Hephaestus said “Nothing lasts forever, not even the best machines. And everything can be reused.” This very line sums up the need for Predictive maintenance. We, at Diginance, are geared up for building the next-gen asset management with our hardware and software teams clearing the decks with full vigor.
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| Role of Software in Predictive Maintenance |
Here’s a quick blog to tell you how the software does its part in predictive maintenance
Internet of Things(IoT)
For the predictions to work, what is essential is the data set consisting of various parametric data viz thermal, vibrational and stress measurements. IoT is that hotshot who fetches us all the data to make the magic work with the aid of its diligent sensors!
Cloud Storage
We get all the data and we very well know how to work with them. Yet, we need to store the data. We knew what we needed is a flexible, cost-efficient and a collaboration efficient data storage unit. And that’s when we chose Cloud without any haze :)
Machine Learning
Once, we are ready with the dataset, we are good to go for the actual magic- the prediction. The ML model has been trained to give out the prediction- i.e. when the machine would require maintenance with utmost possible precision.
Python-Django Framework
We are aiming to make this a web-based application to overcome device compatibility, platform-dependent, and heavyweight concerns. We intend to build a web application using Python and its high-level Web Framework - Django, considering the speed, security and scalability perks.
The Bottom Line
With the might of hardware and software combined, Diginance is all set to put an end to your torment about maintenance in your plant.
great work!!!
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