Machining Parameter Optimization Across Unified Process Data
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Solution Overview
Problem
Industrial machining operations face inefficiencies due to rigid manufacturing processes and separate data storage locations, preventing optimal utilization of production means and leading to suboptimal productivity, precision, and quality.
Innovation Solution
A method for modifying process parameters using non-sequential optimization based on optimum operation performance criteria, which inputs standard parameters from multiple sources, generates operational data, selects optimization techniques, and adjusts performance variables to achieve predefined product properties, allowing for dynamic adjustments in tooling, material, and production processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If standard manufacturing processes are used with separate data storage locations, then data can be stored and processed, but productivity and efficiency are reduced due to inability to synchronize and optimize across the entire manufacturing process
Solution Approach 1:
The patent merges separate data storage locations into a unified data structure where all manufacturing parameters, process data, and performance metrics are stored together in a centralized database. This allows the optimization system to access and synchronize data across the entire manufacturing process, enabling global optimization rather than isolated local optimizations, thereby resolving the contradiction between productivity improvement and system complexity.
Solution Approach 2:
The patent creates a universal optimization system that can handle multiple types of manufacturing operations (cutting, drilling, milling, turning, welding, etc.) and multiple data types (process parameters, performance metrics, tooling data, material data) through a single integrated platform. This multi-functional system improves productivity across diverse operations while managing complexity through standardized data structures and optimization algorithms.
2Adaptability or versatility
If rigid manufacturing processes are followed, then process stability is maintained, but adaptability to optimize production means utilization is reduced
Solution Approach 1:
The patent implements dynamic optimization where manufacturing processes are no longer rigid but can adapt in real-time based on actual machine performance, tooling conditions, and material properties. The system continuously adjusts process parameters during manufacturing operations, allowing the process to respond to changing conditions while maintaining stability through controlled, algorithm-driven modifications rather than arbitrary changes.
Solution Approach 2:
The patent incorporates feedback mechanisms where performance data from manufacturing operations is continuously collected, analyzed, and used to adjust process parameters. The optimization system receives feedback on actual machining results, tool wear, material responses, and machine performance, then uses this feedback to refine and adapt the manufacturing process, balancing adaptability with stability through data-driven decision-making.
3Loss of information
If data is stored at separate locations, then data storage is simplified, but exchange and comparison of process parameters is prevented, reducing optimization capability
Solution Approach 1:
The patent consolidates data from multiple separate storage locations into a unified database structure that enables seamless exchange and comparison of process parameters. The centralized data structure integrates manufacturing parameters, machine data, tooling information, and performance metrics into a single accessible repository, eliminating data silos and enabling comprehensive optimization across the entire manufacturing process.
4Productivity
If conventional CNC systems with physical machine controllers are used, then machine control is reliable, but versatility and productivity optimization are limited
Solution Approach 1:
The patent introduces an intermediary optimization system that sits between the conventional CNC machine controller and the manufacturing process. This intermediary software layer receives process parameters and performance data, performs optimization calculations, and generates optimized control instructions without replacing the reliable physical machine controller. The intermediary acts as a bridge that enhances productivity and versatility while maintaining the stability and reliability of the existing control architecture.
Data Source
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AI summary
The present invention relates to method for modifying process parameters based on optimum operation performance criteria for a metal working process, said method comprising the steps of inputting standard process parameters for at least one product to be machined and generating operational data based on the standard process parameters. Operational data is compared with optimized operation performance criteria and is presented to a decision- making entity. This entity may be allowed to modify the process parameters so as to improve operation of the metal working process.