engineering & design
Semantics for Digital Engineering Archives Supporting Engineering Design Education
Regli, William C. (Drexel University) | Kopena, Joseph B. (Drexel University) | Grauer, Michael (Drexel University) | Simpson, Timothy W. (Penn State University) | Stone, Robert B. (Oregon State University) | Lewis, Kemper (University at Buffalo - SUNY) | Bohm, Matt R. (Oregon State University) | Wilkie, David (Drexel University) | Piecyk, Martin (Drexel University) | Osecki, Jordan (Drexel University)
This article introduces the challenge of digital preservation in the area of engineering design and manufacturing and presents a methodology to apply knowledge representation and semantic techniques to develop Digital Engineering Archives. This work is part of an ongoing, multiuniversity, effort to create cyber infrastructure-based engineering repositories for undergraduates (CIBER-U) to support engineering design education. The technical approach is to use knowledge representation techniques to create formal models of engineering data elements, workflows and processes. With these formal engineering knowledge and processes can be captured and preserved with some guarantee of long-term interpretability.
Modeling Design Process
Takeda, Hideaki, Veerkamp, Paul, Yoshikawa, Hiroyuki
This article discusses building a computable design process model, which is a prerequisite for realizing intelligent computer-aided design systems. First, we introduce general design theory, from which a descriptive model of design processes is derived. Second, we show a cognitive design process model obtained by observing design processes using a protocol analysis method. In the computable model, a design process is regarded as an iterative logical process realized by abduction, deduction, and circumscription.
Knowledge-Based System Applications in Engineering Design: Research at MIT
Sriram, Duvvuru, Stephanopoulos, George, Logcher, Robert, Gossard, David, Groleau, Nicholas, Serrano, David, Navinchandra, Dundee
Advances in computer hardware and software and engineering methodologies in the 1960s and 1970s led to an increased use of computers by engineers. AI techniques, in particular the knowledge-based system (KBS) technology, offer a methodology to solve these ill-structured design problems. In this article, we describe several research projects that utilize KBS techniques for design automation. These projects are (1) the Criteria Yielding, Consistent Labeling with Optimization and Precedents-Based System (CYCLOPS), which generates innovative designs by using a three-stage process: normal search, exploration, and adaptation; (2) the Concept Generator (CONGEN), which is a domain independent framework for conceptual or preliminary design; (3) Constraint Manager (CONMAN), which is a constraint-management system that performs the evaluation and consistency maintenance of constraints arising in design; (4) the distributed and integrated environment for computer-aided engineering (DICE), which facilitates coordination, communication, and control during the entire design and construction/manu-facturing phases; and (5) DESIGN-KIT, which can be envisioned as a new generation of computer-aided engineering environment for process-engineering applications.