89 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 Establishing critical limits for operation (e.g., maximum load on an overhead crane or flow velocity in pipelines). Exceeding these limits drastically accelerates technical degradation. 3.3.2. Change Management (MOC) Any modification to the process (change in mineral hardness, increase in tonnage) must be evaluated by the Asset Integrity team to understand its impact on the static infrastructure. 3.3.3. Safety and Wellbeing Culture Operational integrity encourages operators to be the "first inspectors", reporting unusual noises, vibrations or deformations, integrating field knowledge with the centralized management system. 4. METHODOLOGY The proposed AIM model is deployed through a systematic four-stage methodology that guarantees a solution tailored to the unique operational context of each mining company.
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