Abstract: In order to improve the commercial value of electromechanical equipment brand products and meet the needs of users for brand image, a brand image optimization and innovation method based on gene classification interactive genetic algorithm is proposed. Research and expert evaluation methods are used to extract important design elements and clear brand image vocabulary. Then the quantitative theory I is used to construct the perceptual evaluation matrix according to the corresponding relationship, and calculate the contribution value of each design element to the perceptual element set, bringing them in genetic operation through IGA. Finally, the perceptual evaluation value interval is used as the constraint condition to select the final output scheme. The method and process are applied to the design project of Jingshan Light Machinery Jepley Printing Machines. Comparing the cases before and after gene classification, the improved algorithm can obtain the shape design scheme with high user adaptability more quickly, effectively improve the effective scheme output efficiency and shorten the project period. Moreover, the equipment has been put into production in Antalya and Cerkezkoy factories of Ankutsan Group, which proves that the equipment has certain competitiveness in the high-end market. Therefore, this method can effectively guide the innovative design of electromechanical brand products, and provide a feasible and effective method for the brand image research of electromechanical equipment.

Key words: brand image, gene classification, interactive genetic algorithm, quantification theory type I