Predictive Quality Control for Targeted Manufacturing Inspection
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Solution Overview
Problem
The existing quality control methods for manufacturing processes, such as those for magnetic tape cartridges, incur high inspection costs due to the need for extensive sampling inspections to guarantee product quality, leading to increased costs and resource allocation.
Innovation Solution
A quality control device and method that utilizes a prediction model generated from known process data and quality measurements to identify products with the smallest margin to a preset standard, allowing for targeted inspections and reducing the number of products needing quality checks, thereby minimizing costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the number of products as the inspection target is increased to guarantee quality, then quality guarantee is improved, but inspection cost is increased
Solution Approach 1:
The system performs preliminary quality prediction using a prediction model before actual inspection. By predicting quality based on process data and deriving a predictive value, the system identifies which products are likely to fail quality standards in advance, allowing targeted inspection of only those products rather than inspecting all products or using extensive sampling.
Solution Approach 2:
The prediction model automatically evaluates product quality based on process data without requiring manual inspection of all products. The system serves itself by using historical process data and quality measurements to build a model that autonomously predicts quality outcomes, reducing the need for extensive human-led sampling inspections.
2Quantity of substance
If sampling inspection is performed to reduce inspection cost, then inspection cost is reduced, but quality guarantee is weakened
Solution Approach 1:
The system performs preliminary quality prediction using a prediction model before actual inspection. By predicting quality based on process data and deriving a predictive value, the system identifies which products are likely to fail quality standards in advance, allowing targeted inspection of only those products rather than inspecting all products or using extensive sampling.
Solution Approach 2:
The system changes the approach from physical sampling inspection to predictive parameter-based quality assessment. By using process parameters and quality parameters in the prediction model, the system transforms quality control from a physical inspection task to a data-driven prediction task, enabling cost-effective quality guarantee.
3Reliability
If extensive sampling inspection is performed, then quality of all products can be guaranteed, but inspection time is increased
Solution Approach 1:
The system performs preliminary quality prediction using a prediction model before actual inspection. By predicting quality based on process data and deriving a predictive value, the system identifies which products are likely to fail quality standards in advance, allowing targeted inspection of only those products rather than inspecting all products or using extensive sampling.
Solution Approach 2:
The system extracts only the necessary inspection targets from the entire product batch by using the prediction model to identify products with predictive values closest to quality standards. This extraction principle allows the system to focus inspection resources only on products that truly need inspection, eliminating wasted time on products that are clearly compliant or non-compliant.
Data Source
AI summary
A quality control device that controls quality of a product manufactured through a plurality of processes, includes a prediction model generation unit that generates a prediction model to predict quality of a product with respect to unknown process data by performing learning using known process data obtained from the plurality of processes and a measured value of quality of the product with respect to the known process data as learning data; a quality prediction unit that derives a predictive value of quality of each of a plurality of products, which are manufactured after the prediction model is generated, on the basis of the prediction model using process data of the plurality of products as input data; and an inspection target decision unit that decides the product for which the predictive value having the smallest margin with respect to a preset standard is obtained as an inspection target, among the plurality of predictive values of quality obtained by the quality prediction unit.