Poly-ether-ether ketone (PEEK) is a great potential thermoplastic in industry and medical treatment and health. In this work, PEEK/graphene oxide (GO) and PEEK/MoS₂ composites were prepared by a novel hot isostatic pressing method. The addition of GO alters the tribological behaviors mechanism; fatigue wear mechanism is predominant to PEEK/GO composites. However, the combination of abrasive and adhesive wear mechanisms is observed for PEEK/MoS₂ composites and PEEK. The reason for this is that the hardness and tensile strength of composites are increased with the appropriate addition of GO. The response time to stable friction state of PEEK/GO and PEEK/MoS₂ composites is reduced in comparison with PEEK, which is conducive to shorten running-in time, reduce the energy consumption, and improve the tribological performances of composites. The addition of GO and MoS₂ can effectively decrease the friction coefficient and wear rate, and the optimal content of GO and MoS₂ was 0.7 wt.% and 15 wt.%, respectively. The results indicate that PEEK/GO and PEEK/MoS₂ are impressive composites that possess super tribological properties.

As a vital component of electronic products, the quality of the printed circuit board (PCB) assembly directly affects the applications and service life. During the reflow soldering process, the PCB assembly may suffer excessive warpage. Therefore, in order to avoid such a failure, this paper conducts the finite element simulation of the PCB assembly temperature change and the deformation process according to a theoretical model for heat transfer and then explores the causes of warpage and predicts the percentage of warpage that occurs during the reflow soldering. A reliability sensitivity analysis is creatively applied in the PCB assembly warpage study in order to uncover the quantitative influence of multiple factors with random errors on warpage. Moreover, the reliability calculation provides a theoretical basis for the allowable error range of geometric dimensions, material properties and process parameters of the PCB assembly. This research has a remarkable significance and is valuable to engineering in promoting quality and reliability, and increasing the yield of PCB assembly in mass production.

As the performance function of a mechanical structure is usually based on time-consuming computer codes, predicting time-dependent reliability analysis requires a large number of costly simulations in engineering. To reduce the number of evaluations of time-consuming models and enhance efficiency of time-dependent reliability analysis, Kriging is employed as a surrogate of original performance function. Firstly, a quantitative measure of the error of Kriging-based estimation of time-dependent failure probability is obtained by derivation. Dividing the quantitative measure by the Kriging-based estimation, the associated relative error is approximately estimated. Secondly, to construct an accurate Kriging model using fewer samples, a DoE (the design of experiments) strategy is developed. The idea is to adaptively refresh Kriging model with the best next sample that could enhance Kriging model the most with regard to expectation. Finally, a Kriging-based time-dependent reliability analysis method is constructed. In the method, Kriging model is adaptively refreshed according to the proposed DoE strategy, until the relative error of estimated probability of failure below a given threshold. The threshold could be quantitatively adjusted to accuracy requirement of reliability analysis. The proposed method can predict the evolution of failure probability over time. Its advantage is validated by three numerical examples.

Grind-hardening processing is an emerging approach that combines the grinding and surface quenching process. During the process, the hardened layer—mainly martensite—is produced on the surface of the workpiece to achieve the purpose of surface strengthening. Above all, the surface temperature field of the hypoeutectoid-1045 steel workpiece was determined by finite element method for fully revealing the formation mechanism of the hardened layer. Further, the cellular automata approach was applied to dynamically simulate the transformation of both austenitization and martensitization from the initial microstructure. The hardness penetration depth was also predicted. Finally, a grind-hardening experiment was conducted to assess the theoretical study. Results showed that a combination of the finite element method and the cellular automata approach can effectively simulate the microstructure transformation of hardened layer. The microstructure and the hardness penetration depth were affected by the maximum grinding temperature and the heating rate. Research on the influence of grinding parameters showed that the hardness penetration depth increased as the depth of the wheel cut and feeding speed increased. Experiments revealed that the difference between predicted value and experimental value of the hardness penetration depth varied between 2.83% and 7.31%, which confirmed the effectiveness of the predicted model.

With the increasing operating mileage and ownership of high-speed electric multiple units (EMU), a reasonable operation and maintenance strategy is the key to ensure their safe and reliable operation. As a key component of recombined EMU, creating a reasonable and effective risk assessment method for the fully automatic coupler draft gear (FACDG) is the first task. Therefore, based on fuzzy rough number theory, combined with the analytic hierarchy process (AHP), entropy weight method (EWM), technique for order performance by similarity to ideal solution (TOPSIS) and grey relational analysis (GRA), a risk priority indicator of comprehensive nearness degree is developed. Furthermore, a novel multi-criteria decision making (MCDM) failure modes, effects and criticality analysis (FMECA) assessment method is proposed. The effectiveness and rationality of the risk assessment method proposed are verified by the analysis of data and failure modes of a certain FACDG at fourth-level engineering maintenance.

As an emerging composite processing technology, the grind-hardening process implements efficient removal on workpiece materials and surface strengthening by the effective utilization of grinding heat. The strengthening effect of grind-hardening on a workpiece surface is principally achieved by a hardened layer, which is chiefly composed of martensite. As a primary parameter to evaluate the strengthening effect, the hardness of the hardened layer mostly depends on the surface microstructure of the workpiece. On this basis, this paper integrated the finite element (FE) and cellular automata (CA) approach to explore the distribution and variation of the grinding temperature of the workpiece surface in a grind-hardening process. Moreover, the simulation of the transformation process of “initial microstructure–austenite–martensite” for the workpiece helps determine the martensite fraction and then predict the hardness of the hardened layer with different grinding parameters. Finally, the effectiveness of the hardness prediction is confirmed by the grind-hardening experiment. Both the theoretical analysis and experiment results show that the variation in the grinding temperature will cause the formation to a certain depth of a hardened layer on the workpiece surface in the grind-hardening process. Actually, the martensite fraction determines the hardness of the hardened layer. As the grinding depth and feeding speed increase, the martensite fraction grows, which results in an increase in its hardness value.