Factory Yield Tracking: 2% Waste Per Batch Across 100 Batches = 20% Annual Loss

The Normalized Scrap Problem#

Most factories normalize scrap: "2-3% is normal for this process." They accept it. But accepted waste is still cost. A manufacturer producing circuit boards might have 3% defect rate because: (a) 1% from unavoidable environmental factors (dust, temperature). (b) 2% from preventable issues (operator error, machine drift). They treat all 3% as "normal" and price accordingly. But if they could eliminate the 2% preventable scrap, they'd improve margin by 2% of COGS, which is huge.

Why Yield Tracking Is Hard#

Factories track final yield (units produced / units expected). If 100 units are expected, 97 are produced, yield is 97%. But they don't track why: Was it material batch A, operator X, machine Y, setup Z? Without granular data, patterns are invisible. Worker A might have 5% scrap, Worker B might have 1%, but management doesn't know because they don't track by operator.

AskBiz: Yield Tracking by Batch, Material, Operator, Machine#

AskBiz logs: (1) Batch ID and expected yield. (2) Actual units produced. (3) Units scrapped and reason (material defect, machine error, operator error, environment). (4) Operator name, machine, material lot. Weekly report shows: (1) Overall yield (95.8%). (2) Yield by operator (A: 96%, B: 98%, C: 92%). (3) Yield by machine (Machine 1: 97%, Machine 2: 94%). (4) Yield by material lot (Lot-2024-0510: 98%, Lot-2024-0511: 93%). (5) Scrap reasons (40% operator error, 30% machine drift, 20% material defect, 10% environment). From this, the factory identifies: "Machine 2 has 94% yield (3% below target). Likely misalignment or worn tooling. Schedule maintenance." Or: "Operator C has 92% yield. Provide coaching on quality control." Or: "Material Lot-2024-0511 had 7% scrap. Check supplier QC."

Continuous Improvement Cycle#

Track → Identify issue → Fix → Measure improvement. AskBiz enables this. Week 1: Identify Machine 2 issue. Week 2: Maintenance done. Week 3: Machine 2 yield improves to 97%. Improvement tracked and quantified.

Real Example: Automotive Supplier#

An automotive parts supplier (producing brackets for car seats) had 4% scrap rate across all production. They assumed it was normal and priced accordingly. After implementing AskBiz yield tracking: (1) Discovered that scrap varied: Operator A (3%), Operator B (5%), Operator C (2%). (2) Operator B was damaging units during finishing (over-sanding). Training reduced his scrap from 5% to 3%. (3) Material lot from Supplier X had 6% scrap (vs. 2% for Supplier Y). Negotiated quality improvements with Supplier X. (4) Machine #3 had 5% scrap (vs. 3% average). Maintenance revealed worn bearings. Replacement reduced scrap to 3%. (5) Overall scrap improved from 4% to 2.5%. On $5M annual production, that's $75K in recovered margin.

• A factory producing 10,000 units monthly at $10 COGS per unit accepts 2% scrap = 200 units wasted monthly = $2,000 cost.
• Over a year: $24,000.
• But if scrap is from a fixable process issue (machine calibration, operator error), it's preventable waste.