3D Printed Repair of Non-Conforming Objects Using Digital Twins
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Consumers face challenges in finding easy solutions to fix defective products, as existing 3D printing technologies rely on standard parts and lack automated methods to identify and address non-conformities in consumer products, leading to inefficiencies and additional costs for manufacturers.
Innovation Solution
A system that analyzes image data of a non-conforming object against a digital twin, generates 3D printing instructions to alter the object, and utilizes crowdsourced data to select the best ameliorative solutions, automatically identifying and implementing fixes without user intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If standard 3D printing methods are used to create replacement parts, then manufacturing capability is provided, but the ability to address non-conforming objects is limited
Solution Approach 1:
The system enables the non-conforming object to essentially repair itself by providing 3D printing instructions that allow users to create corrective parts. The object's defect information is automatically analyzed and converted into actionable printing instructions, eliminating the need for complex external repair systems.
Solution Approach 2:
The patent replaces traditional mechanical repair methods with automated image analysis and digital 3D printing instructions. Instead of physical inspection and manual creation of repair parts, the system uses digital image processing and automated instruction generation to address defects.
2Productivity
If manual analysis of defective products is performed, then customization is possible, but time consumption and labor costs increase
Solution Approach 1:
The system replaces manual visual inspection and analysis with automated image processing algorithms. The processor automatically compares captured images against digital twin models to identify defects, eliminating time-consuming manual examination while maintaining high accuracy in defect detection.
Solution Approach 2:
The patent uses digital twin models as virtual copies of physical objects to enable automated comparison and defect identification. By having pre-existing digital representations, the system can rapidly compare actual objects against their ideal counterparts without manual measurement or inspection.
3Ease of repair
If standard replacement parts are shipped to consumers, then product functionality is restored, but manufacturing and shipping costs increase
Solution Approach 1:
The system empowers consumers to become self-sufficient in repairing their own products by providing them with 3D printing instructions and access to a 3D printer. Instead of relying on manufacturers to ship replacement parts, consumers can locally manufacture the corrective parts themselves, eliminating shipping needs and reducing material waste.
Solution Approach 2:
The patent extracts only the specific corrective information needed for repair from the manufacturing process. Instead of shipping entire replacement products or large inventories of parts, the system extracts and transmits minimal digital instructions that enable local production of exactly what is needed.
4Measurement precision
If automated image analysis is implemented, then defect detection accuracy improves, but processing complexity increases
Solution Approach 1:
The patent uses digital twin models as reference copies to enable automated comparison. By having complete digital representations of conforming objects, the system can automatically detect deviations without complex analysis algorithms, as the comparison is made against a known-good reference model.
Data Source
AI summary
Provided is a method, system, and computer program product for analyzing image data of a non-conforming object in comparison with a digital twin of the same object and generating 3D printable instructions for mitigating the non-conformance. A processor may receive one or more images of a physical copy of a three-dimensional (3D) object. The processor may determine, based on an analysis of the one or more images, one or more differences between the physical copy of the 3D object and a digital twin of the 3D object. The processor may determine that the one or more differences exceed a conformance threshold. The processor may generate, in response to exceeding the conformance threshold, 3D printing instructions for altering the physical copy of the 3D object to reduce the one or more differences.