AWS Machine Learning Blog 2024年09月18日
Preserve access and explore alternatives for Amazon Lookout for Equipment
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亚马逊设备预警服务(Lookout for Equipment)将于2024年10月17日停止向新客户开放。现有的客户仍然可以继续使用该服务,但亚马逊将不再为该服务添加新功能。文章介绍了如何继续使用该服务以及一些替代方案。

😊 **服务停用:**亚马逊设备预警服务(Lookout for Equipment)将于2024年10月17日停止向新客户开放。现有的客户仍然可以继续使用该服务,但亚马逊将不再为该服务添加新功能。 为了继续使用该服务,现有客户需要在2024年10月17日之前完成以下操作之一: - 在设备预警服务控制台中创建一个新项目并成功完成模型训练。 - 在设备预警服务控制台中打开现有项目,为指定模型安排推理,并运行至少一次推理。 - 使用设备预警服务API调用CreateInferenceScheduler和StartInferenceScheduler(并在完成时使用StopInferenceScheduler)。

🤔 **替代方案:**对于希望寻找设备预警服务替代方案的用户,亚马逊提供了两种选择: - **AWS合作伙伴网络:**AWS合作伙伴网络提供来自多个合作伙伴的解决方案。用户可以在AWS解决方案库的资产维护和可靠性页面上浏览这些解决方案。这种方法提供了一个解决方案,可以满足用户的用例,而无需用户拥有预测性维护方面的专业知识,并且通常通过使用AWS合作伙伴的专业知识,可以最快速地实现价值。 - **自行构建解决方案:**如果用户更喜欢自行构建解决方案,AWS提供了AI/ML工具和服务,帮助用户开发基于AI的预测性维护解决方案。Amazon SageMaker提供了一套工具,使用户能够使用完全托管的基础设施、工具和工作流来构建、训练、推理和部署适合其用例的ML模型。

😉 **总结:**尽管从2024年10月17日开始,新客户将无法再使用设备预警服务,但亚马逊提供了强大的AI/ML服务和解决方案,例如用于构建客户模型的SageMaker工具,以及通过AWS合作伙伴网络提供的各种解决方案。用户应该探索这些选项,以确定最适合其特定需求的方案。

Amazon Lookout for Equipment, the AWS machine learning (ML) service designed for industrial equipment predictive maintenance, will no longer be open to new customers effective October 17, 2024. Existing customers will be able to use the service (both using the AWS Management Console and API) as normal and AWS will continue to invest in security, availability, and performance improvements for Lookout for Equipment, but we do not plan to introduce new features for this service.

This post discusses how you can maintain access to Lookout for Equipment after it is closed to new customers and some alternatives to Lookout for Equipment.

Maintaining access to Lookout for Equipment

You’re considered an existing customer if you use the service, either through cloud training or cloud inferencing, any time in the 30 days prior to October 17, 2024 (September 17, 2024, through October 16, 2024). To maintain access to the service after October 17, 2024, you should complete one of the following tasks from the account for which you intend to maintain access:

For any questions or support needed, contact your assigned AWS Account Manager or Solutions Architect, or create a case from the AWS console.

Alternatives to Lookout for Equipment

If you’re interested in an alternative to Lookout for Equipment, AWS has options for both buyers and builders.

For an out-of-the-box solution, the AWS Partner Network offers solutions from multiple partners. You can browse solutions on the Asset Maintenance and Reliability page in the AWS Solutions Library. This approach provides a solution that addresses your use case without requiring you to have expertise in predictive maintenance, and typically provides the fastest time to value by using the specialized expertise of the AWS Partners.

If you prefer to build your own solution, AWS offers AI/ML tools and services to help you develop an AI-based predictive maintenance solution. Amazon SageMaker provides a set of tools to enable you to build, train, infer, and deploy ML models for your use case with fully managed infrastructure, tools, and workflows.

Summary

Although new customers will no longer have access to Lookout for Equipment after October 17, 2024, AWS offers a powerful set of AI/ML services and solutions in the form of SageMaker tools to build customer models, and also offers a range of solutions from partners through the AWS Partner Network. You should explore these options to determine what works best for your specific needs.

For more details, refer to the following resources:


About the author

Stuart Gillen is a Sr. Product Manager, Lookout for Equipment, at AWS. Stuart has held a variety of roles in engineering management, business development, product management, and consulting. Most of his career has been focused on industrial applications specifically in reliability practices, maintenance systems, and manufacturing.
Stuart is the Product Manager for Lookout for Equipment at AWS where he utilizes his industrial and AI background in applications focusing on Predictive Maintenance and Condition Monitoring.

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亚马逊设备预警服务 预测性维护 机器学习 AWS
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