Retrieved Features of 2D and 3D Models from CAD as Decision Support for Production Time/Cost Estimation

Predrag Cosic, Drazen Antolic
2011 Strojniski vestnik  
Very frequently a company has to respond quickly to some important requests for offers, generated for individual or batch production, for example: a great number of requested offers (requested prices ) either for production of products at once or for production of small batches (the offers for which are rarely repeated), frequent changes of priorities during production, short deadlines for delivery, market demands for bringing the prices of individual or batch production close to the prices of
more » ... ass production etc. Regression analysis as a possible approach to time/cost estimation is used for the estimation of requested results based on the previous stochastic results and experiments. On the other hand, the requests for classification consideration of the product shape and process sequencing are important conditions for designing a general model for the estimation of machining times. In fact, it means development of a technological knowledge base. The purpose of this paper is to establish possible connections between features (2D and 3D) and necessary machining time for manufacturing of products. Retrieving the required variables (features) from a 2D model involves a certain level of subjectivity concerning the number and size of the variables (manner of presenting dimension lines, number of dimension lines, number of views, tolerance fields). On the other hand, for the retrieving of the required variables from a 3D model a strictly defined procedure in the process of 3D model creation is needed. Estimation of production time is a necessary basis for cost estimation, cost reduction or TCE (Total Cost Estimation). As result of our analysis, we have created eight regression equations with the obtained index of determination, with the most important independent variables different for 2D and 3D model.
doi:10.5545/sv-jme.2009.186 fatcat:h4bgrfexebag5kyqi7kcc2i7fe