Press Load Pattern Optimization for Forming Quality Control
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Setting an optimal load pattern for a press apparatus is complex and requires significant effort and expertise, often involving multiple trials and the use of analysis tools to minimize errors.
Innovation Solution
A press system with a controller that includes a load pattern generator, evaluation input unit, and an optimum load pattern setting unit using response surface generation and optimization calculations to efficiently set load patterns based on quality evaluations, allowing for simplified and accurate optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional analysis tools are used to optimize load patterns, then manufacturing precision can be improved, but device complexity and ease of operation deteriorate due to requiring expertise and complex procedures
Solution Approach 1:
The system creates a virtual copy of the press forming process through simulation, allowing optimization to be performed on a digital model rather than requiring complex physical analysis tools. The simulation model replicates the behavior of the actual press forming process, enabling optimization of load patterns through software-based evaluation instead of complex analytical methods
Solution Approach 2:
The system replaces complex mechanical analysis tools with an automated computer-based optimization system. Instead of requiring manual operation of sophisticated analysis software, the system uses automated algorithms that evaluate multiple load patterns through simulation and automatically determine optimal settings, substituting manual mechanical analysis with automated computational methods
2Manufacturing precision
If multiple trials are conducted to find optimum die cushion load, then manufacturing precision can be improved, but loss of time and productivity deteriorate
Solution Approach 1:
The system performs preliminary optimization through computer simulation before actual press forming production begins. By evaluating multiple load patterns and determining the optimal settings in advance through virtual testing, the system eliminates the need for multiple trial productions, achieving both high quality and efficient production from the start
Solution Approach 2:
The system uses a simulation model that copies the physical press forming process, allowing multiple trials to be conducted virtually rather than physically. This enables extensive optimization testing without consuming actual production time or materials, achieving high manufacturing precision without sacrificing productivity
3Manufacturing precision
If expertise in analysis tools is required to reduce analysis error, then manufacturing precision can be improved, but ease of operation deteriorates
Solution Approach 1:
The system performs self-service optimization by automatically evaluating multiple load patterns through simulation and autonomously determining the optimal settings. The computer-based system independently conducts the optimization process without requiring external expert intervention, achieving accurate results while maintaining operational simplicity
Solution Approach 2:
The system replaces the need for expert operators with an automated computer-based optimization system. Instead of relying on human expertise to operate complex analysis tools, the system uses automated algorithms that perform the optimization independently, eliminating the need for specialized knowledge while maintaining high accuracy
Data Source
AI summary
A press system includes a press portion and a controller configured to control the press portion. The controller includes a load pattern generator, an evaluation input unit, and an optimum load pattern setting unit configured to set an optimum load pattern based on a plurality of evaluations of the quality input by the evaluation input unit. The optimum load pattern setting unit includes a response surface generator configured to create from evaluation value data based on the plurality of load patterns and the plurality of evaluations of the quality, by using as an objective function, the evaluation value data with the load pattern being defined as a design variable, a response surface of the objective function, and an optimization calculator configured to find an optimum solution of the objective function of the response surface by optimization.


