Considering widespread complaints regarding garment fit, it would appear that the geometric (or apple, pear, etc) references associated with body shape are difficult to mathematically quantify to improve garment fit. I would like to add clarification as to why…
While it seems obvious body shape would best be observed in 3D, with regard to garment fit body shape is best observed with 3D distractions removed and from a 2D perspective. Only from a pattern perspective, is the way in which fabric falls from a body best analyzed. Just as the aesthetic components of design are difficult to visualize on a 2D pattern and most effectively analyzed on a 3D body, the mathematical components of body shape (intrinsically linked to fabric grain) are difficult to visualize in 3D and best assessed on a 2D pattern. With respect to body shape, it can be generalized that shape reflects how the mid-torso area varies from the upper and lower body girths. This aesthetic observation, however, does not directly translate to pattern dimensions. Analyzing body shape in this manner only works on a small percentage of the population.
Fitting for body shape requires an intimate understanding of the complex interplay between the multitude of body girths, body lengths and fabric grain. It is this interplay which we call garment fit. With this in mind, I would like to offer a new definition of garment fit inclusive of this interplay, directed at automated fitting technologies, and upon which the foundation for improved garment fit can be built. When the interplay is not controlled (uncontrolled garment fit), as with traditional pattern engineering practices, garment fit is simply the RESULT of the interaction of a garment on a body with improved fit relying on try-on fittings to improve poor results. While such fittings can now take place in 3D virtual environments, this requirement is time consuming and inhibitive of full automation.
Computer automated fitting platforms are inhibited by data analysis incorrectly assessing body shape. The noted widespread dissatisfaction with garment fit is due to uncontrolled garment fit. Traditional made-to-measure (MTM) garments utilize standardized garment shaping while bespoke shaping relies on customized garment shaping dictated by the unique body shape of a individual.
Controlled garment fit is the the manipulation of fabric grain around a body in a predictable manner such that fabric grain and the distribution of that grain is predictable and controllable. While the topic of “desirable” fabric grain is subjective, the ability to quantify it with reference to a 3D Cartesian co-ordinate system permits it to be objectively measured and controlled. As it is the unique characteristics of the the woven or linked horizontal (weft) and vertical (warp) threads in a fabric that create the desirable flow and fall of fabric, this will continue to be a key component of garment fit even with 3D printed garments. Garment fit and fabric grain must always be discussed in tandem. Controlled garment fit is ONLY possible with body shape quantified.
Garment fit is a complex analysis of how an objectively measurable body interacts with the subjective, yet also measurable, aspects of garment design. Traditional pattern-engineering practices do not offer a means by which to quantify the aspects pertaining to garment fit. The Clone Block™ quantifies body shape at the pattern level so the interplay between body girths, body lengths and fabric grain can be measured.