My people on the floor are not going to work with a tablet.

Nor do they have to if it does not work with gloves or in the noise. We design it with them: big buttons, scanning instead of typing, as few actions as possible. If it does not work on the floor, it does not work, full stop.

Everything we make is bespoke, every order is different.

The order is different, the steps are not: enquiry, costing, production planning, production, hours, actual costing. Precisely with bespoke work the actual costing is gold, because that is where the margin leaks away. The unique craftsmanship remains people’s work.

We have only just bought an ERP, surely that should do it?

An ERP records; it rarely forecasts and connects by itself. We build on your ERP (AFAS, Ridder iQ, Exact) and fill the gaps: the job sheet in hand, the drawing attached, the costing that does the maths. No second system next to it.

Won’t this cost more than it brings in?

The workshop is easy to measure: downtime, lead time, hours per order, margin after actual costing. We agree up front what we measure and start small. If the first step does not pay off, we stop. And we will tell you that, even if the answer is disappointing.

Feature · Production & workshop

Two in three business owners are looking for staff. In the workshop that means: the same work with fewer hands.

In the workshop, time is the only real product. A machine standing idle, an order in the wrong place, a drawing that was just not the latest version: it all costs hours you never earn back. And there are fewer and fewer people around to pick up the slack. The question is no longer “how do we do it faster”, but “how do we get by with the people we have”. That is where automation helps, not by replacing people, but by no longer making them search, retype and wait.

// A report from a fictional metalworking company with 34 employees, five CNC machines and a schedule on a whiteboard next to the coffee machine. The company is fictional, the situations are real: we run into them again and again.

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Sound familiar?

The schedule hangs on a whiteboard; whoever works from home or is out on the floor cannot see it.
Job sheets are paper: hours get retyped in the evening, or not at all.
The machinist is looking for the latest version of the drawing; there are three lying around, and one is wrong.
A machine breaks down; the part still has to be ordered and takes three days to arrive.
The costing for a quote is half an hour of puzzling in Excel, and the previous ones are no longer right.
Nobody knows exactly what an order ended up costing; the actual costing never gets done.
New employees learn the job by shadowing; when the experienced hand leaves, the knowledge leaves with them.
The question “can this still be squeezed in this week?” is answered on gut feeling, not on the real capacity.

What usually runs here

The software we come across here most often. It does not have to go; we build around it and in between.

AFAS ERP, hours, productionRidder iQ ERP for manufacturingExact voor Productie ERP and stockKing / Kingfisher orders and productionTrello / planning whiteboards work allocationCAD/CAM drawings and machine codeMES / machine integrations machine data and OEESimplicate / Teamleader hours and projectsSharePoint / network drive drawings and documentsExcel quote costing and actual costingBarcode scanners job sheets and materials

// the same working day, twice

A day in production & workshop: now and next

On the left, the day as it usually runs now. On the right, the same day once the dull parts are automated and AI does the groundwork. Watch what changes: not the people, but where their time goes.

// how it goes nowWithout AI

07:00Production planningPuts the schedule on the whiteboard. Whoever is off sick or working off-site calls to ask what he should be doing.
08:30MachinistLooks for the drawing on the network drive. Three versions; he picks the newest folder, which turns out to be from last week.
10:15MachineThe CNC stops on a worn part. Nobody had seen it coming; the replacement takes three days to arrive. The machine stands idle.
11:30SalesA customer asks for a quote. The costing is half an hour of puzzling in an old Excel file; the material prices are months old.
13:45MachinistWrites his hours on a paper job sheet. It disappears into a tray and might get retyped on Friday.
15:30Production planning“Can that rush order still fit in?” Answer on gut feeling: “Yes, that should work.” Nobody knows the real capacity.
17:00Managing directorWants to know what order 2412 cost. There is no actual costing; the margin is an estimate.

// how it will goWith AI and automation

07:00Production planningThe schedule is digital: everyone sees on their phone or screen what is assigned to them today, including whoever works from home or off-site.
08:30MachinistScans the job sheet; the correct, latest drawing opens straight away. Old versions can no longer be opened, only viewed in the archive.
10:15MachineThe machine had been showing an abnormal pattern for days; the system had proposed maintenance and the part was ready and waiting. Twenty minutes of downtime instead of three days.
11:30SalesThe quote costing is ready: materials at current prices, hours based on comparable orders from the past. Check and send.
13:45MachinistBooks his hours on the job sheet in the app, with one tap per task. In the evening nobody has to retype anything.
15:30Production planning“Can that rush order fit in?” The system shows the real capacity and what would slip as a result. The decision is backed by numbers, not a guess.
17:00Managing directorOrder 2412: booked hours, materials and margin sit next to the costing. He sees straight away where the friction was and where the next quote needs to be sharper.

Where AI makes the difference here

Per use case: what the automation does, what a person keeps doing, and whether it is proven or still promising. We say which one honestly.

01proven

Digital job sheet and hours

The paper job sheet becomes a scan-and-tap in an app: start a task, book materials, record hours. Everything goes straight into the ERP and into the actual costing.

Still human: does the work and taps; the admin fades into the background.

Saving time Working more efficiently

02proven

Always the right drawing

Every job sheet automatically carries the latest, released version of the drawing. Old versions are locked, so nobody makes the wrong thing by accident.

Still human: releases the drawing; after that nothing can go wrong with versions.

Better security Working more efficiently

03promising

Faster quote costing

For a new enquiry, the AI proposes a costing based on comparable orders from your past and current material prices.

Still human: the estimator assesses and adjusts; experience stays in the lead, the maths does not.

Saving time Handling more with fewer people

04promising

Maintenance before the breakdown

Machine data (running hours, vibrations, error codes) is monitored; an abnormal pattern leads to a maintenance proposal before the machine stops. This requires machines that supply data.

Still human: the maintenance team schedules the maintenance and keeps critical parts in stock.

Better security Handling more with fewer people

05proven

Planning everyone can see

The schedule moves from the whiteboard to a screen that keeps up: who does what, what the capacity is, and what slips when a rush order comes in.

Still human: the production planner plans and decides; the system works out the consequences.

Working more efficiently Handling more with fewer people

06proven

Actual costing without extra work

Because hours and materials are booked at the source, the actual costing rolls out by itself: what did the order really cost, and how does that compare with the quote?

Still human: reads the margin and adjusts the next quotes.

Working more efficiently

2 in 3

Dutch business owners faced staff shortages in 2025; in industry that leads to extra pressure on the shop floor. [1]

67,800

open technical vacancies were counted in the Netherlands at the end of 2025; the labour market for technical staff was tight to very tight in every region. [2]

±25%

of companies invested more in automation because of the shortage; others simply limited production instead to what the available hands could manage. [3]

Honestly: what AI does not do here

Predictive maintenance sounds great, but it only works if your machines supply data. If they do not, it starts with simple sensors or with smart maintenance scheduling; no magic box on a machine from 1998.
The quote costing is a proposal based on your past. For genuinely new work you have never done before, it is still guesswork; there, the experience of your estimator is irreplaceable.
A digital job sheet stands or falls with use on the floor. If it does not work with gloves on, or takes more taps than the piece of paper, nobody will use it. That is why we build it with the machinists, not for them.
Automation does not replace the hands you are missing one for one. It removes the searching, waiting and retyping, so your skilled people get to do their actual trade. That is the gain, and it is real.

The objections we hear — and whether we can close them off

We looked them up and heard them from clients. For each objection we say whether it is really solvable, partly solvable, or a risk that stays and that you accept knowingly.

Can it be closed off: partly. Often more than you think, and where it is not possible we start with the process around them: job sheets, planning, drawings, actual costing. We do not promise predictive maintenance on a machine without data; then we say so honestly and choose a different way in.

// how we start, the first thirty days

01Week 1: core session in the workshop. We follow one order from enquiry to actual costing and count the searching, waiting and retyping.
02Weeks 2 and 3: digital job sheet with time booking and the right drawing attached, built together with the people on the floor.
03Weeks 3 and 4: the schedule from the whiteboard to a screen everyone can see; actual costing automatically from the booked hours.
04Week 4: measure. Retyped hours, version errors, lead time, margin per order. Only then predictive maintenance or costing AI.

// what it costs and how it works

First the free AI scan, then a core session on your floor (a half-day of 4 hours, €596 excl. VAT and travel costs) with a core report and an honest go/no-go. We build on a project basis with fixed hours: €110 per hour for straightforward work, €165 for complex development.

More hours only with your written approval. If we cannot deliver, you pay nothing for what was not delivered.

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Want to know what this means for your production & workshop?

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