Most companies that scale a production prepare for the wrong failure.They usually budget for more machines, more people, more square footage.Essentially, they budget for capacity problems.
What they forget is that scaling doesn’t strain an operation evenly.It finds the weakest assumption a company is running on and breaks that first.Not knowing what that weakest assumption is or not knowing the order things fail in is what ends up costing scaling businesses more than the scaling itself.
Here’s the order as we lived it: The first thing to break wasn’t visible as a failure at all We ran on the same off-the-shelf software for roughly nine years and for most of that time it worked fine.It worked because we were small enough and institutional knowledge could live in people’s heads.Someone just knew which builds needed extra attention, which handoffs needed a heads-up, and which shortcuts were safe and worth taking.
That was efficient until the headcount and volume outpaced how fast this knowledge could transfer from one person to another.This is the kind of failure nobody catches early, because it doesn’t look like a failure.It looks like normal variation in day to day operations.
Same job handled slightly differently by two different people, a decision that used to be automatic now needing a slack thread.All these are seen as the aforementioned variation.And by the time you can point it out as a problem, you’ve been losing consistency for months.
We were well into that stretch before we had a name for it.The second thing to break was the part everyone actually noticed The tooling failure is the one companies usually notice because it breaks a lot of things around it at once.We hit this failure when production hit 5000+ parts a week.
The same software that worked for many years started failing and a support ticket or feature request couldn’t fix it.Tracking a build at its exact stage got difficult.Questions like “is this in post processing?”, “Is it ready for QC and dispatch?” started coming up more frequently.
Quantity tracking got trickier and quality checks got more confusing.The gaps in the off-the-shelf system had always been there, only now the scale was exposing them.The instinct at that point may be to go shop for a better software; we didn’t, though.
We built our own, but only after understanding why buying wouldn’t solve these issues for us.The problem wasn’t a missing feature.It was that no tool, bought or built, was going to work until we could describe our own process precisely enough to hand it to one.
That meant going back to the first failure and actually fixing it: documenting everything, stage by stage and handoff by handoff.Documenting everything that had only ever lived in someone’s head.Every step had to be named.
Every piece of information had to be defined clearly enough for a system to use.And this had to be done without it becoming so granular that it overwhelmed the people running it day to day.Once this was done building the software made sense.
The logic had always existed, we’d just never written it down.What that sequence bought us Building in-house means slower delivery than buying off the shelf, and it means owning a piece of software indefinitely.Someone on the team now has to be expert enough in our operations to keep translating what the floor needs into what the software does.
That’s the real cost of building in-house, and it doesn’t go away.What it didn’t cost us was the machines.Every fix in this story – the documentation, the software, the handling of 5000+ parts every week – happened without adding a single new printer.
Handling a bigger scale without adding machines is only possible if you actually understand your bottlenecks.Add machines without that understanding and you’ve just bought the same issues at a bigger scale.What this means if you’re scaling now The order matters more than any individual fix.
Assume your institutional knowledge isn’t scaling as fast as your volume, even before anything looks broken.Start writing it down before you are forced to.And when something does start to break, resist diagnosing it as a software or hardware problem before you’ve ruled out a knowledge problem wearing a software costume.
Most tooling failures are really “we never wrote down what the tool needed to know” failures.Only once you can describe your process precisely does “build vs buy” even become a real question, and by then the answer is obvious.Scaling won’t hand you one big, obvious failure.
It will hand you a sequence of small ones, in a predictable order.The companies that scale well aren’t the ones with better tools, better software, or more machines.They’re the ones who know which sign they’re looking at before they spend money solving the wrong one.
Cinerita Andrades is Head of Manufacturing Engineering, Makelab Subscribe to Our Email Newsletter Stay up-to-date on all the latest news from the 3D printing industry and receive information and offers from third party vendors.Print Services Upload your 3D Models and get them printed quickly and efficiently.Powered by FacFox Powered by 3D Systems Powered by Craftcloud Powered by First Mold Powered by Xometry 3DPrinting Business Directory 3DPrinting Business Directory
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