An Asset Health Index (AHI) is a tool that processes data about asset’s condition. That index is intended to explore if alterations can be generated in the health of the asset along its life cycle. These data can be obtained during the asset’s operation, but they can also come from other information sources such as geographical information systems, supplier’s reliability records, relevant external agent’s records, etc. The tool (AHI) provides an objective point of view to justify, for instance, the extension of an asset useful life, or to identify which assets from a fleet are candidates for an early replacement, or renovation, as a consequence of a premature aging.

This paper describes how to build the AHI model as a continuous time simulation model, which is then implemented using Vensim simulation environment. This is done in order to: 1) improve model formulating robustness, 2) benefit of the outstanding software optimization features for AHI model parameters calibration; and 2) easy the provision of predictions for asset degradation, operational and capital investments risk under different possible exogenous scenarios and endogenous managerial options.

The process of model building, and parameterization is applied to an industrial case of a regasification terminal. Several strategies involving major maintenance scheduling are compared in terms of total expenditure in assets over their life cycle.

资产健康指数 (AHI) 是一种处理有关资产状况数据的工具。该指数旨在探索资产在其生命周期中的健康状况是否会发生变化。这些数据可以在资产运行期间获得，但也可以来自其他信息源，例如地理信息系统、供应商的可靠性记录、相关外部代理的记录等。该工具 (AHI) 提供了一个客观的观点来证明，例如，延长资产使用寿命，或确定车队中的哪些资产由于过早老化而适合提前更换或翻新。

本文介绍了如何将 AHI 模型构建为连续时间仿真模型，然后使用 Vensim 仿真环境实现。这样做是为了：1) 提高模型制定的鲁棒性，2) 为 AHI 模型参数校准提供出色的软件优化功能；2) 在不同可能的外生情景和内生管理选项下，轻松提供资产退化、运营和资本投资风险的预测。

模型建立和参数化过程应用于一个再气化终端的工业案例。根据资产在其生命周期内的总支出，对涉及重大维护计划的几种策略进行了比较。