Research on the Evaluation of Small Sample Reliability for CNC Grinding Machine Tools Based on Bayes Theory

Fan, Jiahao; Zhou, Zhóng Yuan; Wang, Ze Li; Miao, Wei

doi:10.4028/www.scientific.net/amr.971-973.688

Cited by 6 publications

(4 citation statements)

References 2 publications

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“…A Bayesian reliability assessment method of small sample failure data for numerically controlled machine tools with imperfect repair was proposed in a recent systematic study [34][35][36]. The selection of prior and posterior distributions for a virtual age model of a generalized renewal process was discussed.…”

Section: Nc Machine Tool Reliability Analysis Techniquesmentioning

confidence: 99%

Recent development in reliability analysis of NC machine tools

2015

Int J Adv Manuf Technol

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Numerical control (NC) machine tools are the fundamental equipment of the machinery industry. The reliability of NC machine tools directly influences the processing quality, productivity, and efficiency. This paper reviews the latest developments in the reliability analysis of NC machine tools. The main analysis methods and modeling techniques used in reliability assessment of NC machine tools are illustrated with brief case studies. The reliabilities of typical subsystems of NC machine tools are discussed. In addition, several important key problems and issues remain to be addressed about the reliability analysis of NC machine tools and opportunities for further research are identified.

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Section: Nc Machine Tool Reliability Analysis Techniquesmentioning

confidence: 99%

Recent development in reliability analysis of NC machine tools

2015

Int J Adv Manuf Technol

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“…Distribution Type Test Based on Engineering Experience. According to engineering experience, fault nature and failure mechanisms of products can be roughly inferred from the type of product life distribution [7]. For example, if the product's life obey exponentially distributed type, you can determine the fault of the product is mainly caused due to some random reason, nothing to do with the product working hours.…”

Section: Prior Information Distribution Type Testmentioning

confidence: 99%

Study on the Prior Information Credibility Test in Low-Voltage Switchgear Reliability Assessment

Xu¹,

Wang

2014

AMM

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Reliability Assessment of low-voltage switchgear is of great significance to the safety of power system and its equipment. In this thesis, Bayes theory is introduced into the reliability Assessment of low-voltage switchgear. The main failure modes and failure rate of low-voltage switchgear has been summarized, and the fault arrangement diagram of low voltage switchgear is given in this paper. In view of the low-voltage switchgear with high reliability and relatively large number of samples, a feasible compatibility test method is proposed. Firstly, the distribution type can be tested through engineering experience and Goodness of fit test for weibull distribution. Then a prior information compatibility test is carried out by Wilcoxon rank sum test and Kolmogorov-Smirnov nonparametric test method. Finally, the prior information which is incompatible with credible site information is removed and reliable prior information is obtained. This paper lays a solid foundation for the Low-voltage switchgear reliability assessment based on Bayes theory.

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“…A method for estimating the reliability of a wind power system based on modeling and analysis was developed by Erylmaz and Kan [21]. In Fan et al [22], the evaluation of a small sample was applied in a CNC grinding machine evaluation based on Bayes theory. In terms of the production of CNC machine tools, due to the use of big data technology, CNC machine tools have been rapidly produced on a large scale, which has played an important role in the upgrading of CNC machine tools and the improvement of their quality and efficiency [23].…”

Section: Introductionmentioning

confidence: 99%

Human–Machine Systems Reliability: A Series–Parallel Approach for Evaluation and Improvement in the Field of Machine Tools

et al. 2022

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Machine workshops generate high scrap rates, causing non-compliance with timely delivery and high production costs. Due to their natural characteristics of a low volume, high-mix production batches, and serial and parallel configurations, generally the causes of their failure are not well documented. Thus, to reduce the scrap rate, and evaluate and improve their reliability, their system characteristics must be considered. Based on them, our proposed methodology allows us to evaluate the system, subsystem, and component–subsystem relationship by using either the Weibull and/or the exponential distribution. The strategy to improve the system performance includes reliability tools, expert interviews, cluster analysis, and root-cause analysis. In the application case, the failure sources were found to be mechanical and human errors. The component maintenance/setup, institutional conditions/attitude, and subsystem process/operation were the machine factors that presented the lowest reliability indices. The improved activities were monitored based on the Weibull β and η parameters that affect the system reliability. Finally, by using a life–effort analysis, and the method of comparative analysis of two sequential periods, we identified the causes that generated a change in the Weibull parameters. The contribution of this methodology lies in the grouping of the tools in the proposed application context.

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Research on the Evaluation of Small Sample Reliability for CNC Grinding Machine Tools Based on Bayes Theory

Cited by 6 publications

References 2 publications

Recent development in reliability analysis of NC machine tools

Recent development in reliability analysis of NC machine tools

Study on the Prior Information Credibility Test in Low-Voltage Switchgear Reliability Assessment

Human–Machine Systems Reliability: A Series–Parallel Approach for Evaluation and Improvement in the Field of Machine Tools

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