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正面临来自政府、监管机构和公众的巨大压力，要求他们改善其环境绩效、运营绩效、资产（如泵）的安全性和可靠性，同时在比以往任何时候都更严格的审查和监管下工作。他们需要一个资产管理系统，通过最小化资产失效的风险来满足这些需求和气候变化带来的额外需求。我们的创新与预测性资产管理的发展有关，该管理可以最大限度地降低资产故障的风险，从而降低资产故障对环境造成损害的风险。**环境挑战**我们的创新改善了组织的环境绩效，减少了其能源密集型基础设施资产的能源消耗，从而帮助他们实现净零排放。资产故障的后果包括洪水、污染、服务中断、成本显著提高、监管机构开出的巨额罚款以及资产可用性低下。能源密集型资产所使用的能源取决于它们的维护方式。如果资产不处于最佳状态，它们使用的能源就会比预期的要多得多，并且面临更大的故障风险。资产管理策略基于其计算的当前故障风险而不是固定频率的资产，可以在需要时安排主动维护，即当它们不是最佳运行并且具有高故障风险时。我们的创新识别了每个资产在使用和维护过程中的故障风险。失败，然后恢复。该创新的初步模拟结果表明，仅小幅提高主动维护水平就能显著降低资产故障的风险。**解决方案**我们的创新是一种云托管、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：建模、模拟和优化单个资产层面和运营层面的资产管理；战术和战略水平\ *造型每个资产作为一个独特的实体的动态风险失败的配置文件,以便每个资产可以被监控,而不是把每个资产作为一个群体,所有资产在一群有相同的失败的风险配置文件\ *探索性数据分析和数据准备功能来提高数据的质量和确保数据的正确形式分析和建模(必要的所有分析的第一步项目)。

**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).