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The problems of the individualized product evaluation were formalized, and a product evaluation model with algorithms based on case reasoning was proposed. The case library was divided into groups through fuzzy clustering analysis, and different groups had different dynamic weights by mathematical calculation under the constraints of experience rules. The program flow chart of the algorithm of evaluation parameter weights optimization was presented. Euclidean distance with weights was adopted to search a similar instance. The final result of product evaluation was adjusted based on the similar instance. The proposed methodology demonstrated the effectiveness in an instance of the evaluation of crane products.