Press Forming Condition Control for Defect-Stable Press Lines
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Solution Overview
Problem
In mass production press forming of vehicle body components, existing methods struggle to consistently prevent forming defects such as cracking, wrinkling, and dimensional accuracy issues without requiring significant labor and cost, as they fail to account for fluctuations in material characteristics and die conditions.
Innovation Solution
A press line equipped with sensors and a control device using machine learning models to calculate and adjust press forming conditions based on real-time material characteristic measurements and manufacturing information, enabling feedforward and feedback control to prevent defects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional press forming control methods are used, then basic production continues, but forming defects occur due to material characteristic fluctuations and die condition changes
Solution Approach 1:
The patent implements feedback control by measuring actual material characteristic values (tensile strength, elongation, n-value, r-value) during production and using these measurements to dynamically adjust press forming conditions. The system continuously monitors material properties and feeds this information back to the control device, which then modifies forming parameters to prevent defects, thereby resolving the contradiction between maintaining stable mass production and preventing forming defects caused by material fluctuations.
Solution Approach 2:
The patent applies preliminary action by measuring material characteristic values before press forming operations and pre-calculating appropriate forming conditions based on these measurements. The control device determines optimal press forming parameters in advance, before the actual forming process begins, allowing the system to proactively prevent forming defects rather than reacting to them after they occur.
2Manufacturing precision
If material characteristic values are measured and press forming conditions are dynamically adjusted, then forming defect occurrence is inhibited, but measurement and control complexity increases
Solution Approach 1:
The patent applies self-service by implementing an automated measurement and control system that independently handles material characterization and press forming condition determination. The measurement device automatically measures material characteristic values, the control device autonomously processes this data and calculates optimal forming conditions, and the system self-adjusts without requiring manual intervention. This automation reduces the operational complexity burden on operators while maintaining high manufacturing precision.
3Manufacturing precision
If comprehensive material characterization and real-time control are implemented, then forming defects are prevented, but production cost increases
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting press forming conditions (such as forming speed, load, and temperature) based on measured material characteristic values. Instead of using fixed forming parameters, the system modifies these parameters in real-time according to the actual material properties, allowing optimal forming conditions to be achieved without requiring expensive trial-and-error processes or excessive safety margins, thereby controlling production costs while maintaining high manufacturing precision.
Data Source
AI summary
A press line includes: a first press machine configured to shear an outer peripheral portion of a metal material by using a blanking die; a second press machine configured to form a press-formed component by performing press forming on the sheared metal material with a forming die; a preprocessing device configured to perform predetermined preprocessing on the metal material; a measurement instrument configured to measure information on a material characteristic value of the metal material before the press forming; and a control device configured to calculate a press forming condition for inhibiting occurrence of a forming defect for a metal material to be formed by inputting the material characteristic value of the metal material to be formed and manufacturing information to a machine learning model.