Article
Engineering, Multidisciplinary
Yingzhi Zhang, Yutong Zhou, Fang Yang, Zhiqiong Wang, Mo Sun
Summary: To overcome the deviation caused by neglecting the dynamic nature of fault propagation in traditional methods, a new approach is proposed based on the maximum occurrence probability to identify the key fault propagation path. The occurrence probability is defined by dynamic importance, dynamic fault propagation probability, and fault rate. By analyzing the fault information of CNC machine tools that follow Weibull distribution, it is proven that the method is reasonable. The results show that the key fault propagation path of CNC machine tools changes with time, from electrical component (E) to mechanical component (M) before 1000 hours, and from auxiliary component (A) to mechanical component (M) after 1000 hours. This change should be considered in maintenance strategies and reliability analysis.
EKSPLOATACJA I NIEZAWODNOSC-MAINTENANCE AND RELIABILITY
(2023)
Article
Automation & Control Systems
Ruijuan Xue, Peisen Zhang, Zuguang Huang, Jinjiang Wang
Summary: This paper proposes a digital twin-driven fault diagnosis method for CNC machine tools, which establishes and validates a digital twin model and uses model data fusion method and decision tree algorithm to achieve fault diagnosis. Experimental results show that the proposed method can effectively diagnose the stiffness deterioration fault of CNC machine tools.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2022)
Article
Engineering, Industrial
Shoujin Huang, Ningyun Lu, Bin Jiang, Silvio Simani, Ronghua Li, Binda Huang, Jie Cao
Summary: Computer numerically controlled machine tools are crucial in the intelligent manufacturing industry, and unscheduled shutdowns can cause equipment damage and production loss. This paper proposes a novel fault propagation analysis method that accurately evaluates fault propagation coefficients of components in these machine tools. By building a quantitative causal diagram and using an inverse PageRank algorithm, the fault propagation risks of components are assessed, and the fault propagation path is identified. The method is validated on a computer numerically controlled machine tool, and the results match typical cascading events and expert judgment.
JOURNAL OF MANUFACTURING SYSTEMS
(2023)
Article
Engineering, Chemical
Seunghwan Jung, Minseok Kim, Baekcheon Kim, Jinyong Kim, Eunkyeong Kim, Jonggeun Kim, Hyeonuk Lee, Sungshin Kim
Summary: In manufacturing processes using CNC machines, machine tool failures can significantly degrade product quality and process efficiency. Existing fault detection methods using univariate signals have limitations in applying multivariate models. This study proposes a method combining empirical mode decomposition and auto-associative kernel regression to detect faults in machine tools. Experimental results demonstrate the successful detection of actual machine tool faults using this method.
Article
Engineering, Mechanical
Mohmad Iqbal, A. K. Madan
Summary: This paper proposes an intelligent vibration-based condition and fault diagnostic technique for identifying bearing faults in CNC machines. The proposed approach uses Hybrid Signal Decomposition for fault diagnosis and Principal Component Analysis for feature selection. The experimental results show that it outperforms traditional machine learning algorithms and has the potential to prevent unplanned and unnecessary device shutdowns.
JOURNAL OF VIBRATION ENGINEERING & TECHNOLOGIES
(2023)
Article
Automation & Control Systems
Yulong Li, Xiaogang Zhang, Yan Ran, Genbao Zhang
Summary: This paper investigated the early failures of CNC machine tools and proposed concepts of sudden early failures and progressive early failures, establishing corresponding reliability analysis models for each type. The study concluded that different product failures require targeted parameter models for analysis, and the proposed method demonstrates a certain level of applicability and correctness.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2021)
Article
Engineering, Multidisciplinary
Petr Blecha, Michal Holub, Tomas Marek, Robert Jankovych, Filip Misun, Jan Smolik, Martin Machalka
Summary: This paper examines the capability of touch probe measurements on CNC machine tools and evaluates the influence of the machine's geometric accuracy on the measurements.
Article
Computer Science, Artificial Intelligence
Mengrui Zhu, Yun Yang, Xiaobing Feng, Zhengchun Du, Jianguo Yang
Summary: This paper presents a novel thermal error modeling method based on random forest, which accurately predicts the thermal error of machine tools with high robustness. By evaluating the importance of temperature features and selecting key temperature points, the performance of the model is enhanced and the cost is reduced. The hysteresis effect between temperature and deformation is also taken into consideration.
JOURNAL OF INTELLIGENT MANUFACTURING
(2023)
Article
Engineering, Multidisciplinary
Hongxia Chen, Junfeng Zhang, Chuncheng Guo, Hongyue Li, Chenguang Li
Summary: This paper analyzes the fault correlation between CNC machine tool subsystems using decision laboratory analysis and the House of Reliability (HoR) methodology. The cognitive best worst method (CBWM) is used to comprehensively analyze maintenance information and hazard indicators. The HoR method is then employed to perform fault correlation fusion, resulting in comprehensive hazard analysis results. Comparing the fusion fault correlation with traditional hazard analysis, the proposed method identifies important subsystems and vulnerable machine tool parts. Overall, the hazard analysis results contribute to the safe and reliable operation and maintenance optimization of CNC machine tools.
QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL
(2023)
Article
Computer Science, Information Systems
Jinsong Liu, Dong Yu, Yi Hu, Haoyu Yu, Wuwei He, Lipeng Zhang
Summary: This paper explores a digital twin-driven interaction and cooperation framework to improve the accuracy of fault diagnosis by enabling the sharing of data, knowledge, and resource, and realizing the fusion of physical space and cyber space. A self-adaptation rescheduling method based on the MCTS algorithm is proposed to provide support for developing more efficient production planning under this framework. The effectiveness of the proposed framework is validated by experimental study, showing its guidance for enterprises in implementing CNCMT maintenance and production scheduling to meet high accuracy and reliability requirements.
Article
Engineering, Electrical & Electronic
Jozef Peterka, Marcel Kuruc, Vitalii Kolesnyk, Ivan Dehtiarov, Jana Moravcikova, Tomas Vopat, Peter Pokorny, Frantisek Jurina, Vladimir Simna
Summary: This new work investigated the potential impact of spindle heating on the precision of flat surface machining using ultrasonic precision machining. The research found significant differences in interface depth and stability between heated and non-heated spindles.
Article
Computer Science, Hardware & Architecture
Yiming He, Weiming Shen
Summary: This article proposes a novel method for cross-machine fault diagnosis of complex CNC spindle motors. By using a special tokenizer and Transformer architecture, the method is able to effectively diagnose faults. Experimental results validate the effectiveness of the proposed method and analyze the impact of structural hyperparameters on diagnosis performance.
IEEE TRANSACTIONS ON RELIABILITY
(2023)
Article
Engineering, Electrical & Electronic
Honghan Ye, Xinyuan Wei, Xindong Zhuang, Enming Miao
Summary: This paper proposes an improved robust thermal error prediction approach for CNC machine tools based on the adaptive LASSO and XGBoost algorithms. The approach selects temperature-sensitive variables and models thermal errors using the XGBoost algorithm, resulting in improved prediction accuracy and robustness. Experimental data demonstrates its superior performance compared to benchmark methods.
Article
Computer Science, Interdisciplinary Applications
Md Shafiullah, Khalid A. AlShumayri, Md. Shafiul Alam
Summary: This article presents a fault diagnosis approach for active distribution grids using signal processing techniques and machine learning tools. The approach combines the Hilbert-Huang transform and discrete wavelet transform as signal processing tools, while feedforward neural networks are used as machine learning tools. The proposed approach is tested on two different distribution feeders and shows effectiveness in detecting, classifying, and locating faults. The developed models also demonstrate independence in varying pre-fault conditions, fault angles, and fault resistance.
ADVANCES IN ENGINEERING SOFTWARE
(2022)
Article
Automation & Control Systems
Chuanjing Zhang, Huanlao Liu, Qunlong Zhou, Yulin Wang
Summary: An improved hybrid grey wolf optimization algorithm is proposed in this paper to optimize the geometric error modeling scheme of the support vector regression machine. The algorithm combines predicted and measured values of the geometric error to construct the fitness function, and introduces principles of particle swarm optimization and dimension learning-based hunting search strategies. The proposed method outperforms current error modeling methods in terms of precision and efficiency.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2023)
Article
Engineering, Multidisciplinary
Yingzhi Zhang, Liming Mu, Jialin Liu, Jintong Liu, Zhifu Tian, Yilong Zhang
JOURNAL OF THE CHINESE INSTITUTE OF ENGINEERS
(2020)
Article
Thermodynamics
Rui Zheng, Yingzhi Zhang, Liudong Gu
INTERNATIONAL JOURNAL OF GREEN ENERGY
(2020)
Article
Engineering, Multidisciplinary
Yingzhi Zhang, Shubin Liang, Jialin Liu, Peilong Cao, Lan Luan
Summary: This article discusses the impact of failure transitivity and importance of machine tool components on maintenance cycles, proposing definitions for fault transfer probability and utilizing the improved LeaderRank algorithm to evaluate component importance.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART O-JOURNAL OF RISK AND RELIABILITY
(2021)
Article
Chemistry, Multidisciplinary
Liming Mu, Yingzhi Zhang, Jintong Liu, Fenli Zhai, Jie Song
Summary: This paper presents a dynamic analysis method for fault propagation behavior of machining centers that integrates fault propagation mechanisms with model structure characteristics, establishes a fault propagation hierarchy structure model using design structure matrix (DSM), calculates fault influence degree, and constructs a fault propagation intensity model to analyze real-time fault propagation behavior, providing reference for fault maintenance and reliability growth of machining centers.
APPLIED SCIENCES-BASEL
(2021)
Article
Engineering, Multidisciplinary
Liming Mu, Yingzhi Zhang, Xiaofeng Wang, Yutong Zhou
Summary: The research proposed a method using hypergraph theory to analyze failure propagation behavior, constructing a hierarchical structure model, considering the influence of multiple truncation data, and calculating coefficients of failure propagation and diffusion using hypergraph theory. Critical failure nodes and paths were identified based on the calculated influence degrees of failure.
QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL
(2022)
Article
Engineering, Multidisciplinary
Yubin Zheng, Jie Song, Yingzhi Zhang, Shengdong Hou, Jun Zheng
Summary: This article introduces the widely used Universal Generating Functions and L-z transformations in the reliability modeling of multi-state systems. In order to solve the problem of complex calculations in the L-z transformation, a screening function is defined to screen the state performance parameters in advance, and the process is simplified through the screen matrix and the screen block diagram, effectively reducing dimensions and improving reliability analysis efficiency.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART O-JOURNAL OF RISK AND RELIABILITY
(2023)
Article
Chemistry, Multidisciplinary
Liming Mu, Yingzhi Zhang, Guiming Guo
Summary: This paper proposes a comprehensive failure risk assessment method of a machining center component based on topology analysis, which considers the topological characteristics of the system and the influence of propagation risks. The Analytic Network Process (ANP) is used to calculate the influence degree of failure modes, and it is combined with component failure mode frequency ratio and failure rate function to calculate independent failure risk. The topological structure and failure probability are used to calculate the failure propagation influence degree, and the component propagation failure risk is then calculated based on this. This method has been demonstrated to be more effective and advanced compared to traditional assessment methods.
APPLIED SCIENCES-BASEL
(2022)
Article
Chemistry, Multidisciplinary
Lan Luan, Guixiang Shen, Yingzhi Zhang, Guiming Guo
Summary: This study proposes a method for identifying key components of CNC lathe based on the dynamic influence of fault propagation. By analyzing cascaded faults and calculating the dynamic impact value of fault propagation, the key components of the system can be determined.
APPLIED SCIENCES-BASEL
(2022)
Article
Chemistry, Analytical
Yingzhi Zhang, Guiming Guo, Jialin Liu
Summary: This study proposes a new method for immediate fault warning and fault root tracing of CNC lathes. Information acquisition scheme was formulated based on the analysis of the coupling relationship between the mechanical parts of CNC lathes. Transfer entropy theory was introduced to calculate the net entropy of information transfer between the mechanical parts and construct the information transfer model. By analyzing the information transfer changes between the parts, fault early warning and fault root tracking on the CNC lathe were realized. The effectiveness of the proposed method is verified by a numerical control lathe tool processing experiment.
Article
Mathematics
Yingzhi Zhang, Guiming Guo, Fang Yang, Yubin Zheng, Fenli Zhai
Summary: A tool remaining useful life prediction method is proposed based on a non-homogeneous Poisson process and Weibull proportional hazard model, considering the grinding repair of machine tools during operation. The method builds an intrinsic failure rate model using tool failure data and establishes a WPHM by collecting vibration information during operation. By incorporating tool grinding repair, the NHPP-WPHM under different repair times is established to describe the tool's comprehensive failure rate. The effectiveness of the model is verified by comparing it with actual remaining useful life and another WPHM-based prediction model.
Article
Engineering, Multidisciplinary
Yingzhi Zhang, Yutong Zhou, Fang Yang, Zhiqiong Wang, Mo Sun
Summary: To overcome the deviation caused by neglecting the dynamic nature of fault propagation in traditional methods, a new approach is proposed based on the maximum occurrence probability to identify the key fault propagation path. The occurrence probability is defined by dynamic importance, dynamic fault propagation probability, and fault rate. By analyzing the fault information of CNC machine tools that follow Weibull distribution, it is proven that the method is reasonable. The results show that the key fault propagation path of CNC machine tools changes with time, from electrical component (E) to mechanical component (M) before 1000 hours, and from auxiliary component (A) to mechanical component (M) after 1000 hours. This change should be considered in maintenance strategies and reliability analysis.
EKSPLOATACJA I NIEZAWODNOSC-MAINTENANCE AND RELIABILITY
(2023)
Article
Chemistry, Multidisciplinary
Yingzhi Zhang, Yutong Zhou, Bingkun Chen, Han Zhang
Summary: This paper proposes a subdistribution competing risk model to assess the life of a motorized spindle, considering the impact of performance degradation on traumatic failure. The model assumes that the failure rate ratio of tested products remains constant under different stress levels. Basic reliability, without traumatic failure data, is modeled using a unilateral confidence limit method under a two-parameter Weibull distribution. Performance degradation data are used as covariates, and the regression coefficients are calculated using SPSS software. The constructed subdistribution competing risk model reflects the dependency relationship between reliability and performance degradation, enabling the evaluation of the product's reliability life. The correctness and advantages of the proposed model are verified through a case analysis using the performance degradation information of a motorized spindle.
APPLIED SCIENCES-BASEL
(2023)
