As Chief Technical Officer and Solutions Architect, I have designed network topologies for various institutions and helped scale up their existing architectures to meet the demands of technological advancements. I have also been an Adjunct Professor at CMR University.
Currently, I have been utilizing the skills acquired at Great Learning to address one of the client’s demands in reducing wastage at his factory’s production outlet. Since the client’s business dealt with metal stamping, the objective was to minimize losses in stamping forged steel that is customized to different shapes based upon the needs of our client’s vendors.
Analyzing the image dataset that consisted of shapes of different dimensions, we inferred that the standard deviation of these shapes wasn’t highly skewed. After pre-processing the data for improving the features to feed into an AI model, the dataset was fed into a Computer Vision model developed using Tensorflow libraries.
The results looked promising enough, with the AI model being able to accurately predict images from a random test set. The client was recommended to integrate the model into the mechanical operations of his factory.
By implementation of this solution, the client’s supply-side needs could considerably be reduced, thus helping him save on operational costs and thus improve profit margins.
0 Source: GreatLearning Blog