Research on Optimization Strategies for Functional Modules of Smart Home Products Based on Parameterization

The article firstly outlines the concept of parametric design and modeling techniques and processes, then expresses the relationship between customer needs and functional design parameters of smart home products with discrete sensitivity matrix, and introduces the fuzzy pairwise comparison method to calculate the importance of customer needs.The correlations in the dataset are mined on the Rough Set (RS) tool.AGO and IAGO are used to predict the customer demand importance and design parameter importance in the future cycle, and the parametric product family optimization model is solved by combining the non-occupancy sorting genetic algorithm with congestion distance.In this paper, the optimization ranking and core parts of the functional modules of the smart flowerpot are obtained through the parametric smart home design method, and the functional rankings of the modules are automatic irrigation function, intelligent light replenishment function, monitoring function, and human-computer interaction function; the core parts include temperature and humidity sensors, light sensors, water tanks, and single-chip microcomputer parts, and so on.In the intelligent flowerpot product family design, this paper finds that the efficiency of this paper's optimization method increases significantly (4.23%-9.12%)and the weight of the product decreases significantly (0.1141kg-0.617kg),both in the known platform mode and in the unknown platform mode.The results of this paper are extremely important for the development and design of parametric product families based on platforms.