Press Eccentric Load Distribution for Early Mold Abnormality Detection
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Solution Overview
Problem
Conventional methods for press machines struggle to detect abnormalities in molds and defects in product accuracy within the range of the allowable eccentric load diagram, making it difficult to identify and address issues such as mold abnormalities and product defects.
Innovation Solution
A press machine and abnormality detection method that includes a detection unit for load values, a storage unit for associating load values with mold identification, a calculation unit for determining the load center and generating eccentric load distribution data, and a notification unit for alerting abnormalities, allowing for the detection of mold abnormalities and product defects beyond the conventional allowable eccentric load range.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the conventional method uses the allowable eccentric load diagram for press protection, then press machine safety is improved, but the ability to detect mold abnormalities and product defects is worsened
Solution Approach 1:
The patent segments the detection capability by creating multiple determination units: one that evaluates against the allowable eccentric load diagram for press protection, and another that evaluates against distribution data for mold abnormality detection. This allows simultaneous press safety monitoring and mold condition monitoring without interference
Solution Approach 2:
The patent adds a new detection dimension by introducing distribution data representing normal eccentric load patterns for each mold. Instead of relying solely on the absolute allowable limit, the system now detects abnormalities by comparing actual measurements against the statistical distribution of normal operation, enabling detection within the allowable range
2Device complexity
If the conventional method only detects abnormalities outside the allowable eccentric load range, then press protection is simplified, but early detection of mold abnormalities is lost
Solution Approach 1:
The system performs preliminary action by collecting and storing distribution data during normal operation phases. This historical data is prepared in advance to enable rapid comparison and detection when abnormalities occur, allowing early detection without adding complex real-time analysis requirements
Solution Approach 2:
The patent implements feedback by continuously comparing actual eccentric load measurements against the stored distribution data for each mold. This feedback mechanism provides real-time detection of deviations from normal patterns, enabling timely alerts while maintaining relatively simple system architecture
Data Source
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AI summary
A press machine includes: a detection unit that detects a load value during press process on a material to be processed; a storage unit that stores the load value detected by the detection unit in association with identification information of a mold attached to the press machine during detection of the load value; a calculation unit that calculates a position of a load center acting on the press machine based on the stored load value, calculates the calculated position of the load center as an eccentric amount from a center of the press machine to obtain an eccentric load, and generates distribution data of the eccentric load for each mold; a determination unit that determines an abnormality based on the eccentric load obtained on the basis of the load value detected by the detection unit and the distribution data of the eccentric load corresponding to the mold attached to the press machine during detection of the load value; and a notification unit that notifies an abnormality based on a determination result of the determination unit.