Additive Manufacturing Batch Scoring for 3D Product Positioning
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Solution Overview
Problem
The productivity of additive manufacturing processes is hindered by the need to accommodate three-dimensional products with varying dimensions and characteristics, leading to inefficient displacements of the manufacturing head.
Innovation Solution
A method for determining batches of three-dimensional products based on scoring systems that consider geometric, added value, and manufacturing characteristics, optimizing the organization and positioning of products to enhance manufacturing efficiency and delivery priority.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If three-dimensional products with different dimensions and characteristics are manufactured in the same batch, then batch manufacturing productivity is improved, but the manufacturing head displacement efficiency deteriorates
Solution Approach 1:
The batch of products is segmented into sub-groups based on similar characteristics (dimensions, manufacturing parameters, delivery priorities). This segmentation allows the manufacturing head to process products with similar displacement requirements together, reducing unnecessary movements while maintaining batch manufacturing efficiency.
Solution Approach 2:
A scoring system is implemented that assigns numerical values to product characteristics (geometric parameters, manufacturing properties, delivery priorities). This parameter transformation enables systematic comparison and grouping of products, optimizing batch composition to minimize manufacturing head displacement time while maximizing productivity.
2Loss of time
If products are grouped by similar characteristics, then manufacturing head displacement efficiency is improved, but batch flexibility deteriorates
Solution Approach 1:
The scoring system transforms multiple product characteristics into a single numerical score, enabling flexible and dynamic batch composition. This parameter consolidation allows the system to adapt to different product mixes while maintaining optimization criteria, balancing displacement efficiency with batch flexibility.
Solution Approach 2:
The batch determination is performed dynamically based on the specific characteristics of ordered products rather than using fixed batch templates. This dynamic approach allows the system to adapt batch composition to current production needs while optimizing for manufacturing head displacement efficiency.
3Loss of time
If delivery priority is considered in batch determination, then product delivery timeliness is improved, but manufacturing process complexity increases
Solution Approach 1:
Delivery priority is converted into a numerical parameter within the scoring system, allowing it to be systematically integrated with other product characteristics. This parameter transformation simplifies the complexity by providing a unified quantitative framework for considering multiple factors including delivery timing.
Solution Approach 2:
The scoring system creates a simplified numerical representation (copy) of complex product characteristics and delivery requirements. This abstraction allows the batch determination algorithm to work with simplified data structures while still capturing the essential factors needed for timely delivery optimization.
Data Source
AI summary
Disclosed is a method implemented by computer for determining a batch of a number n>1 of three-dimensional products to be manufactured by an additive manufacturing technology, the method including: —a step of receiving at least one order for manufacturing a product by the additive manufacturing technology; —a step of determining a score associated with the product from a set of data included in the at least one order, the score being representative of at least one product's characteristic; —a step of assigning to the batch n products having a corresponding score; and—a step of providing an additive manufacturing machine with the set of data of each product assigned to the batch.