language: en

An Application of Distributed Solid Modeling: Feature Recognition

William C. Regli
National Institute of Standards and Technology Manufacturing Systems Integration Division
Building 220, Room A-127 Gaithersburg, MD 20899
regli@cme.nist.gov
Satyandra K. Gupta
Mechanical Engineering Department Institute for Systems Research University of Maryland
College Park, MD 20742 USA
skgupta@src.umd.edu
Dana S. Nau
Computer Science Department Institute for Advanced Computer Studies Institute for Systems Research University of Maryland
College Park, MD 20742 USA
nau@cs.umd.edu Available as CS-TR-3375, UMIACS-TR-94-126, ISR-TR 94-82.

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. 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 framework enables interconnection of many of the autonomous and geographically diverse software tools used in the modern manufacturing enterprise. 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: Multiprocessor Solid Modeling, Feature Recognition, Feature-Based Modeling, Distributed Computing.

[This work was supported in part by NSF Grants IRI9306580, DDM-9201779, EEC 94-02384 and a forgivable loan from General Electric Corporation awarded to the first author. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.]

[Also affiliated with: Computer Science Department and Institute for Systems Research, University of Maryland, College Park.]