Composite Feature Machining Strategy Selection in CAM

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Solution Overview

Problem

Current computer-aided manufacturing (CAM) processes for subtractive manufacturing are time-consuming and require extensive experience, as they involve complex decision-making for machining operations, often leading to inefficiencies and potential tool damage due to the lack of automated strategies for machining composite geometric features.

Innovation Solution

A method and system that utilize a database of codified strategies for machining different geometric features, allowing users to select and adapt strategies based on priorities like part quality, yield, and productivity, and enabling the use of composite strategies that consider the interaction of geometric subfeatures for improved machining efficiency.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Manufacturing precision

If traditional CAM programming is used to manually plan machining operations, then manufacturing precision and quality can be achieved through experienced judgment, but the process requires extensive time and experience from CAM programmers

Engineering Contradiction:

Improvemanufacturing qualityVSAvoidprogramming time

Core Design Contradiction:

Manufacturing precisionVSLoss of time

Solution Approach 1:

The system enables automatic machining strategy selection where the computer automatically identifies geometric features, queries the database for composite features, and selects appropriate strategies without requiring manual intervention from CAM programmers. This self-service approach eliminates the need for experienced programmers to manually analyze each feature while maintaining high manufacturing quality through database-stored expert knowledge.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces the mechanical system of manual CAM programming with an automated computer-based system that uses database queries and algorithms to select machining strategies. This substitution transforms the manual, experience-dependent process into an automated, knowledge-based system that rapidly generates machining plans without requiring human expertise in the programming phase.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Reliability

If manual trial and error methods are used to optimize machining parameters, then suitable solutions can be reached through experience, but the process becomes time-consuming and inefficient

Engineering Contradiction:

Improvemachining strategy suitabilityVSAvoidmanufacturing efficiency

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The system performs preliminary action by pre-storing optimized machining strategies for various geometric features in a database. When a composite feature is detected, the system queries this database and retrieves pre-vetted strategies, eliminating the need for time-consuming trial and error during actual programming. The expert knowledge is prepared in advance and readily applied.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system incorporates feedback mechanisms where machining results and performance data are used to refine and update the database of strategies. This feedback loop ensures that the stored strategies continue to be reliable and optimized based on actual machining outcomes, improving both reliability and productivity over time.

Inventive Principle:

Principle #23Feedback

3Productivity

If composite strategies for machining are implemented, then productivity and surface quality are improved by optimizing entire features, but the system complexity increases due to database management and feature recognition

Engineering Contradiction:

Improvemanufacturing speedVSAvoidsystem complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The system applies segmentation by breaking down complex composite geometric features into their constituent sub-features for analysis. The feature recognition system identifies individual geometric elements (cylinders, cones, spheres, etc.) within composite features, queries the database for each component, and synthesizes appropriate composite strategies. This segmentation approach manages system complexity by processing features in manageable parts while achieving optimized overall results.

Inventive Principle:

Principle #1Segmentation

Data Source

PatentEP3582047B1Selection of a strategy for machining a composite geometric feature

Publication Date: 2022.08.17 SANDVIK MACHINING SOLUTIONS AB

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AI summary

A method (600) and a corresponding system (180) and computer program are provided. A model (150) of an object (400) to be manufactured via subtractive manufacturing is obtained (601). Geometric features (403, 404, 405) to be machined as part of manufacturing the object are identified (602) based on the model. The identified geometric features include a composite geometric feature (405) including a plurality of geometric subfeatures (401, 402). A database (170) including strategies for machining different geometric features is accessed (603). The database includes a composite strategy for machining the composite geometric feature and separate strategies for machining the respective geometric subfeatures. Strategies for machining the respective geometric features are selected (604) from the strategies included in the database. Instructions for causing one or more machine tools (110) to manufacture the object in accordance with the selected strategies are provided (605). Selecting strategies for machining the respective geometric features via subtractive manufacturing comprises selecting the composite strategy for machining the composite geometric feature.