Agent StoreOperationsYield Management & Scrap Reduction
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Factory Yield and Scrap Rate Analysis Agent

OperationsYield Management & Scrap Reduction

Continuously calculates factory-wide and line-level yield and scrap rates from production data to pinpoint where material and output losses are occurring.

4
Process steps
5
Integrations
3
Data inputs

Plant managers typically reconstruct yield and scrap figures from spreadsheets pulled together at month-end, by which point the underlying causes of material loss are impossible to trace back to a specific batch, shift, or machine setting

Scrap creep goes unnoticed for weeks, quietly eroding margin on every unit produced

This agent pulls production counts, material consumption, and scrap/rework entries directly from the MES and ERP systems to compute real-time first-pass yield and scrap percentages at the line, cell, and SKU level

It benchmarks current performance against historical baselines and target yield rates, surfacing the specific process steps or machines dragging yield down

The agent reconciles production output, raw material issued, and scrap/rework transaction records from the ERP and MES on a rolling basis, computing yield and scrap rate at multiple granularities. It runs variance analysis against target yield thresholds and prior-period baselines, applying Pareto ranking to identify the top contributors to loss. Results are rendered into a yield dashboard and a written analysis summarizing where and why scrap is occurring, refreshed automatically each production shift.

1

Production & Scrap Data Collection

  • Pull finished-unit counts and material issued per work order from the MES/ERP
  • Ingest scrap and rework transaction codes with reason fields
  • Match units produced to bill-of-materials consumption
  • Flag incomplete or missing scrap-reason entries for follow-up
Outcome: A complete, reconciled dataset of production output versus material input is compiled.
2

Yield Calculation

  • Compute first-pass yield and scrap rate by line, cell, shift, and SKU
  • Compare results against target yield and rolling 30-day baseline
  • Segment yield loss by scrap reason code
  • Identify statistically significant deviations
Outcome: Accurate, current yield and scrap metrics are available at every level of the plant.
3

Root-Cause Ranking

  • Rank yield-loss contributors using Pareto analysis
  • Cross-reference scrap spikes with machine, operator, and material lot data
  • Highlight recurring scrap reasons across multiple periods
  • Estimate cost impact of each loss category
Outcome: The highest-impact sources of scrap are identified and quantified in dollar terms.
4

Reporting & Action Recommendations

  • Generate a yield and scrap analysis report for plant leadership
  • Recommend targeted improvement actions per top contributor
  • Track yield trend against improvement initiatives over time
  • Distribute report to operations and finance stakeholders
Outcome: Leadership receives a clear, cost-quantified action plan for closing the yield gap.
MES (Manufacturing Execution System)
ERP (SAP/Oracle/NetSuite)
Bill-of-materials management system
Power BI/Tableau
Slack/Microsoft Teams