Aplicación De Matriz Iperc - Identificación De Peligros, Evaluación De Riesgos Y Controles En Operaciones Civiles En Minas Para La Gestión De Riesgos Laborales.

Resumen

This article analyzes the application of the Hazard Identification, Risk Assessment and Control Matrix in civil, mechanical, electrical, instrumentation and control activities within mining operations in Ecuador, as a mechanism that links hazard identification with verifiable controls. The proposed framework integrates the hierarchy of controls prioritizing elimination, substitution, engineering controls, administrative measures, and personal protective equipment with the management of critical controls for high-severity events, moving beyond mere documentary compliance. Methodologically, an applied mixed design was implemented in four phases: documentary diagnosis of task-based IPERC; semi-quantitative risk assessment and allocation of hierarchical controls; functional verification of critical barriers using defined criteria and frequencies; and before-after evaluation (6–12 months) through leading indicators (percentage of critical controls verified on time, quality of job safety analysis, closure of corrective actions) and lagging indicators (Total Recordable Incident Rate TRIR, Days Away, Restricted or Transferred DART, and high-potential incidents per 200,000 hours), aligned with ISO 45001/45002 and regulatory guidelines. The main contribution is a replicable model that demonstrates performance and directs resources toward barriers with the greatest effectiveness. Threats to validity such as underreporting, changes in task mix, and technological maturity of engineering aids are critically addressed and mitigated through record audits, segmentation by work front, and formal change management. In Latin American contexts, the proposal aligns with DS 024-2016-EM and SUNAFIL’s IPERC Manual, strengthening traceability and regulatory oversight. This approach not only enhances compliance but also fosters proactive risk governance, enabling organizations to anticipate failures and improve safety outcomes in complex mining environments.