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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]

Hydrophilic polymer coatings on artificial implants generate excellent tribological properties. The friction properties of polymer coatings are affected by salt ion factors. Herein, the atomic force microscopy (AFM) was used to show that the superlubricity was achieved between poly(vinylphosphonic acid) (PVPA)-modified Ti6Al4V and polystyrene (PS) microsphere probe lubricated with monovalent salt solutions (LiCl, NaCl, KCl, and CsCl). Considering that adhesion is an important cause of friction changes, the AFM was further utilized to obtain adhesion between friction pairs in different salt solutions. The results indicated that the larger the cation radius in the lubricant, the smaller the adhesion, and the lower the friction coefficient of the PVPA coating. The electrostatic interaction between the PVPA and one-valence cations in lubricants was analyzed by the molecular dynamics (MD) simulation as it was found to be the main influencing factor of the adhesion. Combined analysis results of friction and adhesion indicated that by adjusting the size of cation radius in lubricant, the adhesion between the tribo-pairs can be changed, and eventually the magnitude of friction can be affected. This study opens up a new avenue for analyzing the friction characteristics of hydrophilic polymer coatings from the perspective of intermolecular forces. [ABSTRACT FROM AUTHOR]

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]

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]

Sum-frequency generation (SFG) vibrational spectroscopy is a second-order nonlinear optical spectroscopy technique. Owing to its interfacial selectivity, SFG vibrational spectroscopy can provide interfacial molecular information, such as molecular orientations and order, which can be obtained directly, or molecular density, which can be acquired indirectly. Interfacial molecular behaviors are considered the basic factors for determining the tribological properties of surfaces. Therefore, owing to its ability to detect the molecular behavior in buried interfaces in situ and in real time, SFG vibrational spectroscopy has become one of the most appealing technologies for characterizing mechanisms at friction interfaces. This paper briefly introduces the development of SFG vibrational spectroscopy and the essential theoretical background, focusing on its application in friction and lubrication interfaces, including film-based, complex oil-based, and water-based lubricating systems. Real-time detection using SFG promotes the nondestructive investigation of molecular structures of friction interfaces in situ with submonolayer interface sensitivity, enabling the investigation of friction mechanisms. This review provides guidance on using SFG to conduct friction analysis, thereby widening the applicability of SFG vibrational spectroscopy. [ABSTRACT FROM AUTHOR]

Hydrophilic polymer coatings can improve the surface characteristics of artificial implants. However, because they are used in vivo, they inevitably come into contact with biomolecules that affect their interfacial tribological properties. In this paper, the friction behaviors of poly(vinylphosphonic acid) (PVPA)-modified Ti6Al4V and polytetrafluorethylene balls were analyzed using albumin, globulin, aggrecan, and hyaluronic acid as lubricants. The interaction properties and dynamic adsorption characteristics of the biomolecules and PVPA molecules were explored by a quartz crystal microbalance to identify the cause of the friction difference. It was found that protein molecules disturbed the superlubricity of the PVPA-phosphate-buffered saline system because of the formation of a stable adsorption film, which replaced the interfacial characteristics of the PVPA coating. Polysaccharides, with their excellent hydration properties and polymer structure, had an unstable dynamic interaction or zero adsorption with PVPA molecules, and hardly changed the superlubricity of the PVPA and phosphate-buffered-saline system. The influence mechanism of the specific friction of proteins and polysaccharides was analyzed. Interactions were observed among different biomolecules. Polysaccharides can potentially reduce protein adsorption. The result of the synergistic regulation of the friction coefficient for PVPA-modified Ti6Al4V is approximately 0.017. The results of this study will provide a theoretical basis for the use of polymer coatings in vivo. [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]