Recommendation Method for 3D Visualization Technology-based Automobile Parts

Abstract

The purpose of this study is to set the relationship between each parts that forms the engine of an automobile based on the 3D visualization technology which is able to be learned according to the skill of the operator in the industry field and to recommend the auto parts using a task ontology. A visualization method was proposed by structuring the complex knowledge by signifying the link and the node in forms of a network and using SOM which can be shown in the form of 3 dimension. In addition, by using is-a Relationship-based hierarchical Taxonomy setting the relationship between each of the parts that forms the engine of an automobile, to allow a recommendation using a weighted value possible. By providing and placing the complex knowledge in the 3D space to the user for an opportunity of more realistic and intuitive navigation, when randomly selecting the automobile parts, it allows the recommendation of the parts having a close relationship with the corresponding parts for easy assembly and to know the importance of usage for the automobile parts without any special expertise.