Blow Molder Control System for Crystallinity and Base Sag Optimization
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Solution Overview
Problem
Current blow molder process control systems are unable to effectively manage container properties such as crystallinity, base sag, and various container dimensions, which are crucial for ensuring the quality and performance of blow-molded containers.
Innovation Solution
A control system that communicates with a blow molder and various inspection systems to measure container characteristics, adjusting blow molder input parameters such as preform temperature and mold temperature to optimize crystallinity, base sag, and container dimensions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual off-line inspection methods are used to measure container properties, then operator flexibility is maintained, but measurement precision and consistency deteriorate due to qualitative interpretation variations
Solution Approach 1:
The patent replaces manual mechanical inspection methods (squeeze tests, section weight tests) with automated optical measurement systems. The system uses cameras and image processing algorithms to automatically measure container material distribution, eliminating the need for operators to perform qualitative squeeze tests and manually weigh sections, thereby ensuring consistent and precise measurements.
Solution Approach 2:
The patent introduces an automated inspection system as an intermediary between the blow molding process and the operator. This system includes cameras positioned to capture images of containers, image processing software that analyzes the images to determine material distribution, and a user interface that presents the results to the operator, thereby mediating the measurement process to ensure consistency while maintaining operational control.
2Adaptability or versatility
If operators manually adjust blow molder parameters based on off-line inspection results, then adaptability to container defects is improved, but manufacturing precision deteriorates due to complex parameter correlations and operator skill variations
Solution Approach 1:
The patent implements a closed-loop feedback system where the automated inspection system continuously measures container material distribution and feeds this information back to the control system. The control system then automatically adjusts blow molder parameters based on the measured deviations from target specifications, creating a continuous feedback loop that improves manufacturing precision while maintaining adaptability to defects.
Solution Approach 2:
The patent enables the blow molder to self-adjust its parameters based on real-time feedback from the inspection system. The control system automatically interprets measurement data and modifies process parameters without requiring operator intervention, allowing the system to service itself and maintain precise material distribution control while adapting to various container defects.
3Productivity
If multiple molds (10-48 or more) are used to increase product rate, then productivity is improved, but the rate of defective container generation increases due to process parameter problems
Solution Approach 1:
The patent implements individual inspection and control for each mold position within the multi-mold blow molder. The inspection system can identify which specific mold is producing defective containers, and the control system can independently adjust parameters for that specific mold, allowing each mold to be optimized and controlled separately while maintaining high overall productivity.
Solution Approach 2:
The patent introduces dynamic parameter adjustment capability where blow molder parameters can be changed in real-time for individual molds based on their specific performance. This allows the system to adapt parameters dynamically for each mold position, ensuring consistent quality across all molds while maintaining high production rates, rather than using static parameters for all molds.
Data Source
AI summary
Systems and methods control the operation of a blow molder. An indication of a crystallinity of at least one container produced by the blow molder may be received along with a material distribution of the at least one container. A model may be executed, where the model relates a plurality of blow molder input parameters to the indication of crystallinity and the material distribution and where a result of the model comprises changes to at least one of the plurality of blow molder input parameters to move the material distribution towards a baseline material distribution and the crystallinity towards a baseline crystallinity. The changes to the at least one of the plurality of blow molder input parameters may be implemented.


