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Articles

Analysis of body-to-pattern relationship using traditional pattern drafting techniques: implications for automated digital prototyping

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Pages 37-49 | Received 12 Feb 2023, Accepted 22 Jun 2023, Published online: 10 Jul 2023
 

ABSTRACT

Digital prototyping was extensively employed in the clothing industry during the Covid-19 pandemic. Digital Prototyping can optimise the level of accuracy, where the engineered fit will be close to the accurate fit. However, digital prototyping will not succeed without applications of the underlying theories of manual pattern development. This paper aims to critically review the traditional pattern drafting techniques, including ease allowances, and transfer that tacit knowledge to 2D CAD pattern developments. Five established pattern drafting methods for women’s upper torso garments were selected and examined to check the reliability of body–to–pattern relationship. However, none of the techniques has accurate clothing fit, which implies that the current pattern drafting techniques do not explicitly consider the body-to-pattern relationship. Further, it was determined that traditional pattern drafting techniques could not directly translate to automated digital drafting. The key findings of this experimental research support future developments in automated digital prototyping.

Acknowledgements

This work was supported by the Senate Research Committee (SRC) long-term grant 2021–2023 from the University of Moratuwa, Sri Lanka. Special thanks to Gerber AccuMark and Browzwear VStitcher solutions providers- Head Offices and Sri Lankan agents for providing the software support for this research study.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

This work was supported by Senate Research Committee (SRC) Long Term Grants; 2021–2023, University of Moratuwa, Sri Lanka: [Grant Number SRC/LT/2021/09].

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