Hybrid Manufacturing Process Planning With AI State-Space Pruning
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Solution Overview
Problem
Generating process plans for hybrid manufacturing systems that combine additive and subtractive manufacturing processes is challenging due to the complexity of arbitrary multimodal sequences, which requires exploring a vast state transition space and is computationally expensive, and ensures manufacturability without prior process planning.
Innovation Solution
A system and method that use advanced artificial intelligence techniques to systematically explore viable process plans by decoupling geometric and spatial reasoning from logical and combinatorial search, allowing for rapid evaluation of manufacturability and optimization of hybrid manufacturing actions through canonical intersection terms and atomic decomposition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If arbitrary multimodal sequences of AM and SM actions are used in hybrid manufacturing, then manufacturing efficiency and possibilities are expanded, but the complexity of state space exploration increases significantly
Solution Approach 1:
The patent segments the complex state space exploration by separating geometric/spatial reasoning from logical/combinatorial search. This division allows each component to be handled independently using specialized algorithms, reducing the overall computational complexity while maintaining the ability to explore arbitrary multimodal sequences of AM and SM operations.
Solution Approach 2:
The patent introduces an intermediary representation system that bridges geometric modeling and process planning. By using canonical intersection terms and atomic decomposition as intermediate structures, the system enables efficient evaluation of manufacturability without requiring exhaustive exploration of all possible process sequences.
2Reliability
If full process planning is performed for arbitrary multimodal sequences, then manufacturability is ensured, but computational expense increases significantly
Solution Approach 1:
The patent performs preliminary geometric analysis and atomic decomposition before engaging in full process planning. This preliminary action identifies manufacturability constraints and feasible operation sequences in advance, allowing the system to prune invalid paths early and avoid computationally expensive exhaustive searches while still ensuring manufacturability.
Solution Approach 2:
The patent implements a two-stage approach where partial process planning (geometric analysis) is performed first to evaluate manufacturability, followed by selective full process planning only for promising candidates. This partial action approach ensures manufacturability verification without the computational cost of exhaustive planning for all possible sequences.
3Device complexity
If unimodal manufacturing sequences are used, then computational complexity is reduced, but manufacturing efficiency and flexibility are limited
Solution Approach 1:
The patent segments the process planning problem into independent geometric analysis and sequence optimization components. This segmentation allows the system to handle unimodal sequences efficiently while also supporting hybrid multimodal sequences when beneficial, achieving a balance between computational simplicity and manufacturing flexibility through modular architecture.
Data Source
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AI summary
A systematic approach to constructing process plans for hybrid manufacturing is provided. The process plans include arbitrary combinations of AM and SM processes. Unlike the suboptimal conventional practice, the sequence of AM and SM modalities is not fixed beforehand. Rather, all potentially viable process plans to fabricate a desired target part from arbitrary alternating sequences of pre-defined AM and SM modalities are explored in a systematic fashion. Once the state space of all process plans has been enumerated in terms of a partially ordered set of states, advanced artificial intelligence (AI) planning techniques are utilized to rapidly explore the state space, eliminate invalid process plans, for instance, process plans that make no physical sense, and optimize among the valid process plans using a cost function, for instance, manufacturing time and material or process costs.