ONO SIM
Run the line before you build it: parts per shift, the bottleneck, cost per part, and how long the investment takes to pay back. Runs in the browser.
See it on screen
Producing more has a price. The optimiser lays the trade-off out row by row; one click applies the one you want.
ONO SIMWatch the placement search work — the line visibly settles as it improves.
ONO SIMAsk in plain language. The assistant reads the line, runs the shift and answers with the measurement — not with an opinion.
ONO SIMWatch the shift or scrub it back: as parts flow across the line, you can see where the bottleneck piles up.
ONO SIMIn mixed production, cost splits per product: the part that holds the machine longer takes a larger share of the bill.
ONO SIMRobot cell layouts are built with the same model: three cells, 3,207 parts in a single shift.
ONO SIMGetting a quote for a machine is easy. Knowing whether that machine will pay for itself is the hard part. One more press, one more operator, or neither of those and simply a buffer in the right place — the answer depends on the whole line, not on the machine you are pricing. And finding out after the line is built is expensive.
ONO SIM builds your line on screen, runs a real shift through it, and reports the result in money. Cycle times, breakdowns, buffers, how far operators walk, conveyors, scrap — all of it is inside the model. What comes out is not just a part count: it is cost per part, profit per shift and per month, margin, and how many months the investment takes to return.
What It Does
- Run a shift and see what the line actually produces — the bottleneck machine, utilisation for every machine and operator, blocked and starved time
- Results in money: cost per part, profit per shift and per month, margin, capital required, payback period
- Optimisation that looks for the cheapest way to your target — “what does 900 parts a shift take?” or “what can I buy for this budget?”
- Placement search that lays machines out for the shortest transport and walking time, respecting keep-out zones and the areas you define
- Compare scenarios side by side and apply the one you want to the line in a single click
- Ask in plain language — “how is my line doing?”, “what should I improve first?” — and every answer comes from a run that actually happened
- Nothing to install: it runs in the browser, in Turkish and English
Uncertainty Is Part Of The Model
A real line does not produce the same number every shift. Cycle times vary, machines break, a part is scrapped, an operator walks between two presses. A single deterministic calculation does not describe that world — it gives you the average and hides the risk.
ONO SIM is a discrete-event simulator and every measurement runs several replications. Inside the model:
- Cycle-time variability, with loading and automatic running time defined separately
- Breakdowns and repairs (MTBF/MTTR), including time spent waiting for a maintenance technician
- First-pass yield — scrap leaves the line, so effective throughput drops the way it really does
- Buffers, blocking and starving
- Product mix and mould changeovers, run as campaigns or mixed
- Operators, crews and real walking distances; conveyors and manual carry
- A floor plan in metres — import your own layout as DXF or as an image
It Answers With A Decision, Not A Number
Numbers on their own do not mean much. What matters is which decision the number changes.
So every result in ONO SIM ties back to one: which machine is the bottleneck, what happens if you add another, how many months until it pays for itself, whether the same money is better spent on an operator. When a row in the comparison table is the one you want, one click applies it — and the line becomes that scenario.
You can ask the line assistant in plain language. Every answer it gives comes from a simulation that was genuinely run: the assistant does not offer opinions, it reports measurements.
Who It Is For
- Building a new line — test machine count, headcount and layout before any concrete is poured
- Improving an existing line — measure the bottleneck instead of guessing it, and see what the fix is worth in money
- Preparing quotations — put a model behind the capacity you promise a customer
- Making the investment case — have the answer to “how long until this machine pays for itself” ready in the presentation