We are seeking technologies, such as thermal profiling, vision systems, sensors, and image recognition, to identify and measure defects in plastic containers after the blow molding process. Specifically, we are looking for a method to easily identify and measure cold stretching pearlescence vs. haze from over-heating crystallization during the blow molding process or immediately thereafter. The intention is to use this information to make real-time adjustments and corrections to the blowing process.

Solutions of interest include:

• An apparatus and method for the measurements.
• Imaging (e.g. infrared and polarized light cameras) or in-line optical sensors coupled with automated defect detection.
• Vision inspection systems.
• Specialized instrument providing a full thermal profile of the preform, integrated with machine learning for real-time defect prediction and process optimization.

Our must-have requirements are:

• Identify and measure areas that have either heat haze or over-stretch pearlescence (cold stretch) around the complete perimeter of the container.
• Provide a graphic/visual feedback indicating the location of the crystallinity/pearlescence in the container.
• Deliver fast, verifiable, and repeatable results that can be used to adjust the blow molding process as it happens.

Our nice-to-have's are:

• Graphic/visual interface.
• Portability for use across different production lines.
• Ease of use, geared toward a production line environment.
• Live monitoring system capable of in-line operation at blow molding speeds (~6000 bottles per hour).