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 $L_{18}(2^{1}\times 3^{7})$ 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. Note to Practitioners —The study finds the optimal process parameters for the grinding of hardened mold steel in a nanofluid/ultrasonic atomization minimum quantity lubrication system. At present, grinding hardened mold steel is a costly and time-consuming undertaking, because it lacks an efficient lubricating method. The study considered grinding force ratio, grinding temperature, and surface roughness as single-quality characteristics for gray relational analysis and fuzzy inference to calculate multiple performance characteristic indexes. These indexes identified the optimal parameter combination for grinding hardened mold steel. The results suggested that the proposed lubrication system is highly effective in this regard.