@article {18813,
	title = {An Application of Distributed Solid Modeling: Feature Recognition},
	volume = {ISR; TR 1994-82},
	year = {1994},
	month = {1994///},
	institution = {Institute for Systems Research, University of Maryland, College Park},
	abstract = {The availability of low-cost computational power is a driving force behind the growing sophistication of CAD software. Tools designed to reduce time-consuming build-test-redesign iterations are essential for increasing engineering quality and productivity. However, automation of the design process poses many difficult computational problems. As more downstream engineering activities are being considered during the design phase, guaranteeing reasonable response times within design systems becomes problematic. Design is an interactive process and speed is a critical factor in systems that enable designers to explore and experiment with alternative ideas during the design phase. Achieving interactivity requires an increasingly sophisticated allocation of computational resources in order to perform realistic design analyses and generate feedback in real time.<P>This paper presents our initial efforts to develop techniques to apply distributed algorithms to the problem of recognizing machining features from solid models. Existing work on recognition of features has focused exclusively on serial computer architectures. Our objective is to show that distributed algorithms can be employed on realistic parts with large numbers of features and many geometric and topological entities to obtain significant improvements in computation time using existing hardware and software tools. Migrating solid modeling applications toward a distributed computing frame-work enables interconnection of many of the autonomous and geographically diverse software tools used in the modern manufacturing enterprise.<P>This has been implemented on a network of SUN workstations using the ACIS solid modeler and the NIH C++ class library; inter-processor communication is handled with TCP/IP- based network communication tools.},
	keywords = {Distributed computing, feature recognition, feature- based modeling, multiprocessor solid modeling, Systems Integration Methodology},
	url = {http://drum.lib.umd.edu//handle/1903/5552},
	author = {Regli,W. C. and Gupta, Satyandra K. and Nau, Dana S.}
}
