A constructive approach toward a parametric pattern-making model

Abstract

The made-to-measure technique is created to accommodate the requirement of mass customization. A parametric design in various made-to-measure techniques is considered as a significant solution, however, variant programming as a parametric design has its limitation in principle, scope and operation. This paper proposes a novel approach based on variable and geometric constraint to generate a parametric pattern-making model. In an interactive and graphical environment, at the same time that geometric entities are created, geometric constraints between entities are identified, constructed and added into a constraint graph which represents the sequence of construction and constraints, thus it also holds a set of rules and knowledge in pattern-making. To reduce the cost of time and space, the reversible graph of a constraint graph is introduced to represent a dimension-driven process. Parametric modeling of a pattern is illustrated with the rear panel of a women’s jacket in this paper. First of all, a constraint graph and reversible graph are expressed using an adjacent constraint list and an adjacent dimension-driven list respectively, then pattern-making process is stored in an adjacent constraint list, when a set of specific values of variables or the properties of an entity is altered, the properties of the relatively constrained entities are recalculated and updated by using an adjacent dimension-driven list and constraint solving algorithm. The experiments show that the approach has the advantage of the interactive construction of a pattern and convenient operation similar to conventional garment CAD, and the implementation of the dimension-driven process and entity-edited function of parametric pattern model.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 27 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.