MUMBAI, India, Oct. 5 -- Intellectual Property India has published a patent application (202641114492 A) filed by Vallurupalli Nageswara Rao Vignana Jyothi Institute Of Engineering And Technology on September 24, 2026, for An Ai-Enabled Predictive Quality Control System For Blow Molding Using Process Parameter Analysis And Machine Learning.
Inventor includes Sri S. R Somayajulu.
The application for the patent was published on October 02, 2026, under issue no. 40/2026.
Abstract: ABSTRACT [0025] Manufacturing industries are increasingly using data-driven methods to improve process reliability and product quality. Blow molding is a common technique for creating hollow plastic items like bottles, containers, and packaging parts. However, changes in process parameters such as melt temperature, cycle time, shot volume, clamping force, and injection pressure can greatly impact product quality. Even minor fluctuations in these parameters can cause defects like uneven wall thickness, dimensional inaccuracies, and surface flaws. This research describes the development of a machine learning model for quality assurance in blow molding. We analyzed industrial data that included process parameters and quality labels, using data processing and visualization methods. This study introduces an application of machine learning to implement quality control during the blow molding process. Analysis of industrial data containing information about manufacturing processes and quality indicators was conducted through data pre-processing and visualizations. Application of machine learning methods such as Random Forest, Decision Tree, and Support Vector Machine was performed for predicting product quality. It has been found that cycle time, melt temperature, maximum injection pressure, and shot volume are key factors affecting the quality of the final product.
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