Transforming water management through smart 重要enance

Water is essential to our survival – yet has become one of the scarcest natural resources on the planet.

人口增长的关系, 工业发展和气候变化给世界带来了前所未有的挑战，即确保足够的水供应以维持城市需求, 以及支持可再生能源技术的新兴发展和不断增长的农业需求.

Wood’s mission is to create a water-secure future for our world through technology-driven, sustainable solutions; drawing on our global network of expertise to apply innovative solutions to the regionally discrete challenges of water security.

Globally, Wood has had a long and innovative connection to the water sector. 在澳大利亚, we have more than 20 years’ experience supporting the local water and wastewater sectors. 我们致力于维护和改善当地基础设施，以满足日益城市化和农业发展的现代水网的需求.

在澳大利亚，水是一种更为宝贵的资源，因为年均降雨量只有470毫米，而且据预测还会受到气候变化的影响. As urban development progresses, it is imperative that smarter and more sustainable solutions for water management are developed in tandem. With the conflict of growing demand and emissions reductions goals, 处理和分配效率正迅速成为全国各地水务公司最重要的要求之一.

Wood’s partnerships with multiple Australian water operators and global inter-industry experience, 意味着我们 scalable smart 重要enance solutions can be targeted toward all levels of current 重要enance capabilities and data maturity. 拥有端到端的专业知识, 我们的解决方案始终专注于开发基于全球制造的行业领先实践, production and distribution technologies.

Through our deep understanding of the fundamental barriers to 重要enance data acquisition and management, 伍德的智能维护解决方案结合了我们对市政供水资产的综合知识，确保领先的技术适用于我们的水务合作伙伴的定制需求, delivering cost reductions and improved asset reliability.

Criticality of data structures in smart 重要enance solutions

当代水务组织有效数据结构的障碍通常与资产所有权的历史性合并和管理多个控制系统的困难有关, project processes and optimisation programs.

成功实施智能解决方案的一个关键方面是水务公司资产和运营数据结构的有效性.

Wood对水务行业合作伙伴的数据成熟度和操作流程进行了全面的研究，并开发了一种系统的方法，以确保研究结果和优化理论可以通过我们的维护交付合作伙伴全面实施. Creating a range of intelligent solutions, we enable effective decision-making for our clients’ water 重要enance strategies.

我们的智能维护方法的一个核心前提是，改进的默认媒介不是立即实施新技术, rather a leveraging of existing technologies to feed advanced analytics. 然后通过优化基础设施的现状和差距分析来确定新技术，以确保适当的资本投资目标.

Wood智能维护研究的一个共同发现是未充分利用的计算机化维护管理软件(CMMS)功能的未开发潜力. 我们对水务基础设施最有效的深度学习架构的应用和理解，使维护成本直接降低了20%以上, and indirect benefits including immediate 备件 stockholding reductions and increased asset reliability.

Implementing machine learning and intelligence for the water industry

机器学习和人工智能的进步开启了水务行业的数字化转型. 人工神经网络的广泛应用已经超越了传统的数据驱动决策和水作业优化的许多局限性. As deep learning capabilities reach new heights, the water industry is ideally positioned as a beneficiary through applications including:

• Dynamic asset management programs, including optimised 重要enance intervention scheduling
• Scalable asset performance and condition monitoring
• Network current state estimation
• Numerical detection of physical and apparent water losses
• 能源 savings and carbon footprint reduction
• Definition of contingency supply plans and protocols, aiding shutdowns and capital project delivery
• Identification of 备件 consumption patterns and demand forecasting

人工智能也通过多源数据集成在智能商业分析中发挥着关键作用, leveraging cloud technologies and business intelligence visualisations for real-time 的见解 and analysis. 当与优化计划同时实施时，目标是增强水操作模型和资产维护, 这些泛化的商业智能洞察允许实时识别机会性的资源重新分配, enabling optimised 重要enance benefits.

机器学习和人工智能也为自传播数据结构的发展创造了机会, enabling advanced trend forecasting using external variables such as calendar events, 社会经济发展, 还有气候变量. 这 creates consistent value drivers throughout the data maturity curve, 从基本结构和管理发展到高级分析和集成的实际好处.

Wood的增强机器学习开发已经将CMMS和传感器数据的人工分析减少了90%, transcending limitations of big data analysis. These reductions in operational investment have allowed rapid payback periods for investment, providing confidence for optimisation to be scaled across large asset bases.

Implementation of Wood’s smart 重要enance solutions has enabled remarkable outcomes for our industry partners.

优化库存 通过识别和优化关键库存单元来支持资产可用性，使关键库存价值和相关运营成本降低了约40%, as well as 重要enance strategy optimisation, yielding cost reductions of over 25% and as high as 45% across high criticality assets. Further supporting sustainability goals, energy and fuel consumption reductions of 10% have also been achieved through optimised operating philosophies.

Coupled with qualitative benefits including improved asset reliability, identification of data integrity and structure improvement opportunities, and 重要enance performance visibility, 我们的智能维护方法提高了维护和运营成本效率，同时在日益缺水的情况下支持供应的确定性和可靠性.

Although Australian water utilities vary broadly in their treatment and distribution processes, the goal of water security remains the same.

通过智能维护从一开始就在数据程序中创造价值是简化水管理的关键. 这, 随着全球跨行业专业知识的整合和我们的水务合作伙伴之间成功驱动因素的独特见解, 解锁解决方案，提供最佳的资产可靠性，不仅为澳大利亚提供水安全的未来, 但是这个世界.

* http://www.nationalgeographic.com/environment/article/partner-content-how-australia-is-securing-its-water-future