Enhancing CAD/CAM systems communication by understanding engineering machine drawings

The design process, especially that of mechanical products, involves translating the designer's ideas into spatial information describing the product. Prior to the CAD/CAM era this was done on the drafting board. With current technology, designers are capable of creating three dimensional models directly in the database. In both cases, however, spatial information is created by using visual rather than coded representation, as this is the most natural way for humans to express geometric concepts. The CAD system is responsible for interactively converting the design into its specific coded spatial description, which may, in turn, be redisplayed and manipulated.Advanced CAD/CAM used by many companies are often dissimilar, primarily because each system is most productive at one specific application. Nevertheless, to maintain overall productivity within the company and to communicate among companies, systems need to exchange product data without the need for costly, error prone reinput. A similar problem arises when it becomes necessary to divert into any CAD/CAM system the flow of hard-copy design data from suppliers and subcontractors. Moreover, Most CAE users have discovered a wide gap in their ability to apply CAE power to existing designs and products, because their manually prepared drawings are not in the database.Currently, communication among various CAD/CAM systems is carried out by means of a neutral format translator, in which the internal format of the sending system is translated by a preprocessor into a neutral data format. This format, in turn, may be translated into the format of any other CAD/CAM system, using the postprocessor of that system. The Initial Graphics Exchange Specification (IGES) is a widely accepted neutral file format for CAD/CAM system communication.Current research efforts are aimed at augmenting the domain of the "IGES function" so as to include the originating system's human readable output as an additional possible source to be viewd, understood, and translated into IGES format. A scheme is presented for carrying out this task that employs elements of machine vision, along with syntactic and geometric analysis.The input to the high level vision and analysis processes is the outcome of preprocessing. This early vision, low level stage consists of scanning the original document, thresholding, edge detection, and raster to vector operations. The problem of functional line classification into geometry and annotation entities is addressed, and the key role played by dimensioning is discussed. Dimension-sets and their primitive components are defined. Geometric, non syntactic pattern recognition techniques are devised to detect object-dissimilar components, such as arrowheads and text. A learning mechanism that deduces specific geometric parameter values for a given drawing and decreases the rate of false identifications is introduced. A dimensioning language based on customary standards and defined in terms of a two dimensional web grammar is used to detect object-similar dimension-set components by predicting their syntax and confirming their spatial orientation relative to the previously identified components. Finally, identification validation of entire dimension-sets and appropriateness of the overall dimensioning in simple cases are considered.