Optimization of feature transfer based on BioTRIZ

Abstract

Feature transfer is an important and practical tool to eliminate the disadvantages of old technology systems and develop new ones. However, in TRIZ feature transfer tools, there are some problems, such as an incomplete search of competitive systems and an imprecise selection of alternative systems. To solve these problems effectively, based on the basic principles of feature transfer and BioTRIZ, this study optimizes feature transfer by combining the related theories of BioTRIZ. Function-oriented search and bionic knowledge case base are used to supplement the search of competitive systems in the domain. The similarity principle is used for the strict selection of alternative systems. This method can find the competitive system more comprehensively, and provide quantitative criteria for the selection of alternative systems. By improving the terrain passing capacity of the wheeled walking mechanism, this paper proves the feasibility and effectiveness of the optimized feature transfer method.