Container Sampling Control for Microbiological Quality Assurance
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Solution Overview
Problem
Current quality control methods in container processing plants are not reliable enough to consistently meet stringent hygienic and microbiological quality requirements, relying heavily on user expertise and not adaptable to different conditions.
Innovation Solution
An automated system that determines a sampling plan using statistical logic to achieve a desired quality level, calculating the sample size and estimating microbiological quality based on input data such as production features and quality objectives, with a processing unit that includes a sampling-control module to manage acceptance sampling plans and provide indications of acceptable and rejectable quality levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual sampling and analysis methods are used based on production manager's expertise, then operational simplicity is maintained, but quality control reliability is insufficient
Solution Approach 1:
The system performs self-assessment of contamination risks by automatically collecting production data, analyzing it through statistical models, and generating sampling plans without requiring external expert intervention. The processing unit autonomously determines sample sizes and sampling frequencies based on real-time production conditions
Solution Approach 2:
Manual expert judgment and experience-based decision making are replaced with an automated electronic system that uses statistical logic and algorithms to determine sampling plans. The mechanical process of manual sampling determination is substituted with computational analysis performed by the processing unit
2Adaptability or versatility
If fixed sampling intervals are used regardless of production conditions, then operational simplicity is maintained, but adaptability to different production conditions deteriorates
Solution Approach 1:
The sampling plan is made dynamic by continuously adjusting sample sizes and sampling frequencies based on real-time production data. The system adapts to changing production conditions such as speed variations, container types, and product characteristics by recalculating optimal sampling parameters
Solution Approach 2:
The system changes key sampling parameters (sample size, sampling frequency, acceptance criteria) based on production conditions. Statistical parameters are adjusted according to production speed, container type, and risk assessment results, allowing the sampling plan to adapt to different operational scenarios
3Measurement precision
If larger sample sizes are used to improve quality assessment accuracy, then measurement precision is improved, but productivity and time consumption deteriorate
Solution Approach 1:
The system dynamically adjusts sample size parameters based on statistical requirements and production conditions. Instead of using fixed large sample sizes, the processing unit calculates optimal sample sizes that provide sufficient statistical precision while minimizing the number of tests required
Solution Approach 2:
The system uses feedback from production data and preliminary test results to adjust sampling intensity. When production conditions are stable and predictable, smaller sample sizes suffice. When variations are detected, the system increases sampling intensity to maintain quality assessment precision
Data Source
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AI summary
A system for quality control management in a plant (1) for processing containers, having a processing unit (12) to control a sampling of the containers to be carried out in order to evaluate production microbiological quality; wherein the processing unit (12) receives input data relating to a quality objective for the container processing plant (1); and determines, using a statistical logic, an acceptance sampling plan for sampling of the containers aimed to achieve the desired quality objective. In particular, the processing unit (12) has a sampling control module (14) to determine a sample size (N) for the acceptance sampling plan, corresponding to a number of containers to be sampled and analysed within groups of containers that are statistically considered either acceptable or rejectable based on the microbiological quality.