Products/Fluids

Fluids capability

Production & Machines

What happens between receiving gas and dispatching it, and the condition of the equipment that does it. Both measured, both costed, both feeding the same margin calculation as everything else.

Why production and maintenance sit together

A filling bay that is down is a production problem, a delivery problem and a customer problem in that order — but in most plants it is recorded as none of them. Fluids ties the machine to the job it was running, the hours it accrued, the maintenance that came due as a result and the cost of the spares consumed, so downtime is visible as money rather than as an anecdote.

Production

Three layers, one costed record

01

Filling and transfilling

The gas side of production, measured rather than assumed.

  • Reserve, fill and complete states on a live production queue
  • Donor and receiver gas transfer with a consumption log by order, cylinder, operator and date
  • Internal production jobs for top-up, transfer and buffer work not tied to a sales order
  • Gas cost resolved in priority order: manual entry, then filling cost, then purchased and landed cost
02

Item production

The manufacturing side, for plants that build as well as fill.

  • Separate item production queue with release, start, partial and complete transitions
  • Material consumption drawn from the inventory ledger with location tracking
  • A released bill of materials with planned-versus-actual variance per job
  • Production costing and work-in-progress absorption feeding item valuation
03

Traceability

Answering the recall question before anyone asks it.

  • Genealogy reporting forward and backward across the production chain
  • Assembled from tracking events, quality tests, certificates, inspections and movements
  • Any cylinder, gas composition, item or order can be traced from one screen

Machines

Equipment as a managed asset

📊

How much of the day a machine really ran (OEE)

Was it available, did it run at full rate, and was the output good — multiplied into one figure per machine, worked out from the usage log and the quality results rather than typed into a spreadsheet at month end.

🔧

How often it breaks, and how long it stays down

The average run between breakdowns and the average time to get it going again, split by the reason it stopped — with those reasons ranked biggest first, so the argument about what to fix is settled by numbers.

⏰

Preventive maintenance on run hours

Database triggers keep total run hours, accrued hours and next-due dates current from the usage log. Maintenance is scheduled by how much the machine has actually worked, not by a calendar reminder someone set once.

🧰

Maintenance log with parts

Breakdowns and planned work recorded with reason codes, and the spare parts consumed drawn directly from inventory so maintenance cost is real.

📅

Calibration register

Statutory and machine calibration tracked with validity windows and due alerts, so an instrument does not quietly fall out of certification mid-shift.

📶

Telemetry and threshold rules

An ingestion endpoint accepts machine data tagged as manual, PLC, SCADA or IoT sourced, with maintenance rules you set over it — a reading outside its band raises a task. The endpoint is live today; the plant-floor connector is the next step.

🗓️

Finite scheduling

A shop-load view showing what each machine is committed to, so a promised delivery date is checked against capacity rather than optimism.

Next

See what holds all of this together

Multi-company isolation, thirteen roles, module toggles per branch, and the checks that run before the application will even start.

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