🇧🇷Brazil

Ociosidade e Atrasos por Classificação Manual de Sucata

Updated: Feb 20262 verified sources

Definition

A case study of Brazilian metal-mechanical industry showed that 'unspecified reasons' in scrap classification consumed significant administrative burden. Implementation of systematic classification reduced unspecified categories from >40% to 11.73%, immediately freeing production scheduling. Manual classification of 100+ supplier shipments requires visual inspection, weighing, chemical analysis, and data entry—each step is a potential queue point.

Key Findings

Financial Impact: LOGIC-based estimate: Manual scrap classification = 40–60 hours/month per facility. At Brazilian industrial labor cost (R$ 80–120/hour all-in): R$ 3,200–R$ 7,200/month = R$ 38,400–R$ 86,400/year per facility. Capacity loss from melt queue delays: conservatively 2–4 unscheduled production delays/month × 4 hours = 8–16 hours/month × R$ 5,000–R$ 8,000 lost production value = R$ 40,000–R$ 128,000/year per facility. **Total per facility: R$ 78,400–R$ 214,400/year.**
Frequency: Daily (scrap arrival), each production shift (charge preparation).
Root Cause: Fragmented supplier network requiring individual supplier relationship management; absence of supplier quality certification programs; manual data entry and electronic grouping (no real-time integration); no standardized scrap classification vocabulary across suppliers.

Why This Matters

The Pitch: Manual scrap classification in Brazilian EAF operations consumes 40–60 labor hours monthly per facility, delaying melt cycles and idle capacity. Automated scrap grading systems eliminate classification queues and accelerate charge mix decisions.

Affected Stakeholders

Scrap yard operators (receiving, sorting, weighing), Materials inspectors (quality assessment), Production planners (charge mix scheduling), EAF charge operators (waiting for classified scrap), Data entry clerks (recording scrap metadata)

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Financial Impact

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Current Workarounds

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Methodology & Sources

Data collected via OSINT from regulatory filings, industry audits, and verified case studies.

Evidence Sources:

Related Business Risks

Falhas de Qualidade por Mistura Inadequada de Cargas em Fornos de Arco Elétrico

PROVEN: 4.4% scrap rate reduction achievable via analytics optimization. For a 100-ton/day EAF facility: 4.4 tons/day = ~1,600 tons/year × R$ 2,500–R$ 3,500/ton scrap loss = R$ 4,000,000–R$ 5,600,000 annual impact. Conservative rework rate in quality-driven facilities: 2–5% of output.

Decisões Subótimas de Compra de Sucata por Falta de Visibilidade de Qualidade

LOGIC-based estimate: Assume average EAF facility processes 100 tons/day of scrap input. If poor quality forces 10–15% additional dilutant cost (pig iron/DRI at premium): 10–15 tons/day × (R$ 500–R$ 1,000 premium over scrap cost) = R$ 5,000–R$ 15,000/day = R$ 1,500,000–R$ 4,500,000/year per facility. Conservative estimate: 5% overpay on scrap sourcing = R$ 800,000–R$ 1,200,000/year per 100-ton facility.

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