity for selecting the highly related assembly parameters with assembly quality of linear axis, and the proposed data-driven modeling approach is effective for assembly quality evaluation of linear axis. Keywords Assembly quality evaluation · Linear axis of machine tool · Data-driven · Variable selection · SMOTE · GA-optimized multi-class SVM
Introduction The assembly of linear axis of machine tool is a complex multi-stage manufacturing process, which involves a series of adjustments of relative position of parts to keep the final assembly quality at an acceptable level (Guo et al. 2016; Li et al. 2014). However, the implementation of each adjustment process may generate different impact on the assembly quality of linear axis, and then it leads to fluctuations of the final assembly quality. In order to improve assembly quality consistency of linear axis and enhance assembly efficiency,
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Gedong Jiang [email protected]
1
State Key Laboratory for Manufacturing Systems Engineering, Xi’an Jiaotong University, Xi’an 710054, China
2
Shaanxi Key Laboratory of Intelligent Robots, Xi’an Jiaotong University, Xi’an 710049, China
3
School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an 710049, China
the research on evaluation of assembly quality of linear axis must be carried out. Till data, many theoretical modeling methods have been developed to deal with the assembly quality evaluation problem of linear axis (Du et al. 2018; Ma et al. 2016; He et al. 2017; Zhou et al. 2018; Sun et al. 2018; Kim et al. 2014; Rahmani and Bleicher 2016; Majda 2012; Zhong et a
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