See the hidden "factory within a factory" that consumes your capacity. Visual proof of why 10% rework costs far more than 10%.
See It In ActionWatch defective parts cycle back through the system, consuming capacity that should be making new product
Plant Managers, Production Supervisors, and Continuous Improvement Engineers trying to maximize line throughput.
Simulating how first-pass yield rate changes (e.g., 90% vs 98%) affect overall cycle times, station queues, and effective line capacity.
Calculate how much hidden capacity is unlocked by eliminating a rework loop, showing that a 5% yield increase can boost overall output by 20% due to reduced station blockages.
But it's actually worse: reworked items can fail again. With 90% FPY, you process an average of 1.11 units for every 1 that ships. That's 11% overhead just from the first rework cycle.
World-class FPY is typically 95% or higher, but "good" depends on your industry and process complexity. The key insight is that even small FPY improvements have outsized capacity benefits due to the multiplier effect of rework.
Simple formula: if FPY = 90%, you process 1/(0.90) = 1.11 units on average per shipped unit. But this compounds if reworked items can fail again. The simulation shows the full dynamic effect.
Common causes include operator error, equipment drift, material variation, unclear work instructions, and process capability issues. The simulation helps you see the impact before deciding where to invest in improvements.
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