Manufacturing Equipment Defect Cause Identification From Member Data
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Solution Overview
Problem
Existing manufacturing equipment inspection methods fail to conclusively identify the direct cause of defects, often requiring expert knowledge and trial-and-error approaches to determine whether defects are due to device members, components, or process-related issues, leading to inefficient maintenance and quality management.
Innovation Solution
A management system that acquires and analyzes product and device member information, along with quality inspection data, to specifically identify the cause of abnormalities in manufacturing equipment, including the use of quality indices to determine abnormality and automate the identification of defect causes, thereby preventing unnecessary maintenance and improving efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If inspection devices are installed to automate defect detection, then productivity is improved, but device complexity increases
Solution Approach 1:
The system automatically collects inspection results, device member information, and product member information without manual intervention. The abnormality cause identification unit autonomously analyzes the collected data and identifies defect causes, eliminating the need for expert knowledge and trial-and-error approaches.
Solution Approach 2:
The system establishes a feedback loop where inspection results are continuously collected and fed back to the abnormality cause identification unit. This feedback mechanism enables real-time quality management and automatic adjustment of manufacturing processes based on detected abnormalities.
2Measurement precision
If proportion defective information is presented by device members, then measurement precision is improved, but reliability of defect cause identification deteriorates
Solution Approach 1:
The system segments the defect analysis by collecting information for each device member (e.g., each nozzle in a mounter) and each product member (e.g., each component). This segmentation enables precise identification of which specific device member caused which specific defect, rather than just showing aggregate proportions.
Solution Approach 2:
The system merges multiple information sources including inspection results, device member information (type, model, serial number), and product member information (component type, position). By combining these data sets, the system achieves reliable defect cause identification that goes beyond simple proportion measurements.
3Manufacturing precision
If expert knowledge is used to identify abnormality causes, then manufacturing precision is improved, but loss of time increases
Solution Approach 1:
The system replaces the mechanical process of expert analysis with an automated information processing system. The abnormality cause identification unit uses algorithms to automatically analyze collected data and identify defect causes, substituting human expert knowledge with automated computational analysis that is both accurate and rapid.
Solution Approach 2:
The system performs preliminary data collection and organization before abnormality analysis is needed. Inspection results, device member information, and product member information are continuously collected and stored in advance, so when a defect occurs, the analysis can immediately use pre-organized data without time-consuming data gathering.
4Adaptability or versatility
If trial-and-error methods are used for maintenance, then adaptability is improved, but productivity deteriorates
Solution Approach 1:
The system automatically identifies abnormality causes and provides actionable insights without requiring maintenance personnel to perform trial-and-error diagnostics. The automated identification of specific device members and their abnormal states enables direct, targeted maintenance actions that eliminate unnecessary trial-and-error procedures.
Data Source
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AI summary
A technology for specifically identifying whether one of a device member, a product member, and a combination of the device member and the product member is a direct cause of a defect in manufacturing equipment of products and causing maintenance and quality management of equipment to be efficient is provided. A management system is a management system of manufacturing equipment that includes one or more manufacturing devices including one or more device members and one or more inspection units that inspect a quality of the product and includes a product member information acquisition unit, a device member information acquisition unit, a quality information acquisition unit, and an abnormality analysis unit.