In automobiles, lock parts are matched with inserts, and this is a crucial quality standard for the dimensional accuracy of the molding. This study employed moldflow analysis to explore the influence of various injection molding process parameters on the warpage deformation. Deformation of the plastic part is caused by the nonuniform product temperature distribution in the manufacturing process. Furthermore, improper parameter design leads to substantial warpage and deformation. The Taguchi robust design method and gray correlation analysis were used to optimize the process parameters. Multiobjective quality analysis was performed for achieving a uniform temperature distribution and reducing the warpage deformation to obtain the optimal injection molding process parameters. Subsequently, three water cooling system designs—original cooling, U-shaped cooling, and conformal cooling—were tested to modify the temperature distribution and reduce the warpage. Taguchi gray correlation analysis revealed that the main influencing parameter was the mold temperature followed by the holding pressure. Moreover, the results indicated that the conformal cooling system improved the average temperature distribution.

The purpose of this paper is to make a nanofluid/ultrasonic atomization minimum quality lubrication (MQL) system, and to explore the effectiveness of the system used in the grinding process of SKD11 mold steel with heat treatment. Besides, a set of optimized multiple quality characteristics of grinding parameter combinations is obtained by using the Taguchi method and the fuzzy inference system. The experimental parameter combinations design is performed by using L18(2 ¹ × 3 ⁷ ) orthogonal table of the Taguchi method, where the experimental parameters are the type of nanoparticles, nanofluid concentration, tangential velocity, table rate, nozzle angle, nozzle distance, air pressure, and spray volume. The single-quality characteristics such as grinding force ratio, grinding temperature, and surface roughness are considered in this paper. The gray relation analysis and the fuzzy inference system are adopted to obtain the multiple performance characteristic index (MPCI), then the combination of maximum MPCI is the optimized multiple quality characteristics of grinding parameter combinations. This paper also compares the difference of nanofluid/ultrasonic atomization MQL and nanofluid/air MQL through the optimized multiple quality characteristics of grinding parameter combinations. Experimental results indicate that the nanofluid parameters containing the type of nanoparticles, nanofluid concentration, and spray volume are the most influential control factors. Comparing nanofluid/ultrasonic atomization MQL with nanofluid/air MQL can also get the best of grinding force ratio, grinding temperature, surface roughness, and surface morphology.

Nanofluid/ultrasonic atomization minimal quantity lubrication (MQL) was used in an SKD11 steel micro-milling process with ultrasonic dispersion. The nanofluid atomizer substantially improved nanofluid reunification and delivery to the cutting zone. The micro-milling cutting force and temperature were used to calculate the signal-to-noise ratio (S/N). Normalization of the S/N in a grey relational analysis obtained a grey correlation coefficient, which was used in a fuzzy analysis to obtain a multiple performance characteristic indexes (MPCI). The MPCI was maximized by optimizing the process parameters for multiple quality characteristics and then comparing the optimized parameters with those in the MQL system. Experimental results indicate that the nanofluid parameters containing the density of nanofluid, feed rate, and distance of nozzle are the most influential control factors, while 3.617 Newton and 117.1 degrees Celsius, respectively, are the optimal combination of parameters. Different lubricating methods were also compared in terms of effects on micro-milling cutting force, micro-milling temperature, micro-milling tool wear, and surface burr. Experiments showed that nanofluid (MWCNTs)/ultrasonic atomization MQL obtained the best results.