3D Online Parts Catalog for Quick Identification and Learning

Abstract

People sometimes face challenges when they have to memorize many components or parts of a machine. Although a complete schematic description of a machine and its parts is generally available, many similar parts with different uses can be troublesome, especially for those not specifically in that field. Inventory system managers and item supply custodians must thoroughly understand the parts requested by specific customers, so as not to make mistakes in distributing the ordered parts. Identifying with the correct nomenclature or using part identification number can overcome this problem in general, but it is not without problems. Users who don't understand the code also create the potential for mistaken identification when there are similarities between different items. The general public users experience many difficulties in identifying, selecting, and sourcing suitable parts from the increasingly diverse choices available from various online sources. The ongoing research is developing the concept of an integrated information system cataloging parts using 3D visualization. 3D visualization identifies the parts and shows them in relation to each other in a 3D view derived from a complete machine. The initial prototype was built based on the spiral evolutionary engineering method, as it contained the core features with extended functionality built around them to exchange data, including fetching from external sources. The proposed system is intended to help users speed up learning and identifying each part, thereby reducing mistakes when they need a specific part or to understand it. The catalog presents various data about spare parts, including their availability status, since it can be linked directly to the provider's inventory system or other third parties from which the parts can be purchased. Users can also utilize it to quickly learn about certain parts of the machine since it can be connected to information providers related to those parts, including through the use of AI and automated search engines to gather specific information.