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Machining time and energy consumption are common process planning evaluation metrics. However, it is difficult to obtain accurate machining time and energy consumption values in the process planning stage, which may result in non-optimal obtaining process routes. To solve these problems, this paper proposes a flexible process planning method based on processing time and energy consumption prediction models. The historical processing data is analyzed, and a prediction model of machining time and energy consumption based on a radial basis function neural network is proposed. Considering the flexibility of multiple processes, a mathematical model of the flexible process planning problem based on the machining time and energy consumption prediction model is established. A multi-objective algorithm using a multidimensional real number coding method is proposed for problem-solving with the completion time and energy consumption minimization as the optimization objective. Two algorithms with better multi-objective optimization performance, the strength Pareto evolution algorithm 2, and the dominance ranking genetic algorithm II are selected for comparative analysis to obtain a better effect of optimization. The better algorithm is selected with the best parameters. Finally, case studies are conducted to verify the validity of the prediction model and the flexible process planning model. [ABSTRACT FROM AUTHOR]

It has been widely recognized that there are influences of static friction characteristics in a bolted joint on pre-tightening and service reliability. This study proposed a static friction coefficient model of joint surfaces based on the modified three-dimensional fractal model. A method of measuring the static friction coefficient of joint surfaces was investigated to verify the accuracy of model. The results showed that calculated value of the model and measured value of experiment are highly matched. Furthermore, the influential mechanisms of material, pressure, and surface topography were investigated. The relative error between experimental results and model calculations are all less than 15%. This research provides a theoretical basis for subsequent research on the friction characteristics of joint surfaces and connection reliability of bolted joints. [ABSTRACT FROM AUTHOR]

With the increasing applications of the planetary roller screw mechanism (PRSM) in mechanical systems particularly machine tools, a comprehensive mathematical model is required to define the kinematic characteristics and relations of the PRSM, such that its performances can be predicted for reliability analysis and design of machine tools. In this paper, the influences of machining and assembly errors on the motion characteristics of the PRSM are analyzed, and the kinematic model of the PRSM is established considering runout errors and elastic deformation. The planetary roller screw mechanism can be considered as a spring-mass system for analysis of the elastic deformation of the ball screw's thread under inertial force. For the spring-mass system, adjacency matrix is introduced to define the relationships between the elastic displacements of the joints and the deformations of the elements. Then, by considering the balance of force and the coordination of deformation, the nonlinear motion model of the double-nut roller screw is established. The effectiveness of the proposed model is verified by comparing the analytical results with the experimental data. [ABSTRACT FROM AUTHOR]

In the reliability optimization design field of CNC machine tools, reliability allocation plays a significant part, which has the characteristics of high complexity and strong uncertainty. Traditionally, reliability allocation methods have the disadvantages of a single allocation influence factor, too subjective or too objective, not flexible enough, etc. To solve the related problems, a novel reliability allocation method for machine tools is proposed, which combines subjective and objective weightings, and a variety of influencing factors are considered comprehensively. To deal with the characteristic of uncertainty and fuzziness in machine tool reliability analysis, different intuitionistic trapezoidal fuzzy numbers (ITrFNs) are allocated according to the importance of influencing factors. As the subjective method, the analytic hierarchy process (AHP) can reflect the decision maker's subjective preferences of machine tool influence factors, while the grey relational method (GRA) can analyze the relationship between data which is adopted as an objective weighting method. The reliability of each subsystem is obtained by combining the two methods. Finally, the validity of the proposed method is proved by an illustration analyzing and comparing it with the traditional AHP method and fuzzy allocation methods. [ABSTRACT FROM AUTHOR]

In the state of machining service, to evaluate the machining accuracy reliability of multi-axis CNC machine tools, analyze the accuracy failure mode and the reliability sensitivity under the failure mode, this paper proposes a research method by the cross-correlation studies of geometric error parameters to improve and promote the accuracy reliability of CNC machine tools. Firstly, by multi-body system theory, the homogeneous coordinate transformation matrix between each body of the machine tool is established, and the spatial machining accuracy model is constructed. At the same time, considering the time series problem in the measurement process of geometric error parameters, this paper studies the correlation between the error parameters for reliability analysis and proposes a novel reliability analysis index for each measurement point in the machine tool workspace. To validation of the method, the analysis results of this paper are compared with those by Monte Carlo simulation. In addition, the accuracy failure conditions of the machine tool are studied, the failure state function of machine tool accuracy is established, and the accuracy failure modes that may occur are analyzed from this, to carry out the accuracy failure sensitivity analysis under the failure mode, and to identify key geometric errors which have a great impact on the machining accuracy reliability of machine tool in the failure mode. Finally, taking a 3-axis machine tool as an example, according to the analysis results, this paper puts forward measures to improve the accuracy reliability and verifies the feasibility of the proposed method. [ABSTRACT FROM AUTHOR]

For the flat plastic parts with the size range of 200 to 1300 mm, the structural parameters decision model of injection mold gating system is established in this paper. Firstly, the relationship between the warpage and the structural parameters of gating system is fitted by Kriging model, and the minimum warpage is optimized by genetic algorithm (GA) to obtain the best structural parameters. Secondly, the best structural parameters of gating system corresponding to 16 groups of plastic parts are taken as samples, and the relationship between the structural parameters of gating system and the size parameters of plastic parts is established by Kriging model. In addition, K-means is used to reduce the number of the structural parameters of gating system from 5 to 2, in order to improve the accuracy of decision model. Finally, the size parameters of plastic parts are input to the decision model to obtain the structural parameters of gating system. Through the verification of mold flow analysis experiment, the structural parameters of gating system obtained by this method meet the design requirements and can effectively shorten the structural design cycle of injection mold. [ABSTRACT FROM AUTHOR]