What's your bottleneck worth per year?

Free tool · potential gain

What's your bottleneck worth per year?

Describe your line, then set where its OEE is today and where it could realistically get to after the improvements a simulation points to. You get an order-of-magnitude estimate of the yearly money in that gap — shown as an average and a range. It's an estimate, not a promise: RASQI measures the real number on your line.

Your line

Bottleneck cycle time Seconds per piece at your slowest station.

Profit per piece (USD) Contribution margin — extra pieces earn this.

Closest product type Sets benchmark starting points for the two OEE sliders — adjust them to your line.

Operating hours / day — 16 h ~8 h ≈ 1 shift · 16 h ≈ 2 shifts · 24 h = round-the-clock.

Working days / year Typical single-site year ≈ 250.

Current OEE — 58% Where the line runs today. Lower = more to recover.

Target OEE after improvements — 72% Realistic level once the constraint is fixed (world-class ≈ 85%).

The prize

—

estimated recoverable value per year (mid-case)

Range: — (conservative → full target OEE)

Bottleneck pace—

Current good output / year—

Extra good pieces / year (mid)—

RASQI license ($500/yr) pays back in—

OEE gap modeled—

Annual operating hours—

How this is estimated · sources

These figures are estimates, for reference only — not a measurement of your line, and not a guarantee. The preset OEE values for each product type are typical ranges drawn from the published benchmarks below — not values measured on your equipment. Your real result depends on your line's specific losses (which cause, where), and that is exactly what RASQI measures in a paired A→B run before you invest.

Gain = (3600 ÷ cycle time) × operating hours × (target OEE − current OEE) × profit/piece. The headline is a mid-case (~85% of the modeled OEE gap); the range spans a conservative first pass to reaching the full target.
Sources: OEE benchmarks — industry average ≈ 60%, world-class ≈ 85% (only ~6% of plants reach it): Lean Production — OEE, OEE benchmarks. Debottlenecking / DES throughput gains ≈ 3–15%: Discrete-event simulation for productivity (MDPI, 2026), Bottleneck management via DES. Working hours context: OECD — hours worked (worker-hours ~1,700/yr; a line's operating hours come from its shift pattern, used above). Theory: Nakajima, Introduction to TPM (OEE); Hopp & Spearman, Factory Physics.

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