Machining Process Control Using Dynamic Multi-Source Optimization
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Solution Overview
Problem
Industrial machining operations face challenges in optimizing performance criteria due to dynamic variables such as logistics, material properties, and operator needs, leading to inefficiencies, precision issues, and increased waste, especially in sheet metal working processes.
Innovation Solution
A method that integrates multiple data sources to dynamically monitor and control industrial machining processes, using real-time information to adjust process parameters and performance variables, optimizing tooling configurations, and minimizing tool changes to enhance productivity and reduce waste.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional production methods with individual part definitions are used, then manufacturing precision can be maintained, but productivity is reduced and waste increases
Solution Approach 1:
The patent merges multiple individual part definitions into a single unified production definition that encompasses multiple parts. This allows the system to process multiple parts simultaneously under one definition, eliminating the need to individually define each part and thereby increasing productivity while reducing waste through more efficient material utilization.
Solution Approach 2:
The patent creates a universal production definition that can serve multiple parts with different geometries and requirements. This multi-functional definition allows the same set of parameters and constraints to be applied across multiple parts, streamlining the manufacturing process and reducing the overall definition complexity and processing time.
2Manufacturing precision
If dynamic variables such as logistics, material properties, and operator needs are not considered, then process simplicity is maintained, but manufacturing precision deteriorates
Solution Approach 1:
The patent introduces dynamic variables including logistics constraints, material properties, and operator needs into the production definition system. These variables allow the system to adapt to changing conditions during manufacturing, ensuring precision is maintained even as external factors vary, while the structured integration keeps complexity manageable.
Solution Approach 2:
The patent incorporates feedback mechanisms that continuously monitor and adjust production parameters based on actual manufacturing conditions. By feeding information about material properties, logistics status, and operator requirements back into the system, the patent maintains precision through real-time adaptations without requiring overly complex manual interventions.
3Productivity
If tooling configurations are not optimized, then device complexity is reduced, but productivity decreases and waste increases
Solution Approach 1:
The patent performs preliminary optimization of tooling configurations during the definition phase, before actual manufacturing begins. By pre-calculating and pre-configuring optimal tooling arrangements based on part geometries and production requirements, the system eliminates the need for complex real-time adjustments during manufacturing, thereby increasing productivity while keeping operational complexity low.
Data Source
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AI summary
The present invention relates to a method for selecting optimum operation performance criteria for a metal working process. The method comprises the step of developing a process model relating process parameters for the operation with performance variables for said operation, wherein the process parameters and performance variables are retrievable via integrated multiple data sources, and selecting at least one optimization technique to define a function, said function comprising of process parameters. Moreover, generating the function for optimization by using acceptable tolerances of a product to be machined as a basis to define ranges for performance variables along with ranges for process parameters, and applying the at least one optimization technique to said function, whereby optimum operation performance criteria are calculated for the process model including process parameters and performance variables to obtain a set of requirements to be used for controlling the metal working process.