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Article
Publication date: 25 July 2008

Sungshik Yim and David W. Rosen

The purpose of this paper is to present an information model (ontology) for design‐for‐manufacturing (DFM) problems, where parts are to be manufactured using an additive…

Abstract

Purpose

The purpose of this paper is to present an information model (ontology) for design‐for‐manufacturing (DFM) problems, where parts are to be manufactured using an additive manufacturing process. DFM problem formulation is often challenging since the formulation step requires both design and manufacturing process knowledge. The ontology also captures some relationships that model how that manufacturing knowledge applies to part designs. The ontology is implemented and serves as a repository of DFM problems that are available for reuse.

Design/methodology/approach

The ontology is encoded using a description logic (DL) known as ALE. Using this ontology, a designer can retrieve archived DFM problems that are similar to a problem being formulated. DLs are a subset of first‐order logic that have been used for information modeling in several application areas, including engineering information management. They are used typically to construct classification hierarchies that can be efficiently searched.

Findings

The paper demonstrates that the DL model is correct by showing that the classification hierarchies that are computed match our DFM ontology. Retrieval of DFM problems is demonstrated using a prototype implementation of our ontology. Examples are taken from the area of design for manufacture using the stereolithography process.

Research limitations/implications

The domain of the ontology is limited to additive manufacturing processes. Only DFM problems related to the determination of design parameters (e.g. dimensions) were within the scope of this work.

Originality/value

No ontology for DFM problems has been presented previously. Implementation of the ontology using DL is also original.

Details

Journal of Manufacturing Technology Management, vol. 19 no. 6
Type: Research Article
ISSN: 1741-038X

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