Data Structure Product for Additive Manufacturing Quality Verification
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Solution Overview
Problem
Additive manufacturing processes, such as 3D printing, face challenges in ensuring product quality and reliability due to minor deviations in manufacturing processes, which can affect the product's characteristics and lifespan. Current methods for quality control are time-consuming and costly, leading to inefficiencies and unnecessary product rejection.
Innovation Solution
A data structure product is developed that stores sensor data collected during the additive manufacturing process. This data structure is protected against manipulation and contains information on the product's maintenance, including service time. It interacts with manufacturing devices using a key-keyhole principle and can include smart contracts to automatically adapt service times based on specific usage conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If additive manufacturing is used to enable flexible production and quick switching between products, then productivity and adaptability are improved, but manufacturing precision and product reliability deteriorate due to minor process deviations
Solution Approach 1:
The system performs preliminary actions by capturing and storing manufacturing process data (temperature, speed, acceleration, deceleration, toolpath) during the additive manufacturing process in a data structure product. This preliminary data collection enables later verification and adaptation without requiring real-time intervention during production, thus maintaining production flexibility while ensuring precision through post-process verification.
Solution Approach 2:
The patent implements feedback mechanisms by monitoring service time during product operation and comparing it against the stored manufacturing data. The system adapts service time recommendations based on the actual manufacturing conditions recorded, creating a closed-loop feedback system that continuously improves reliability while maintaining the flexibility of additive manufacturing.
2Reliability
If strict quality standards are enforced to ensure product reliability, then product quality is improved, but productivity decreases due to time-consuming tests and increased product rejection
Solution Approach 1:
The system performs quality verification in advance by storing comprehensive manufacturing process data during production. Instead of conducting time-consuming physical tests after manufacturing, the system has already captured all relevant process parameters (temperature, speed, toolpath) that determine product quality, enabling virtual verification and reducing the need for physical testing and product rejection.
Solution Approach 2:
The patent creates a digital copy of the manufacturing process through the data structure product, which contains all essential manufacturing data. This digital twin or copy of the manufacturing process allows for virtual quality verification and service time adaptation without requiring physical testing of the actual product, thereby maintaining reliability while improving productivity.
3Manufacturing precision
If comprehensive quality testing is performed to verify product characteristics, then manufacturing precision is improved, but loss of time and productivity increase
Solution Approach 1:
The system creates a digital copy of the manufacturing process data in the data structure product, which serves as a virtual representation of the physical product's manufacturing history. This digital copy enables comprehensive quality verification through data analysis rather than time-consuming physical testing, maintaining manufacturing precision while significantly reducing testing duration.
Solution Approach 2:
The patent replaces mechanical/physical quality testing systems with data-based verification methods. Instead of performing physical tests on the manufactured product to verify characteristics, the system uses the stored manufacturing process data (temperature, speed, toolpath) to virtually verify product quality, eliminating the time loss associated with physical testing.
4Reliability
If service intervals are set based on predefined standards to ensure reliability, then product reliability is improved, but adaptability to specific usage conditions deteriorates
Solution Approach 1:
The system transforms static, predefined service intervals into dynamic, adaptive service time recommendations. By continuously monitoring actual product usage conditions and comparing them against the stored manufacturing data, the system dynamically adjusts service time recommendations to match the specific operational context, thereby maintaining reliability while improving adaptability to different usage conditions.
Solution Approach 2:
The patent implements a feedback mechanism where service time recommendations are continuously updated based on actual usage data and manufacturing data comparison. The system learns from operational feedback and adapts service intervals to specific usage patterns, replacing rigid predefined standards with flexible, condition-based service planning that maintains reliability while enhancing adaptability.
Data Source
Figure 1
AI summary
The invention refers to a data structure product containing information with regard to the manufacturing of a product. Furthermore, the invention refers to a kit of a product and its data structure product. Furthermore, the present invention refers to a manufacturing device providing at least a part of the data structure product. Furthermore, the invention refers to a method to manufacture a product, wherein a corresponding data structure product is created.