A Reliability Statistical Evaluation Method of CNC Machine Tools Considering the Mission and Load Profile

Mu, Zongyi; Zhang, Genbao; Ran, Yan; Zhang, Shengyong; Li, Jian

doi:10.1109/access.2019.2935622

Cited by 10 publications

(6 citation statements)

References 20 publications

(22 reference statements)

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“…MUCs can be obtained by combining the MUs according to the transmission relationship, 19 shown as Figure 3. Every MUC can perform a specific output motion of machine tools independently.…”

Section: Fma Decomposition and Degradation Analysis Of The Machine Toolmentioning

confidence: 99%

Remaining useful life prediction method for machine tools based on meta-action theory

Ran

Zhang

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part O:

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Remaining useful life (RUL) is a crucial indictor to measure the performance degradation of machine tools. It directly affects the accuracy of maintenance decision-making, thus affecting operational reliability of machine tools. Currently, most RUL prediction methods are for the parts. However, due to the interaction among the parts, even RUL of all the parts cannot reflect the real RUL of the whole machine. Therefore, an RUL prediction method for the whole machine is needed. To predict RUL of the whole machine, this paper proposes an RUL prediction method with dynamic prediction objects based on meta-action theory. Firstly, machine tools are decomposed into the meta-action unit chains (MUCs) to obtain suitable prediction objects. Secondly, the machining precision unqualified rate (MPUR) control chart is used to conduct an out of control early warning for machine tools’ performance. At last, the Markov model is introduced to determine the prediction objects in next prediction and the Wiener degradation model is established to predict RUL of machine tools. According to the practical application, feasibility and effectiveness of the method is proved.

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“…MUCs can be obtained by combining the MUs according to the transmission relationship, 19 shown as Figure 3. Every MUC can perform a specific output motion of machine tools independently.…”

Section: Fma Decomposition and Degradation Analysis Of The Machine Toolmentioning

confidence: 99%

Remaining useful life prediction method for machine tools based on meta-action theory

Ran

Zhang

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part O:

Self Cite

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“…To comprehensively evaluate the reliability of the ve-axis CNCMT, Wang [2] et al applied the matter-element theory in extension to establish the matter-element model of reliability evaluation and fully established the reliability evaluation index system. Mu [3] et al used radial basis function (RBF) neural networks to model the mapping between mission pro le and load pro le and machine tool reliability. ese methods consider the failure characteristics of the CNCMT and build a reliability model based on time data.…”

Section: Introductionmentioning

confidence: 99%

Ranking of Key Components of CNC Machine Tools Based on Complex Network

Peng

Zhang

Liu

et al. 2022

Mathematical Problems in Engineering

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Complex networks have become a center of interdisciplinary research. The robustness and reliability of complex systems can be determined by analyzing the characteristics of networks. The computer numerical control machine tool (CNCMT) is a typical complex system, and reliability is the key factor that affects the processing quality and performance of the CNCMT. The process of quantitatively determining the key functional components of CNCMT and carrying out reliability growth experiments on them remains difficult. A new importance-ranking method for the key functional components of the CNCMT is proposed in this study. First, the real characteristics of the CNCMT are analyzed, and the complex network of the CNCMT is constructed. Then, we study various indicators of the network and determine that the network has small-world characteristics. Finally, a variety of complex network characteristic indicators are fused, the weight of each indicator is determined based on the analytic hierarchy process (AHP), the importance of each node is quantitatively determined, and the fused indicators are compared with a single indicator.

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“…At present, the research on meta‐action unit has been relatively mature, and some achievements have been achieved, such as Refs. (25–30). In order to eliminate the early failure of electromechanical product as much as possible before it leaves the factory, it is necessary to establish a reasonable failure elimination system.…”

Section: Introductionmentioning

confidence: 99%

Early failure active elimination system research for electromechanical product based on meta‐action

Wen

Liu

et al. 2021

Quality & Reliability Eng

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Frequent early failures have been the key factor restricting the reliability improvement of electromechanical product, and also reducing its market competitiveness. Most of the current early failure elimination methods are passive elimination technologies after a failure. Their purpose is to quickly restore the production capacity of products, which is mainly used to improve the reliability of the products, and cannot fundamentally improve the quality of the manufactured product. To address those problems, this paper first analyzed the causes of early failures in the production stage of electromechanical product, and studied the corresponding early failure elimination mechanism; second, according to the FRACAS (Failure Report Analysis and Corrective Action System), an early failure elimination method for electromechanical product was proposed based on the meta‐action unit; finally, in order to ensure the smooth implementation of early failure elimination measures, a set of early failure active elimination guarantee management system was established. In addition, this paper also introduced the specific implementation process of the proposed method. The proposed method is applied to engineering, and the results verify its correctness. The proposed method provides a theoretical basis and technical support for the elimination of electromechanical product early failure.

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A Reliability Statistical Evaluation Method of CNC Machine Tools Considering the Mission and Load Profile

Cited by 10 publications

References 20 publications

Remaining useful life prediction method for machine tools based on meta-action theory

Remaining useful life prediction method for machine tools based on meta-action theory

Ranking of Key Components of CNC Machine Tools Based on Complex Network

Early failure active elimination system research for electromechanical product based on meta‐action

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