Methods and systems for additive manufacturing of nutritional supplement servings
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Solution Overview
Problem
Existing systems for nutritional analysis face complexity and variability challenges due to the vast array of factors affecting nutritional needs, making consistent application of nutritional data difficult.
Innovation Solution
A system and method for additive manufacturing of nutritional supplement servings using a computing device that determines nutritional deficiencies, calculates supplement doses, selects ingredient combinations, and manufactures nutritional supplements based on user-specific nutritional needs and plans, incorporating a machine learning process to personalize supplement delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional nutritional analysis systems are used, then nutritional data can be processed, but the complexity and variability of nutritional factors make consistent application difficult
Solution Approach 1:
The system segments the complex nutritional analysis process into distinct functional modules: nutritional needs assessment, deficiency detection, supplement dose calculation, and personalized formulation. Each module handles a specific aspect of the complex problem independently, making the overall system more manageable and consistent despite the variability in nutritional factors.
Solution Approach 2:
The system dynamically adjusts parameters such as supplement dosage, ingredient combinations, and formulation based on detected nutritional deficiencies and individual user profiles. This parameter adaptation allows the system to maintain consistent and accurate nutritional supplementation despite the complexity and variability of individual nutritional needs.
2Measurement precision
If personalized supplement formulation is implemented, then accuracy of nutritional supplementation improves, but manufacturing complexity increases
Solution Approach 1:
The manufacturing system is designed to be dynamic and adaptable, automatically adjusting formulation parameters based on detected nutritional deficiencies. The system can modify ingredient combinations, dosages, and product characteristics in real-time based on user-specific data, achieving personalized supplementation without requiring complex manual intervention.
Solution Approach 2:
The system performs self-service by automatically calculating supplement doses, selecting ingredient combinations, and configuring manufacturing parameters based on detected nutritional deficiencies. This automation reduces the need for complex manual processes while maintaining high accuracy in personalized nutritional supplementation.
3Adaptability or versatility
If multiple ingredients and formulations are produced, then versatility of nutritional supplements increases, but production efficiency decreases
Solution Approach 1:
The additive manufacturing system is designed with multi-functionality to handle various ingredient types and formulations through a single platform. The system can process different materials (powders, liquids, gels) and produce various product forms (tablets, capsules, gummies) using the same basic manufacturing infrastructure, thereby maintaining high production efficiency while achieving formulation versatility.
Solution Approach 2:
The system achieves versatility by dynamically changing manufacturing parameters such as material properties, deposition rates, and formulation compositions based on the specific supplement requirements. This parameter adaptation allows the same manufacturing process to efficiently produce diverse formulations without requiring separate production lines for each product type.
Data Source
AI summary
A system for additive manufacturing of nutritional supplement servings, the system comprising a computing device configured to receive a plurality of nutritional needs of a user and a nutrient plan; determine a nutritional input to the user as a function of the nutrient plan; detect at least a nutrition deficiency as a function of the plurality of nutritional needs, the nutritional input and the nutrient plan; calculate at least a supplement dose; select an ingredient combination as a function of the at least a supplement dose, and selecting an ingredient combination including at least a substrate ingredient and at least a supplement ingredient as a function of the nutritional deficiency and the at least a delivery vehicle; and initiate manufacture of a nutritional supplement serving at the additive manufacturing device.