Customizing products based on customer needs is an irreversible trend, and many companies strive to provide customized products to customers in less time. Customer requirements are a key factor in the company's ability to provide customized products. In order to better meet customer needs, solve the problem of incomplete and inaccurate expression, and improve the correlation between customized product performance and customer demand, a customized product method based on Bayesian network is proposed. First, the company built a custom product model based on Bayesian networks. According to the model, the customer selects some nodes and their related information. Then, we can accurately predict the final product model through the link tree algorithm, test the customer demand node to determine the focus of the customer's needs, and optimize the model. Finally, an example of a multifunctional nursing bed is used to illustrate the effectiveness of the method.
Customer requirement is a crucial factor for a company to provide customized products. In order to better acquire customer requirements and instruct customers to express their requirements, customer requirement acquisition system is proposed in this article. First, requirement node and the form of requirement expression are constructed as the base of this system. Customer requirements are transformed into the description of requirement nodes. The form of requirement expression limits specific method of describing requirement nodes avoiding ambiguous requirements. Then, requirement expression guidance is proposed to rational plan expression path. Optimal expression path is beneficial for customer to concentrate on significant requirement nodes. Ant colony optimization is used to search for it. As a result, complete and clear customer requirements are acquired and the focus of customer requirements is recognized, which improves the design efficiency of enterprises. Finally, an example of automated guided vehicle is used to illustrate the validity of the proposed method.
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