Casting Process Control Using Metamodels and Steady-State Detection

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Solution Overview

Problem

The existing methods for determining process parameters for casting devices are time-consuming and costly, as they rely on trial and error, require extensive computer simulations, and often simulate components before reaching a steady state, leading to inefficient use of resources and potential defects in cast components.

Innovation Solution

A method that involves test point calculation, casting process simulation, and optimization using metamodels to efficiently determine robust process parameters by simulating components until a steady state is reached, reducing the number of simulations needed and incorporating input and output constraints to optimize parameter selection.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If the number of shots per test point is increased to ensure steady state is reached, then the reliability of simulation results is improved, but the computing time and cost increase significantly

Engineering Contradiction:
Improvereliability of simulation resultsVSAvoidcomputing time
Core Design Contradiction:
ReliabilityVSLoss of time

Solution Approach 1:

The patent applies preliminary action by implementing an automatic steady state detection mechanism before the user-defined number of shots is completed. The system monitors temperature development during the shooting process and automatically terminates simulations once steady state is detected, preventing unnecessary additional shots. This resolves the contradiction by ensuring reliability through adequate shooting while avoiding wasteful extension of computing time.

Inventive Principle:
Principle #10Preliminary action

2Manufacturing precision

If the number of test points is increased to cover the parameter space, then the manufacturing precision is improved, but the computing capacity requirements increase enormously

Engineering Contradiction:
Improveprecision of process parametersVSAvoidcomputing capacity
Core Design Contradiction:
Manufacturing precisionVSPower

Solution Approach 1:

The patent applies partial action by implementing adaptive sampling strategies that focus computational resources on critical regions of the parameter space. Rather than uniformly distributing test points, the system identifies and concentrates simulations in areas where parameter variations most significantly affect component quality. This resolves the contradiction by achieving sufficient manufacturing precision through targeted testing while reducing overall computing capacity requirements.

Inventive Principle:
Principle #16Partial or excessive action

3Productivity

If simulations are performed with user-defined number of shots without steady state detection, then the productivity is improved, but the quality of results deteriorates due to premature evaluation

Engineering Contradiction:
Improvesimulation speedVSAvoidquality of simulation results
Core Design Contradiction:
ProductivityVSManufacturing precision

Solution Approach 1:

The patent applies feedback by implementing a closed-loop steady state detection system that continuously monitors temperature development during simulations and provides real-time feedback on convergence status. The system compares temperature values between successive shots and automatically determines when steady state has been achieved. This resolves the contradiction by maintaining high productivity through efficient termination while ensuring result quality through objective steady state verification.

Inventive Principle:
Principle #23Feedback

Data Source

PatentUS20240269738A1Method for process design for a casting device and method for controlling a casting device
Publication Date: 2024.08.15 MARTINREA HONSEL GERMANY
  • US20240269738A1 patent drawing
  • US20240269738A1 patent drawing
  • US20240269738A1 patent drawing

AI summary

A method for quickly finding robust operating points of a casting process is disclosed. Metamodels and extrapolatable models contribute to reducing the experimental effort both in simulation and for practical experiments, and these models are subsequently used for autonomous control of the casting process.