Predictive maintenance (PdM) is a data-driven approach to maintenance that uses historical data to predict when equipment is likely to fail. We leverage ML models developed by OpenAI, as well as OpenAI's language models to extract insights from text data.
It is important to understand the high-level architecture to get a clear idea how we leverage OpenAI capabilities while building a predictive maintenance system.
ThirdEye Data develop predictive maintenance system from scratch. We implement the required ML models developed by OpenAI. These algorithms get trained on historical data to identify patterns that can be used to predict future failures.
We have prepared custom Predictive Maintenance ML models which are ready to be deployed.
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Before enterprises opt for predictive maintenance, they may have some common asks. We are trying to answer them here.
The key features of a predictive maintenance model will depend on the specific data that is available and the business goals of the model. However, some common features include:
It is common to get stuck with an AI initiative or project. To avoid the same, consider these points at the very begining:
Your budget: How much are you willing to spend on a sentiment analysis platform?
Your needs: What do you need the platform to do?
The accuracy of the platform: How accurate is the platform?
The ease of use of the platform: How easy is the platform to use?
The support offered by the engineering team: What kind of support does the engineering team offer?
The budget for the project will depend on the specific scope of the project. However, in general, predictive maintenance projects can be relatively expensive.
The data we feed to a predictive maintenance model will vary depending on the specific assets that are being monitored. However, some common data sources include:
The business goals of a predictive maintenance model will vary depending on the specific needs of the organization. However, some common goals include:
We offer end-to-end predictive maintenance solution. It means we not only develop the model from scratch but also take full responsibility of maintaining, monitoring and retraining the model.