Quick calculators and advanced simulators for manufacturing & production to make data-driven business decisions.
Sector context
An SMB manufacturing operator juggles three tensions at once: how much raw material to buy without freezing capital, how much capacity to reserve for runs that haven't been confirmed yet, and how much operational variability to absorb without spiking unit cost. A single unplanned downtime hour can wipe out a shift's margin, and a miscalculated setup turns a profitable run into a break-even one. The simulators in this section model those decisions with concrete numbers: expected output, tolerable scrap, maintenance policy, and the real cost per finished unit.
Key metrics
Indicators an SMB operator in the sector should know before modeling decisions.
OEE (Overall Equipment Effectiveness)
Availability × Performance × Quality. 70% OEE is reasonable for an SMB; world-class is 85%, but it requires investment in sensors and predictive maintenance.
Scrap rate
Percentage of produced units discarded for defects or waste. Counts both lost raw material and machine-time spent on a piece that won't sell.
Cost per produced unit
Raw materials + direct labor + energy + allocated fixed costs per unit. When it climbs and prices don't, margin evaporates.
Changeover time
Minutes between the last good piece of run A and the first good piece of run B. Cutting it by 30% usually frees more capacity than buying a new machine.
MTBF (Mean Time Between Failures)
Average hours between unplanned stoppages. Tells you whether preventive maintenance is protecting capacity or just logging failures.
How to pick the right simulator
If your question is short-term operational (how many units can I produce this week with current capacity), start with the industrial production simulator. If the question is how much raw material to buy and on what cadence, open the raw-material simulator to avoid both stockouts and over-inventory. If scrap percentage or inconsistent quality keeps you up at night, jump to the quality and waste simulator. And if unplanned downtime is breaking the operation, the preventive maintenance simulator helps you financially justify the service frequency that actually pays off.
Practical example
Hypothetical case in US dollars. Plug your real numbers into the simulator to validate your own scenario.
An SMB metalworking shop runs two presses at a current unit cost of $4.20 USD. They produce 1,200 units per shift with 6% scrap and 62% OEE. The operator enters those numbers into the simulator, sets the target to bring scrap down to 3% and lift OEE to 70%. The result shows unit cost dropping to $3.60 USD and effective production climbing to 1,344 units per shift, i.e. 144 additional units × $7 USD price = $1,008 USD of extra margin per shift. The required investment in operator training and a die change pays back in 14 shifts.
Common modeling mistakes
Traps we see when reviewing sector planning. Avoid them before closing your own model.
Counting scrap only from raw material
Scrap also consumes machine-hours and labor-hours. Adding only the discarded piece cost understates the impact by 40–60%.
Assuming a constant setup
A 100-unit run with a 90-minute setup is not comparable to a 1,000-unit run with the same setup. The simulator must read the actual batch size, not an annual average.
Ignoring off-line quality time
If inspection happens in another shift, the latency between defect and correction invalidates the whole lot. Model inspection as consumed capacity, not zero cost.
Confusing theoretical with effective capacity
The nameplate says 1,500 pieces/hour; in real operation, with shift changes, breaks, and micro-stops, it's 950. Use the measured number, not the factory one.
Scope and limitations
These models assume batches with homogeneous composition and don't project the effect of drastic product-mix changes. For capex decisions (buying new equipment), always pair them with the cash flow simulator to verify payback under realistic conditions. They don't replace certified industrial engineering when operational safety risks are involved.
Start here
The simulators with the most adoption in the sector. Each tackles a different business question.
Industrial production
Models real capacity, scrap, and unit cost for planned production runs.
Quality and waste
Quantifies the full scrap cost (raw materials + machine-hours + labor-hours).
Raw materials
Purchase cadence, lead time, and safety stock so you don't freeze cash.
Preventive maintenance
Justifies service frequency based on the cost of unplanned downtime.