Computer-Aided Design Data Extraction Approach to Identify Product Information

Abstract

Problem statement: Many approaches have been proposed in previous such as AUTOFEAT algorithm, feature recognition, Intelligent Feature Recognition Methodology (IFRM), a part recognition algorithm and graph theory-based approach in order to solve the integration issue between CAD and CAM. However, there is no direct connection from CAD database and machine database. Therefore, comparison among the approaches has been conducted because to recognize the suitable approach is the importance tasks before this research can be proceed for the next stage. Approach: This study focused on CAD data extraction approach to identify product information. CAD data referred as Computer-Aided Design (CAD) data extracted from the CAD drawing which contained the drawing of product that be produce by manufacturing. CAD data consisted of geometric and non-geometric data. Geometric data contained lines, curves and vertex. While non-geometric data include texts, colors and layers. The extracted CAD data were needed to generate the product information which is useful information for the machine in production field to produce the product for the manufacturing same as depicted in the CAD drawing. Basically, the product information consisted of product details such as length, thickness, wideness and radius of the product, processes information for the machine to process the product such as taper, cutting, drilling and punching. In addition, product information also contained type of materials for the product. Results: As a result, feature recognition is the most suitable approach can be applied for this research. Thus, the approach was selected to precede the next stage. Conclusion: Conclusion from the comparison among the approaches is in term of accuracy of extracted data is not accurate when the drawing is incomplete drawing or contains the noise such as unwanted lines or any shapes cross the object in the drawing.