Automated Batch Recall Assessment for Early Faulty Lot Detection
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Solution Overview
Problem
Traditional methods for product batch recall decisions are time-consuming, costly, and prone to human errors, leading to delays and potential harm to consumers and financial losses due to inefficient identification of defective batches.
Innovation Solution
An automated system for batch recall assessment that quantifies quality concerns for each product batch, compares them against predetermined threshold values, and uses a mapping table to determine a quality risk level, facilitating quick and accurate decisions on batch recalls.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional manual investigation methods are used to identify defective product batches, then human resources can make recall decisions, but the process becomes time-consuming and prone to human errors
Solution Approach 1:
The patent replaces manual human investigation with an automated computer-based system that collects quality data, processes it through algorithms, and generates recall recommendations automatically. This substitution eliminates human error and significantly reduces the time required for batch assessment while maintaining or improving decision accuracy.
Solution Approach 2:
The system enables self-service by automatically performing data collection, analysis, and recommendation generation without requiring human intervention at each step. The automated batch assessment system independently evaluates quality data and produces recall decisions, freeing human resources for higher-level oversight.
2Reliability
If comprehensive quality investigations are conducted to ensure consumer safety, then recall decisions can be well-informed, but the cost and complexity of the process increase
Solution Approach 1:
The patent segments the quality investigation process into distinct automated modules: data collection from multiple sources, quality parameter analysis, batch identification, and recommendation generation. This segmentation simplifies the overall complexity while maintaining comprehensive quality assessment through systematic processing of each component.
Solution Approach 2:
The automated system serves multiple functions within a single platform: it collects quality data, analyzes multiple quality parameters, identifies affected batches, generates recall recommendations, and provides a user interface for decision-making. This multi-functionality reduces the need for separate systems and tools, lowering overall complexity.
3Reliability
If manual quality checks and investigations are performed by dedicated human resources, then quality concerns can be assessed, but the process becomes costly and inefficient
Solution Approach 1:
The patent replaces manual quality checking and batch identification with automated computer-based processing. The system efficiently collects quality data, processes it through algorithms, and rapidly identifies affected batches, dramatically improving productivity while maintaining or enhancing assessment accuracy through consistent algorithmic application.
Solution Approach 2:
The automated system enables continuous operation without the breaks, fatigue, and resource constraints that limit manual processes. The system can continuously collect quality data, process batches, and generate recommendations without interruption, significantly improving overall productivity and response time.
Data Source
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AI summary
Approaches for automated batch recall assessment are described. The approach includes identifying product batches having a plurality of faulty products manufactured by the organization. For each of the identified product batches, a plurality of quality concerns raised for faulty products manufactured as part of the product batch are quantified. Accordingly, for each product batch, the quantified values of each of the plurality of quality concerns is compared with a corresponding pre-determined threshold count value to enable determination of a quality risk level associated with the product batch. Based on the quality risk level, a batch recall assessment is performed to determine whether to recall product batches having the plurality of faulty products. Thus, the described approaches provide an automated technique for early detection of problematic batches, facilitating quick decision-making on potential batch recalls and improving overall quality management in manufacturing processes.