Manufacturing Route Control for Targeted Final Metal Properties
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In metal product manufacturing, it is complex to produce customer-specific products from existing stock, as existing methods struggle to accurately control the transformation of intermediate metal products into final products with desired characteristics, often resulting in deviations that exceed predefined thresholds.
Innovation Solution
An electronic controlling device and method that acquires intermediate product characteristics, predicts final product characteristics using prediction models, compares these with target characteristics, and calculates new manufacturing routes to align with target specifications, incorporating transformation actions like hot rolling, cold rolling, and coating to minimize deviations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If existing manufacturing methods are used to transform intermediate metal products into final products, then production can proceed with current processes, but the final product characteristics deviate from target specifications
Solution Approach 1:
The system performs preliminary actions by acquiring intermediate product characteristics before final manufacturing, predicting final characteristics in advance, and calculating optimal manufacturing routes beforehand. This allows the system to proactively adjust processes to meet target specifications rather than reacting after deviations occur.
Solution Approach 2:
The system implements feedback by comparing predicted final characteristics with target characteristics, detecting deviations, and using this information to calculate and adjust manufacturing routes. This closed-loop feedback mechanism ensures continuous improvement and alignment with target specifications.
2Manufacturing precision
If manufacturing routes are dynamically adjusted to meet target characteristics, then product quality improves, but process complexity increases
Solution Approach 1:
The system replaces complex mechanical trial-and-error adjustment processes with computational methods. Prediction models and optimization algorithms automatically calculate optimal manufacturing routes, substituting physical experimentation with digital computation to reduce overall system complexity.
Solution Approach 2:
The system introduces an intermediary computational layer between intermediate products and final manufacturing. This intermediary layer includes prediction models and optimization algorithms that translate intermediate characteristics into optimal manufacturing parameters, simplifying the control process while improving precision.
Data Source
AI summary
A method for controlling a manufacturing of final metal product(s) from intermediate metal product(s) is implemented by an electronic controlling device and comprises, for each intermediate metal product acquiring (110) a set of intermediate characteristic(s) (CIP) for said intermediate metal product; determining (120) a current estimated set of final characteristic(s) (Cest_cur) with a prediction model, according to the set of intermediate characteristic(s) and a current manufacturing route; comparing (130) the current estimated set of final characteristic(s) with a current target set of final characteristic(s) (Ctarget_cur); and if a deviation between the current estimated set of final characteristic(s) and target set of final characteristic(s) is above a threshold obtaining (140) new target set(s) of final characteristic(s) (Ctarget_new) for new final metal product(s); and calculating (150) a new manufacturing route according to the set of intermediate characteristic(s) and to the new target set(s) of final characteristic(s).