Applying knowledge structure to the usable fault diagnosis assistance system: A case study of motorcycle maintenance in Taiwan

Abstract

Abstract Today, Taiwan motorcycle is the third major exporting country and has better competition than other countries in a kind of under 150 cc motorcycle. According to the statistics, there are 12,822,455 motorcycles of Taiwan in 2005. Though Taiwan motorcycle's density is the highest in the world, the motorcycle maintenance technique seems not on the same level. Therefore, how to promote motorcycle maintenance knowledge and service level for customers has become a critical issue in the transportation market of Taiwan. This study proposes a fault diagnosis assistance system (FDAS) that applied in the motorcycle maintenance. The knowledge structure of experts was derived from expert's experience knowledge to construct a knowledge base, and then to build a usable human–computer interface. This study also examined the knowledge structures of a novice group and an expert group by using a knowledge network organizing method. The similarities between novice's and expert's networks were assessed using the three indices of proximities (PRX), graph-theoretic distance (GTD), and closeness (PFC or C). The results indicated that the knowledge structure of the FDAS group is better than that of the manual group. Additionally, the usability test confirmed the well-used system interface. It also proved that the novice's knowledge structure became better after using FDAS. It can, of course, serve as an educational training tool for maintainers and shorten learning time effectively and also make up for the shortage of Taiwan motorcycle's maintainers.