Using Data Science to Improve Asset Resilience and Environmental Performance

**背景**公用事业和其他资产丰富的部门面临来自政府、监管机构和公众的巨大压力，要求它们改善环境业绩，以及其资产的运行业绩、安全和可靠性，例如水泵，同时比以往任何时候都更严格地审查和监管。它们需要一种资产管理系统，通过将资产失败的风险降至最低来满足这些要求以及气候变化带来的额外要求。我们的创新致力于开发预测性资产管理，将资产失败的风险降至最低，从而将资产失败对环境造成的破坏风险降至最低。**环境挑战**我们的创新提高了组织的环境绩效，减少了其能源密集型基础设施资产的能源消耗，从而帮助它们实现净零。资产失败的后果包括洪水、污染、服务中断、成本大幅上升、监管机构的巨额罚款以及低资产可获得性。能源密集型资产的能源消耗取决于它们的维护方式。如果资产没有处于最佳状态，它们消耗的能源比预期的要多得多，失败的风险也更大。资产管理策略基于其计算的当前故障风险，而不是基于固定频率的资产，可以在需要时安排进行主动维护，即当它们没有以最佳方式运行且故障风险较高时。我们的创新确定了每项资产在使用、维护时的故障风险。失败，然后恢复。创新的初步模拟结果表明，仅需少量提高主动维护水平，资产故障风险就会显著降低。**解决方案**我们的创新是一款云托管、安全、可扩展的预测性资产管理产品，以SaaS的形式提供。它通过以下方式优化资产管理：\*在单个资产级别以及运营、战术和战略级别对资产管理进行建模、模拟和优化\*将每项资产建模为具有其自己的动态故障风险配置文件的唯一实体，以便可以监控每项资产，而不是将每项资产视为队列中所有资产具有相同故障风险配置文件的成员\*具有探索性数据分析和数据准备功能，以提高数据质量并确保数据以正确的形式用于分析和建模(这是所有分析项目的基本第一步)。

**Background**Utilities and other asset-rich sectors are under intense pressure from governments, regulators and the public to improve their environmental performance, and the operational performance, safety and reliability of their assets, for example pumps, whilst working under more intensive scrutiny and regulation than ever before. They require an asset management system that satisfies these demands and the additional demands posed by climate change by minimising the risk of asset failure. Our innovation is concerned with the development of a predictive asset management that minimises the risk of asset failure and therefore the risk of damage to the environment caused by asset failure.**The Environmental Challenge**Our innovation improves the environmental performance of organisations and reduces the energy used by their energy intensive infrastructure assets and so helps them reach net zero. The consequences of asset failure include flooding, pollution, service interruption, significantly higher costs, very large fines from regulators and low asset availability.The energy used by energy-intensive assets depends on how they are maintained. If assets are not in optimal condition, they use much more energy than expected and are at greater risk of failure. Assets whose asset management policy is based on their calculated current risks of failure rather than on a fixed frequency can be scheduled for proactive maintenance when they need it, i.e. when they are not operating optimally and have high risks of failure. Our innovation identifies the risk of failure of each asset as it is used, maintained. fail and then reinstated. Preliminary simulation results from the innovation show that the risk of asset failure is reduced significantly by only small increases in the level of proactive maintenance.**The Solution**Our innovation is a cloud hosted, secure, scalable predictive asset management product offered as SaaS. It optimises asset management by:\* modelling, simulating and optimising asset management at individual asset level and at the operational, tactical and strategic levels\* modelling each asset as a unique entity with its own dynamic risk of failure profile so that each asset can be monitored rather than treat each asset as a member of a cohort where all assets in a cohort have the same risk of failure profile\* having exploratory data analysis and data preparation functionality to improve the quality of the data and ensure that the data are in the correct form for analysis and modelling (the essential first step in all analytics projects).