Container Treatment Line Control for Stable Flow and Fewer Stops
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Solution Overview
Problem
Current beverage filling lines lack a higher-level control system, leading to suboptimal line behavior such as container flow pulsations, increased energy consumption, and reduced efficiency due to avoidable machine stop and start cycles.
Innovation Solution
A method for controlling a container treatment line using a central control unit that receives data from machines and transport units, employing model-based control to calculate and send instructions for optimizing machine and transport unit operations, incorporating sensors and cameras for real-time monitoring and adjustment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If only a few stored operating states (e.g., nominal capacity 100%, overcapacity 120%) are used to control the beverage filling line, then the control system remains simple, but the line efficiency and energy consumption optimization is insufficient
Solution Approach 1:
The patent implements dynamic control by continuously adjusting operating parameters based on real-time sensor feedback rather than relying on fixed stored operating states. The control system dynamically optimizes fill levels, conveyor speeds, and machine parameters to maintain optimal efficiency across varying production conditions, resolving the contradiction between simplicity and effectiveness.
Solution Approach 2:
The patent introduces a feedback mechanism where sensors continuously monitor container flow, fill levels, and machine status, and this information is fed back to the control system for real-time adjustments. This closed-loop control enables continuous optimization of line efficiency without requiring complex pre-programmed operating states for every possible condition.
2Reliability
If continuous monitoring and model-based control are implemented, then pulsations in container flow and machine stop-start cycles are reduced, but energy consumption increases due to continuous data processing
Solution Approach 1:
The patent applies partial monitoring strategies where not all parameters are continuously monitored at full resolution. Instead, critical parameters affecting container flow stability are monitored continuously, while less critical parameters are sampled periodically or only when thresholds are exceeded. This reduces the computational burden and energy consumption while maintaining sufficient control over flow stability.
Solution Approach 2:
The patent implements predictive control using stored models that anticipate future system states, allowing the control system to make adjustments before pulsations or stop-start cycles occur. This proactive approach maintains container flow stability with less frequent intensive processing compared to reactive continuous correction, thereby reducing energy consumption while maintaining reliability.
3Loss of time
If model-based control with continuous optimization is used, then machine downtime is reduced, but the device complexity and difficulty of implementation increase
Solution Approach 1:
The patent stores pre-developed control models and optimization algorithms in the control system that have been developed offline using historical data and system modeling. During operation, these pre-prepared models are executed with minimal real-time computation, allowing the system to reduce machine downtime through predictive maintenance and optimized scheduling without requiring complex real-time optimization algorithms that would increase implementation difficulty.
Data Source
Figure 1
AI summary
The invention relates to a method for controlling a container treatment line (1) which comprises at least one machine (2, 3, 4) for treating containers, at least one transport unit (5, 6) for transporting the containers and a central control unit (7).The method comprises: - receiving first control data (14, 15, 16) from the at least one machine in the central control unit, receiving second control data (17, 18) from the at least one transport unit in the central control unit, - calculating a first control instruction for the at least one machine by means of a model-based control based on the first and second control data and/or calculating a second control instruction for the at least one transport unit by means of the model-based control based on the first and second control data, - sending the first control instruction to the at least one machine and/or sending the second control instruction to the at least one transport unit, - controlling the at least one machine according to the first control instruction and/or controlling the at least one transport unit according to the second control instruction.