卫生技术领导者 Ecolab 借助 Microsoft Azure 和 Iguazio 将数据科学引入生产
公司规模
Large Corporate
地区
- America
国家
- United States
产品
- Microsoft Azure
- Azure DevOps
- Azure Machine Learning
- Azure Pipelines
- Iguazio
技术栈
- Python
- Git
- Kubeflow
实施规模
- Enterprise-wide Deployment
影响指标
- Cost Savings
- Productivity Improvements
技术
- 分析与建模 - 机器学习
- 平台即服务 (PaaS) - 数据管理平台
适用行业
- 化学品
适用功能
- 离散制造
- 质量保证
用例
- 预测性维护
- 过程控制与优化
服务
- 数据科学服务
- 系统集成
关于客户
Ecolab 是一家专注于水处理和安全的大型化学品制造商。该公司总部位于明尼苏达州圣保罗，业务遍及 170 多个国家。Ecolab 拥有 44,000 名员工，为食品、医疗保健、酒店和工业市场的近 300 万个客户地点提供服务。该公司的使命是让世界更清洁、更安全、更健康，帮助客户取得成功，同时保护人员和重要资源。
挑战
Ecolab 是水、卫生和感染预防解决方案领域的全球领导者，该公司希望为水系统、工业机械和其他应用开发预测风险模型。该公司的机器学习之旅始于 2016 年，当时的一个项目是使用现有传感器数据开发细菌生长风险模型。然而，在生产中构建、部署和维护机器学习模型的过程既复杂又具有挑战性。该公司需要一个数据科学协作平台，将其庞大的、地理上分散的团队聚集在一起，同时高效利用云计算资源。Ecolab 的机器学习模型部署遵循“重写和部署”模式，其中模型开发独立于应用程序开发人员进行。这种方法导致部署时间平均超过 12 个月。
解决方案
Ecolab 求助于 Microsoft Azure 和 MLOps 专家 Iguazio，以缩短其机器学习开发和部署时间、降低成本，并使其地理分散的团队能够无缝协作，加速推出 AI 应用程序。Iguazio 解决方案基于包括 Kubeflow 在内的开源架构构建，可轻松采用以扩展和简化流程。Ecolab 将 Iguazio 与 Git 和 Azure DevOps 结合使用，以开发特征工程管道和机器学习应用程序。该解决方案还可以直接查看生产过程中运行的代码。Iguazio 平台的部署恰逢 COVID-19 健康危机的爆发，推动了将数据科学模型纳入 Ecolab 更广泛的数字产品的需求急剧增加。
运营影响
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