With the continuous expansion of system scale, the parameter coupling of the system is prominent. Due to limitations in knowledge and experience, it is difficult for designers to objectively analyze the interaction relationship between parameters, resulting in the low accuracy of engineering parameter selection, hence affecting conflict solving. In order to improve the accuracy of engineering parameter selection and the efficiency of conflict solving, this paper proposes a conflict solving process based on mapping between physical parameters and engineering parameters. First, the physical parameters related to the components of the system function model are extracted, and dimensional analysis is used to construct a physical parameter logical network. Secondly, the physical parameter change path related to the problem in the physical parameter logical network is found, and the physical parameter sets corresponding to both conflicting parties are obtained. Then, the engineering parameters corresponding to conflicts can be selected through the mapping model between physical parameters and engineering parameters, which is trained by a neural network with the sample data of physical parameter sets and engineering parameters in existing cases. Finally, Theory of Inventive Problem Solving (TRIZ) tools are used to solve conflicts, and the final design scheme is obtained through evaluation. The feasibility and effectiveness of the proposed method are verified by redesigning a bulk traditional Chinese medicine dispenser.