Machine states, piece counters and downtime enter the system straight from the controllers. The operator confirms the operation on a screen at the machine, and the planner and accounting see the same thing right away.
The operator writes pieces and downtime on a job card, someone types them into a spreadsheet the next morning. You know the shift's result a day later, when nobody remembers why the machine stopped.
The salesperson calls the shift manager to tell a customer which stage their order is at. The manager walks over to check.
The batch number is on the label, but the raw material, machine and operator mean searching the QC binder and job cards. The answer to the customer takes days.
The scope depends on the machines: one setup for CNC work centers, another for a food line with batches. Controllers and SCADA stay.
Three years ago features like these needed a data science team. Today language models read emails, documents and photos, and we build them into the system we make for you. Below is what makes sense in this solution. A person approves, AI prepares.
The model learns from downtime history, alarms and machine parameters. When a pattern resembles previous failures, it warns maintenance before the machine stops.
Example a rising number of micro-stops on the press over the last three shifts → a maintenance ticket with a list of similar cases
A photo of a handwritten job card or measurement report becomes data to confirm. Useful at machines with no screen.
Example a job card photo with "feeder jam 20 min" written on it → downtime with a reason on the order, ready to approve
The manager asks in plain language, the answer comes from machine and order data.
Example "why did work center 4 make less than planned yesterday?" → three downtime events with reasons and durations
AI groups the week's QC non-conformances by machine, operator, raw material batch and shift. The process engineer decides.
Example 12 dimensional non-conformances in a week → all from one batch of bar stock, a proposed supplier complaint
We do not replace controllers or rebuild SCADA. We read what the machines already send and hand the data to the ERP and planning.
We start with the few machines that hurt most. The rest of the floor joins once the first work center is running.
You have the diagnosis, we build the solution. Web applications, B2B portals and automations for companies without a large IT department. Today a system can read emails and documents, suggest decisions and answer customers on its own, so we build that in from the first version, not as an add-on a year later.
We agree scope, price and dates upfront, show progress every week, and the code and data stay yours.
You tell us which machines you run and what goes on job cards today, we tell you which work center to start with.
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