Process Pattern Generation for Hybrid Additive-Subtractive Machining
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Solution Overview
Problem
Conventional machining devices require user expertise to combine multiple machining devices for optimal material removal and addition, making it difficult for inexperienced users to determine suitable manufacturing processes.
Innovation Solution
A process decision support device that generates and displays process patterns combining machining steps from multiple devices, including additive and removal machining, based on design data and machining performance data, allowing users to select appropriate manufacturing processes without trial and error.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple machining devices are combined for optimal manufacturing, then productivity and manufacturing precision are improved, but device complexity and ease of operation worsen due to requiring user expertise
Solution Approach 1:
The machining device automatically determines the optimal manufacturing process by itself using the determination unit, which evaluates multiple process patterns and selects the best one based on predefined criteria. This eliminates the need for user expertise in combining multiple machining devices, as the system performs the complex determination autonomously while still achieving optimal productivity and precision.
Solution Approach 2:
The patent replaces the manual expert judgment system with an automated computer-based determination system. The determination unit uses algorithms and data processing to evaluate process patterns, substituting the need for human expertise with an automated computational approach that objectively selects the optimal manufacturing process.
2Manufacturing precision
If multiple machining devices are combined for optimal manufacturing, then manufacturing precision is improved, but ease of operation worsens due to requiring trial and error
Solution Approach 1:
The system performs preliminary determination of the optimal manufacturing process before actual machining begins. The determination unit evaluates multiple process patterns in advance and selects the best one, allowing users to directly implement the predetermined optimal process without trial and error during production, thus maintaining high machining accuracy while simplifying operation.
Solution Approach 2:
The determination unit uses feedback from machining performance data and process pattern evaluation to automatically select the optimal manufacturing process. This closed-loop approach ensures that the system learns from past performance and continuously improves its selections, providing users with reliably accurate processes without requiring their expertise or trial-and-error experimentation.
3Ease of operation
If automated process determination is implemented, then ease of operation is improved, but device complexity increases
Solution Approach 1:
The determination unit serves multiple functions: it evaluates process patterns, determines optimal manufacturing processes, and adapts to different machining scenarios. By consolidating these diverse functions into a single multi-functional component, the system improves ease of operation without proportionally increasing overall device complexity, as the determination unit handles various tasks within a unified framework.
Data Source
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AI summary
A process determination assistance device (100) is provided with: a processing performance data storage unit (15) which stores processing performance data representing the processing performance of each processing device of a plurality of processing devices that include processing devices for adding material and processing devices for removing material; a process pattern generation unit (17) which refers to the processing performance data and generates a process pattern, which is a combination of processing processes that can produce a product, by sequentially allocating processing processes performed by a combination of some of the plurality of processing devices; and an output unit (13) which outputs the content of the process pattern generated by the process pattern generation unit (17).