3.1.1. Standards and Regulations: It involves verifying that the design complies with international codes (AISC for steel, ACI for concrete) and local regulations. 3.1.2. Selection of Materials Evaluate whether the choice of materials and protection systems (galvanizing, epoxy coatings) is compatible with the aggressiveness of the mining environment (presence of chlorides, extreme pH in leaching processes or critical humidity). 3.1.3. Documentation Management Design integrity depends on the availability and accuracy of as-built drawings. The proactive model uses these documents to validate whether operational modifications made over the years (e.g., increased conveyor belt capacity) have eroded the original safety factor. 3.2. Technical Integrity It represents the physical health of structures at a given moment. It is the dimension where AI and drone technology generates its greatest value. 3.2.1. Deterioration Mechanisms The technical analysis focuses on identifying and quantifying degradation mechanisms such as corrosion (uniform or pitting), structural fatigue due to mechanical vibration, and abrasive wear. 3.2.2. Fitness and Condition for Service (FFS) Assessment Using standards such as API 579-1 / ASME FFS-1, the model determines whether an asset with visible defects is still safe to operate. AI automates this assessment by processing images according to ASTM 610, providing an objective metric for section loss or surface integrity. 3.2.3. Risk-Based Inspection (RBI) According to API 580/581, technical integrity does not imply inspecting everything equally, but rather prioritizing those elements whose probability of failure and consequence (productive or environmental) is critical. 3.3. Operational Integrity It is the governance dimension that ensures the asset is operated within its design limits. As the CCPS (2016) points out, a technically perfect asset can fail catastrophically if the human factor and process parameters are ignored. 3.3.1. Operational Windows of Integrity
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