Desperdício de Matéria-Prima por Otimização Inadequada de Rendimento
Definition
Search results document that operator decision-making during log breakdown has 'a great influence on lumber yield' (Source [2]). Yields range 40–55% for Amazonian species vs. 57.3% reported with optimized methods (Source [1]). This 2–17% gap represents direct raw material loss. For a sawmill processing 10,000 m³/year at current yield vs. optimized yield: loss of 200–1,700 m³ of lumber (valued at R$100–300/m³ = R$20,000–510,000/year in lost wood value).
Key Findings
- Financial Impact: R$20,000–R$510,000/year per sawmill (depending on scale); equivalent to 2–17% of raw material waste or 5–15% of labor-driven yield variance
- Frequency: Continuous (every log processed)
- Root Cause: Reliance on operator skill rather than computer-optimized cutting templates; absence of standardized cut-pattern modeling
Why This Matters
The Pitch: Sawmill operators in Brasil waste 5–15% of raw log volume annually due to manual cutting decisions and unoptimized sawing patterns. Automation of cutting-pattern simulation (using tools like CalcMadeira or MaxiTora) eliminates operator variance and recovers 3–8% material value.
Affected Stakeholders
Operador de Serra, Gerente de Produção, Engenheiro Florestal
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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.
Related Business Risks
Risco de Autuação Fiscal por Discrepância Rendimento vs. Plano de Manejo
Erros de Decisão em Seleção de Padrão de Corte por Falta de Dados de Rendimento
Multa por Madeira Ilegal e Não-Conformidade com Licenças Florestais
Fraude em Autorização de Manejo Florestal e Lavagem de Madeira Ilegal
Perda de Capacidade Operacional por Tempos Improdutivos no Transporte de Madeira
Supercustos de Transporte por Seleção Inadequada de Composição Veicular
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