Machining Knowledge Model for Closed-Loop NC Process Optimization
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Solution Overview
Problem
Current numerical control machining processes in industries like aviation and aerospace face challenges with inefficiency, poor stability, and lack of knowledge accumulation, leading to extended development cycles and unpredictable machining outcomes due to reliance on manual experience and lack of closed-loop control and seamless data connectivity.
Innovation Solution
A method that constructs a machining knowledge data model integrating programming, post-processing, cutting simulation, monitoring, and inspection to achieve closed-loop control and knowledge reuse through feature similarity evaluation and data integration across the machining cycle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual experience-based process design is used, then flexibility in handling complex machining tasks is maintained, but process preparation time becomes excessively long and efficiency is low
Solution Approach 1:
The patent pre-establishes a machining knowledge base containing process schemes, cutting parameters, and machining expertise before actual machining tasks. When a new machining task arrives, the system quickly retrieves and adapts pre-stored knowledge rather than designing from scratch, dramatically reducing process preparation time while maintaining quality
Solution Approach 2:
The patent creates a digital copy of machining knowledge and process schemes in the form of structured data models and knowledge bases. These digital copies can be rapidly retrieved, reused, and adapted across different machining tasks, eliminating the need to manually recreate process designs and significantly improving efficiency
2Reliability
If human-computer interaction mode is used, then process design flexibility is maintained, but process quality stability deteriorates due to reliance on individual expertise
Solution Approach 1:
The patent implements a closed-loop feedback mechanism where machining results, quality data, and process outcomes are continuously fed back into the knowledge base. This feedback loop enables the system to learn from actual machining performance, automatically adjust process parameters, and improve quality stability over time while managing system complexity through structured data models
Solution Approach 2:
The patent develops a universal machining knowledge base that consolidates expertise across multiple domains including process planning, cutting parameters, tool selection, and quality control into a single integrated system. This universal knowledge repository serves all machining tasks regardless of complexity, ensuring consistent quality standards while reducing dependence on individual expert knowledge
3Loss of information
If traditional process design methods are used, then implementation simplicity is maintained, but knowledge accumulation and inheritance become impossible
Solution Approach 1:
The patent implements a nested data model structure where machining knowledge is organized in hierarchical layers: basic machining data at the core, surrounded by process schemes, then cutting parameters, and finally application-specific optimizations. This nested structure enables systematic knowledge accumulation and inheritance while managing complexity through organized data relationships that can be progressively built and reused
Data Source
AI summary
A numerical control process design and optimization method based on machining knowledge includes: constructing a machining knowledge data model by taking a machining feature as a carrier, performing ordered integration on various stages of programming, post-processing, cutting simulation, machining process monitoring and inspection, and machining result measurement, determining various storage data types, and storing data in each stage. By means of the numerical control process design and optimization method, data stream during the whole flow of product machining are connected; effective accumulation of knowledge in a full cycle of product machining is realized; a numerical control process basic data model is constructed by means of establishing an association relationship between machining knowledge and a feature of a part.