While digital product creation promises rapid turnarounds, and revolutionary ways to shorten product lifecycles, significant bottlenecks exist in the material digitisation process. Machine learning could offer new ways to automate and accelerate the creation of digital materials at scale.
COVID turned digital materials & 3D assets into survival tools, but the Boston footwear giant could be a guiding light towards what's going to be possible with digital product creation post-pandemic.
Why the right 3D environment could be the key to unlocking the potential of end-to-end digital workflows, and to powering on-demand production.
As fashion moves further into digital product creation, digital materials are increasingly in the spotlight. But creating them has been a more complex, time-consuming process than most designers can afford. Machine learning could be about to change all that.
The digitisation of material sourcing is a matter of efficiency and business continuity for large enterprises. For micro-brands and emerging designers, it's a door to a whole new world.
Combined, digital materials and machine learning could offer a route to more sustainable research and development. Provided the playing field is kept even.
Digital materials are essential to digital product creation, which means it's vital they're built with creative designers in mind. But what does that actually mean?
As the popularity of digital materials explodes, competing commercial interests could get in the way of realising their true benefits. This article considers a different, more democratic approach to digitisation.
Building a digital product creation workflow relies on digital materials that behave identically to their physical counterparts. The technologies are in place to make this happen, but as an industry we still need to slot the pieces together.
As the material most synonymous with fashion's history, cotton's future could herald a fundamental shift in the industry’s approach to digital materials.