The AI and automation wave is coming for leather. The choice is either ride it, or risk being washed away. Depending on who you talk to, automation is either the doom or the saviour of whatever sector they’re operating in.
In manufacturing, automation – usually just lumped together under the ever spreading AI umbrella – is often a bogeyman to skilled workers fearing they’ll be replaced and a boon to managers looking to tighten their bottom lines.
Like with any complex issue, the truth is somewhere in the middle. But whatever your fears or hopes for AI, the leather industry is at a crucial turning point which, if we navigate the coming years carefully, could transform our sector for the better.
When it comes to leather, automation has come slowly, when it’s come at all. While chemical mixing for tanneries which once relied on individual human expertise has long since become standardised and machine operated, many aspects remain almost archaic.
Areas like wet-blue grading where we still essentially rely on the same technology we did a thousand years ago – human eyes passing over hides and parsing defects.
This has baked in redundancies into our supply chain which cost all of us every day, with disputes over grading, multiple sorting steps between sites and a high rate of reject hides considered just the cost of doing business.
So what’s (so far) kept automation from our door?
The first thing preventing widescale automation and systems overhaul is also part of what makes the leather industry so great; the large number of smaller scale, independently owned tanneries around the world. Typically, the industries most likely to automate first are highly centralised in a few massive players with the kind of capital required to set up incredibly expensive new systems.
The automotive industry has always led the charge in automation for this reason and they’re already at the bleeding edge of the next wave. Just watch Figure’s humanoid robots walking onto the BMW production line to see how they’re embracing a brave new robotic world.
By contrast, our industry still relies on a diverse ecosystem of small, local players interacting with the giants.
Anyone who has spent any time walking around a tannery knows the expense required to spin up a fleshing machine, new drums or wringers and very few have pockets as deep as BMW to employ robotic employees.
And unlike automotives, we’re dealing with a soft material that doesn’t lend itself to the same kind of repetitive physical interaction. Automation struggles with human centric, highly physical and process driven tasks like those we specialise in.
But make no mistake, the wave of automation washing over so many sectors is lapping at our shores, it just won’t look like a robot arm reaching out and moving a defective hide, more like a robot eye catching and categorising that defect more efficiently than any human could.
This isn’t a hypothetical scenario; at Mindhive Global, we’re already making this possible through AI-driven quality assessment for leather manufacturing and directly addressing the redundancies discussed above.Â
Our automated grading systems help tanneries standardize quality assessment across their operations, processing up to 360 hides per hour – or as fast as they can reliably feed us wet-blue hides to grade.
These machines are designed to fit on top of your existing equipment, simply slotting over the back of ringers or over outfeed conveyors. An evening of downtime is all it takes us to actually drop it in place.
We have systems processing thousands and thousands of hides per day for some of the biggest producers out there, like JBS Couros, and we’re doing it with 91% accuracy – the match for any human master grader.
What this creates is an invaluable and previously non-existent resource for leather – verified, standardized data across the supply chain.
Verified hide data is standardized, objective quality information about leather hides, generated through AI-powered assessment and maintained throughout the manufacturing process.
This creates a single source of truth about hide characteristics, defects, and grades that can be trusted by all parties in the supply chain.
For example: A Brazilian tannery uses verified hide data to guarantee the quality of each pallet shipped to their European customers, eliminating the need for re-inspection and enabling precise fulfillment of specific grade requirements.
Because a customer has precise data at the wet-blue stage, they can start using this data to enable better choices downstream.
And while we’re focused on wet-blue currently, our finished leather system is in the final stages of R&D, unlocking even more potential for synergy up and down the supply chain.
Crucially, this kind of AI implementation isn’t about replacing any specific worker or job category – instead it works with graders, tannery managers and other operators to avoid mundane, repetitive work which costs everyone time and money.
In Mindhive’s case, our tools can provide efficiency gains on the margins for a leather maker, which compounded over thousands of hours can mean millions of dollars saved.
But for the leather industry writ large, where does the opportunity for automation come from, and how much is that progress worth?
As the industry consolidates and looks to find new efficiencies, it must also wrestle with important questions of how to maintain innovation for a new world. This is the time for us to both respect our traditions while securing our future.
The pace of progress in the underlying technologies powering AI is breathtaking and isn’t showing any signs of slowing down.
I won’t pretend to know exactly where we’re heading (and don’t trust anyone who does) but the only thing we can say for certain is that change is inevitable.
The AI and automation wave is coming. The choice is either riding the wave or being washed away.
