The modern era brought new production paradigms and personalized production is among the most challenging ones. The integration of the customer's specific requirements into the product design is a challenge which can be addressed with the product configurator. In the mass production, the product configurators usually used the constraint-based approach which becomes insufficient for the B2C (business-to-consumer) relationship of the personalized production. Today, complex products result with complex product configurators which are not user-friendly. Nevertheless, the user is usually not interested in detailed technical specifications of the product, but rather in its performance. If the user could only define his/her needs in a term of product's performance, an intelligent backend algorithm should configure the product with desired performance. In this research, a step forward is made by designing a system, rather than designing an algorithm, which can take into account user preferences and decide which product configuration is the best compromise. This paper presents a prototype of the knowledge-based cognitive system for solving special case of product configuration problem. It is the performance-based B2C product configurator for the personalized production era. The proof of concept is the case of solving the product configuration instance with criteria which require humanoid decision-making.

现代时代带来了新的生产范式，个性化生产是最具挑战性的生产范式之一。将客户的特定要求集成到产品设计中是一项可以通过产品配置器解决的挑战。在批量生产中，产品配置者通常使用基于约束的方法，这对于个性化生产的B2C（企业对消费者）关系来说已经不够用了。今天，复杂的产品导致复杂的产品配置器对用户不友好。然而，用户通常对产品的详细技术规格不感兴趣，而是对其性能感兴趣。如果用户只能从产品性能的角度来定义他/她的需求，智能后端算法应配置具有所需性能的产品。在这项研究中，通过设计系统而不是设计算法向前迈进了一步，该算法可以考虑用户偏好并决定哪种产品配置是最佳的折衷方案。本文提出了一种基于知识的认知系统原型，用于解决产品配置问题的特殊情况。它是个性化生产时代基于性能的B2C产品配置器。概念证明是使用需要人形决策的标准来解决产品配置实例的情况。这可以考虑到用户的偏好，并决定哪种产品配置是最好的折衷方案。本文提出了一种基于知识的认知系统原型，用于解决产品配置问题的特殊情况。它是个性化生产时代基于性能的B2C产品配置器。概念证明是使用需要人形决策的标准来解决产品配置实例的情况。这可以考虑到用户的偏好，并决定哪种产品配置是最好的折衷方案。本文提出了一种基于知识的认知系统原型，用于解决产品配置问题的特殊情况。它是个性化生产时代基于性能的B2C产品配置器。概念证明是使用需要人形决策的标准来解决产品配置实例的情况。