predictive-maintenance | Demonstration of MapR for Industrial IoT | Dashboard library
kandi X-RAY | predictive-maintenance Summary
kandi X-RAY | predictive-maintenance Summary
There are two objectives relating to predictive maintenance implemented in this project. The first objective is to visualize time-series data in an interactive real-time dashboard in Grafana. The second objective is to make raw data streams and derived features available to machine learning frameworks, such as Tensorflow, in order to develop algorithms for anomaly detection and predictive maintenance. These two objects are realized using two seperate data flows:. Put together, these data pipelines look like this. The APIs used for reading and writing data are shown in red.
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QUESTION
I wanted to re-label the healthy label (0) to failure label (1) 3 days before the actual failure (1) like what they did in the attached link: Reference link. It worked well for the equal time length but did not work for the variable length. That is, all serial number must fail in the same day which doesn't make sense. For the sample dataset, we see that serial C failed in January 5, 2014, A failed in January 6, and A failed in January 7. I want to relabel the re-label the healthy label (0) to failure label (1) 3 days before the actual failure (1) for the serial number C, and for the other serial numbers as well. I appreciate your time. Thanks!
My code:
...ANSWER
Answered 2021-Nov-22 at 17:30Here is a working solution. Note: I preferred to rewrite it completely for clarity.
QUESTION
We are trying to execute and check what kind of output is provided by Predictive Maintenance Using Machine Learning on AWS sample data. We are referring Predictive Maintenance Using Machine Learning and AWS Guide to launch the sample template provided by the AWS. The template is executed properly and we can see the resources in account. Whenever we run the sagemaker notebook for the given example we are getting the error in CloudWatch logs as follows
...ANSWER
Answered 2020-Apr-28 at 08:50A fix for this issue is being deployed to the official solution. In the meantime, you can make the changes described here in your SageMaker environment by following the instructions below:
1) In the notebook, please change the framework_version
to 1.6.0
.
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