Dynamic Filling Rate Control for Carbonated Beverage Containers
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Solution Overview
Problem
The challenge in filling containers with carbonated beverages is the tendency for foaming when filled too quickly, which can be mitigated by slower filling but results in longer filling times, necessitating an optimization method for achieving a balance between speed and minimal foaming.
Innovation Solution
A method involving an eight-step optimization process using a learning phase with a self-learning algorithm to determine optimal filling parameters, such as filling rate and valve control, through a data model that simulates the filling behavior, allowing for rapid and effective optimization of filling operations for both known and new products.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the filling rate is increased to improve productivity, then the filling speed increases, but foaming occurs which degrades product quality
Solution Approach 1:
The filling rate is dynamically adjusted during the filling process rather than maintained at a constant high rate. The system varies the filling rate based on real-time feedback about foam formation, allowing high productivity when conditions permit and reduced rates when foaming occurs, thus resolving the contradiction between speed and quality
Solution Approach 2:
A feedback mechanism monitors foam formation during filling and uses this information to adjust the filling rate. When foaming is detected, the system reduces the filling rate to eliminate foam; when no foam is present, it maintains or increases the rate for maximum productivity
2Object-generated harmful factors
If the filling rate is decreased to minimize foaming, then product quality improves, but filling time increases reducing productivity
Solution Approach 1:
The filling process uses periodic adjustments in filling rate rather than a continuously reduced rate. The system alternates between higher and lower filling rates in response to periodic foam formation patterns, maintaining overall productivity while minimizing foam through rhythmic rate variations
3Ease of operation
If a fixed filling rate is used for different products, then the filling process is simple to operate, but the filling quality varies across different product types
Solution Approach 1:
The filling system performs self-adjustment based on product characteristics and real-time process conditions. Rather than requiring manual reconfiguration for different products, the system automatically adapts the filling rate profile to achieve optimal results for each product type, maintaining both simplicity and precision
Data Source
AI summary
A container-filling method includes executing a learning phase by starting a filling operation with a filling parameter that was used to start filling of a another product. The learning phase includes the filling element and saving relationships between a filling parameter, such as expected filling time or foam formation, and a value indicative of that filling parameter. The method includes comparing a saved target with this value to see a termination criterion has been achieved. If not, the filling parameter is varied in response to instructions provided by a simulator and the process repeated.