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The reliability allocation of machine tools which is a multi-attribute decision-making problem has great significance in designment of machine tools. This paper integrates the intuitionistic trapezoidal fuzzy numbers and performance sorting technique based on similar ideal solutions to achieve the flexible allocation of machine tools reliability. Firstly, intuitionistic trapezoidal fuzzy numbers are employed to integrate decisions made by multiple decision-makers and fuzzy information of their preferences. Then, intuitionistic trapezoid fuzzy numbers' expectations are treated as the weights of criteria. Finally, performance sorting technique based on similar ideal solutions is used to obtain the reliability allocation weight of every subsystem. To investigate the efficacy and simplicity of the provided approach, reliability distribution in a CNC machine tool is introduced as an example to explain its specific contents. It can be concluded that the provided method is more precise and convenient by comparing the results of this approach with those obtained by analytic hierarchy process method. [ABSTRACT FROM AUTHOR]

In the actual production, it is expected to find several sensitivity geometric errors which have great influence on machining accuracy, so as to provide references for the manufacturing, assembly, and other links of the machine tool, and fundamentally improve the working performance. To study this problem, a novel global sensitivity analysis (GSA) method is proposed. Based on the MBS theory, the spatial error model is established to analyze the local influence of geometric error on machining accuracy. An improved second-order partial correlation coefficient based on the Pearson product moment is proposed to analyze the correlation between geometric errors. In addition, the error parameters will change greatly in the stroke of the moving parts. However, the rapid fluctuation of geometric error value will have a dynamic impact on the machining accuracy of machine tools, which is rarely noticed in the previous sensitivity analysis. This change is defined as the fluctuation of error. The high fitting degree function of error-displacement is obtained by using the high order Fourier series and sine series. Then, the fluctuation of the error in the machining stroke is analyzed by using the derivative of the function to the displacement. Through geometric error characteristics (including the local influence, correlation, and fluctuation) are studied comprehensively, the GSA of error is carried out. Finally, taking a machining center as an example and combining the sensitivity analysis results, the improvement measures are proposed to verify the correctness of the method. [ABSTRACT FROM AUTHOR]