Between 30% – 50% of women’s apparel online orders get returned. Why? Because the items simply don’t fit. Which is not very surprising considering the fact that the average retailer offers a fairly limited size range. Moreover, these standard sizes are based on standard proportions. And the reality is that the majority of customers don’t have standard proportions, or a standard height for that matter. Resulting in returns that are costing fashion brands nearly $400 billion annually. What’s even worse is that roughly 25% of these returns end up in landfills. 20 billion garments a year, to be exact.

If we can solve the fit issue, we can solve excessive returns, size exclusion, and the over piled landfills. If brands only produced what is actually ordered and they tailored it to the customer, then the customer would have no reason to return it. No returns, no waste and a more size inclusive fashion industry. Sounds great right?

So what will this future look like? Envision a future in which ordering a tailor made t-shirt or jeans is affordable, easy and quick.

From a customer perspective: It’s going to be just like online shopping now, only instead of ordering a size medium, you’ll just order a size ‘you’. There are a number of mobile 3D body scan apps available and they are becoming more accurate every day. Most apps only require a front and a side picture to create a highly accurate 3D avatar. Scan yourself, choose your options (colour, sleeve length, neck line etc.) and simply order. Your tailor made garment will be on your doorstep within weeks, maybe even days.

From a production perspective: Once a customer has placed their order, their order details (garment choice, customisations, and measurements) need to be automatically forwarded to the pattern development software. Then, a custom pattern needs to be generated for the customer. Then this pattern will be sent to the marker software, the final step before the actual physical production can start.

If automated tailoring creates inclusivity for customers and better margins for brands while having such a positive impact on the environment, then why on earth is no one doing this at scale?

Because scaling made to measure (MTM) production requires three things; accurate mobile 3D body scans, manufacturers who can work on a made to order (MTO) basis and parametric patterns. What is the status of these requirements? Mobile 3D body scans have been greatly improved since 2020, they now work on any mobile device. They are no longer the bottleneck. MTO production is increasing in popularity, because everyone now realises that the traditional way of mass producing stock is no longer viable. Parametric patterns are patterns based on variables, meaning that they can be transformed into a custom pattern for any and all shapes and sizes. These patterns have been around for a long time, but appear complicated to construct and require mathematical knowledge to edit. The latter is why many pilots on automating made to measure pattern making have failed. They tried it and it didn’t work. Hence the hesitation towards mass tailoring.

The remaining challenges for scaling MTM production from a pattern perspective are:

  1. Adequate parametric patterns
  2. Software to edit these patterns

1. Adequate parametric patterns

Constructing adequate parametric patterns doesn’t seem that complicated at first glance. Any pattern making technique starts with constructing a block, using a standard size. Why not simply replace the standard values with variables and you’re good to go?

Because it turns out that just replacing values with variables does not work out that well in actuality. This will result in patterns with shoulders that point upwards instead of downwards, scyes that bulge outwards instead of inwards, etc. Manual checks and corrections will remain necessary. Which is precisely what you want to avoid if we really want to fully automate MTM production.

So why will simply replacing values with variables result in odd patterns?

  • Existing pattern making techniques (roughly a century old) are built on ‘standard proportions’. But this type of pattern construction can easily result in errors if you enter measurements that deviate from those standard proportions (a narrow waist with wider hips for example).
  • A second problem of this method is the construction order of creating a block. An example: point D is determined on the basis of point C, point C was determined on the basis of point B and point B was constructed from point A. With real measures instead of table measures, there is a margin of error in each point. Because of this construction chain, in which each point depends on the previous point, those error margins are increasing. The last point in the list has become completely unreliable.
  • A third issue: the dimensions used in the construction of a block cannot always be measured reliably in reality. This is not a question of technology, it is a matter of unambiguous definition of measuring points. Take shoulder length as an example, a commonly used measure in block construction. This size only differs by a few millimeters per size, so it is very close. But in practice, on a real body, ‘the points’ shoulder tip and neck base, the start and end points of the measurement, are not defined to the nearest millimeter. The margin of error in this measure is of the order of a few sizes. Shoulder length is therefore unsuitable to use as a base for construction measures.

In short: traditional pattern drawing techniques cannot be used to construct adequate parametric blocks.

The good news is, this problem is solvable. In fact, it has been resolved. Parioli has developed a drawing technique especially designed for constructing patterns based on 3D measurements. With this technique it is possible to create adequate parameterised blocks. These blocks will work with any body proportions, they are based on measures that can be clearly defined and measured reliably.

But we are not there quite yet. Because to make a pattern of these blocks, they have to be edited. That is possible, but most pattern makers are not familiar with an interface that looks more like a programming environment than a pattern drawing tool.

2. Software to edit these patterns

The second challenge is therefore: can we create an environment in which pattern makers can edit a parametric block like they normally do, without using formulas, variables, goniometric functions, etc.? Or better yet: can we develop software that automatically converts traditional patterns to parametric patterns?

Yes, we can. How does that work?
It starts with a company’s traditional block. By traditional we mean non-parametric, a fixed block, based on company standard base sizes. We convert that block into a parameterised block. Then we fill

in the standard base sizes. The result is a block that looks exactly like the traditional block, but now contains parameters below the surface.

The pattern maker works with this block in a traditional manner. When the pattern is ready, the pattern maker exports the pattern to their library. There, this pattern is converted into a parameterised pattern on the basis of the corresponding parameterised block. This process can be compared to exporting a word document to a PDF. If a patternmaker wants to adjust the pattern after conversion, she/he uses the version before the export, makes the changes there, and then exports again. Soon, every pattern maker will be able to convert their traditional pattern to a parametric pattern, with just one click.

However, even when the custom pattern is automatically generated, the garment still needs to be produced. And mass producing custom garments is a whole different ball game. There are several manufactures, mostly smaller ones, that have adapted to this new way of manufacturing. Most emerging brands focus on small batch or on demand, local production. But it’s not just emerging brands that are moving to MTO. Innovative fashion giants like Gucci are already offering custom made garments that take about six weeks to produce. This is only the beginning, the market for custom garments is projected to take up 30% of all orders by 2025.

With an increasing demand of customers for less waste, a hassle free shopping experience, and more inclusive fits combined with retailers’ pressure for higher margins, automated made to measure production might just be the answer we’re all looking for. Imagine a future where we can all experience the luxury of bespoke clothing, right from the comfort of our own home. Tailoring for the many, not the few.

Sources:

https://medium.com/@parker_content/an-expensive-problem-for-the-online-fashion-industry-too-many-returns-abc441ed1b51

https://www.wsj.com/articles/the-high-price-of-fast-fashion-11567096637

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