Inspection Result Prediction Using Routing Environment Data
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Solution Overview
Problem
Existing inspection systems fail to accurately predict inspection results due to the influence of environmental conditions on the state of inspection targets before inspection, leading to potential errors in determining product quality.
Innovation Solution
An inspection information prediction apparatus that acquires environment and manufacturing information from various stages of the inspection target's processing and storage, using a correction-amount calculation model to predict inspection results, thereby accounting for temperature and other environmental influences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If environmental conditions are not considered in inspection prediction, then the inspection system is simple, but prediction accuracy deteriorates due to environmental influences on inspection target state
Solution Approach 1:
The system performs preliminary acquisition of environment information from routing steps before inspection occurs. By collecting temperature, humidity, and other environmental data in advance from where the inspection target has been routed, the system prepares correction data before the actual inspection, enabling accurate prediction while maintaining a relatively simple system architecture.
Solution Approach 2:
The system introduces environment information as an intermediary element that mediates between the inspection target state and the inspection result. This intermediary data allows the prediction unit to account for environmental influences without directly modifying the inspection process itself, resolving the contradiction by adding a data layer rather than a complex physical system.
2Measurement precision
If environmental information from routing steps is acquired and considered, then prediction accuracy improves, but information processing complexity increases
Solution Approach 1:
The system extracts only the necessary environment information from routing steps that has actual influence on the inspection target state. Rather than processing all possible environmental data, the system selectively acquires temperature, humidity, and other relevant parameters from specific routing locations, reducing information processing load while maintaining determination accuracy.
Solution Approach 2:
The system applies different environmental information from different routing steps according to where the inspection target was actually located. Each routing step's environment information is applied locally to correct the inspection result based on the specific conditions at that location, rather than applying a uniform correction, which optimizes the information processing efficiency.
Data Source
AI summary
An inspection information prediction apparatus includes an environment-information acquisition unit that acquires environment information of a routing step through which an inspection target has been routed before an inspection step of inspecting the inspection target, a manufacturing-information acquisition unit that acquires manufacturing information of the inspection target, and a prediction unit that predicts inspection information which indicates an inspection result of an inspection portion of the inspection target determined by the manufacturing information and is obtained by applying the environment information, based on the manufacturing information of the inspection target and the environment information of the routing step through which the inspection target has been routed.