Machine learning driven Organic synthesis process monitor application built by gramener with low-code development approach
Machine learning driven Organic synthesis process monitor application built by gramener with low-code development approach
2500+
lines of code reduced
3 Days
to build Machine Learning App
Low Code Organic Synthesis Process Monitoring

One of our leading pharmaceutical clients wanted to monitor the organic synthesis process in their factory to predict the quality of tablet production.

What did we do?
  • Created a low-code Machine Learning platform to monitor every aspect of the organic synthesis process
  • Devised the model to use real-time data of reactor temperature, crystallizer cooling rate, stirring speed, and more to predict the quality of the batch
  • Offered the low code application in floor layout and with four versions - Mobile Alert, Floor Monitor, Predict Quality, Simulator
These four views along with the complete application were built using our low-code development platform Gramex
Result

The ML model helps the manufacturers to predict the quality of batch during the process and offers provisions to change the machine settings for better quality. It predicts the quality based on the fineness of the powder, i:e; if 90% of the powder particles are fine, the batch will be of good quality.

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