Advanced Digital Molding: Next-Gen Manufacturing Tech

Publication ID: 24-11857023_0003_PTD
Published: October 27, 2025
Category:Synergistic Combinations

Legal Citation

pr1or.art Inc., “Advanced Digital Molding: Next-Gen Manufacturing Tech,” Published Technical Disclosure No. 24-11857023_0003_PTD, Published October 27, 2025, available at https://archive.pr1or.art/24-11857023_0003_PTD
This technical disclosure describes improvements that would be readily apparent to a Person Having Ordinary Skill In The Art (PHOSITA) when considered in combination with the foundational architecture disclosed in U.S. Patent No. 11,857,023.

Background and Problem Solved

The original digital molding patent ("Digital molding and associated articles and methods") revolutionized the manufacturing process, but it had limitations in terms of customization, material properties, and process control. The new invention addresses these limitations by synergistically combining digital molding with advanced technologies to create a more powerful system.

Novelty and Inventive Step

The new invention's novelty lies in the synergistic combination of digital molding with AI, IoT, blockchain, and new materials, which provides a more powerful system that optimizes article properties, ensures authenticity, and enables real-time monitoring and control. The inventive step is the integration of these distinct technologies to create a novel system that overcomes the limitations of the original digital molding patent.

Alternative Embodiments and Variations

Alternative embodiments of the invention could include integrating the digital molding system with other advanced technologies, such as machine learning, computer vision, or robotics. Variations could include using different types of materials, such as biodegradable or conductive materials, or applying the invention to different industries, such as aerospace or automotive.

Potential Commercial Applications and Market

The invention has significant commercial potential in various industries, including footwear, aerospace, automotive, and healthcare. The market for customized articles with optimized properties is growing rapidly, and the invention's ability to ensure authenticity and enable real-time monitoring and control makes it an attractive solution for manufacturers and consumers alike.

CPC Classifications

SectionClassGroup
A A43 A43B1/14
A A43 A43B3/34
A A43 A43B13/04
A A43 A43B17/003
A A43 A43B17/14
A A43 A43B23/0215
A A43 A43D1/00
A A43 A43D1/02
A A43 A43D999/00
B B29 B29C64/112
B B29 B29C64/209
B B29 B29C64/336
B B29 B29C64/393
B B29 B29D35/00
B B29 B29D35/12
B B33 B33Y10/00
B B33 B33Y30/00
B B33 B33Y50/02
B B33 B33Y70/00
A A43 A43B5/00
A A43 A43D2200/60
B B29 B29K2075/00
B B29 B29K2105/04
B B29 B29K2713/00
B B29 B29L2031/50
B B33 B33Y80/00

Field of Art

Advanced manufacturing, additive manufacturing, and digital fabrication technologies, with specific expertise in 3D printing, molding techniques, and customized article production, particularly in footwear manufacturing

Person of Ordinary Skill (PHOSITA) Profile

A skilled practitioner with advanced engineering degree, expertise in 3D printing technologies, material science, and digital fabrication techniques, familiar with integrating software control systems with manufacturing processes

Obviousness Rationale

A PHOSITA would recognize that integrating AI, IoT, and blockchain technologies with the existing digital molding process represents a predictable extension of the source patent's core teachings about dynamic liquid dispensing and customized manufacturing. The fundamental principles of variable composition molding and robotic control established in US 11857023 naturally suggest opportunities for technological enhancement through intelligent monitoring and adaptive processing systems.

Obvious Combinations & Variations

Source Patent Element
Robotic gantry with printing nozzle for dispensing variable composition liquids
PTD Variation
AI module dynamically adjusting printing parameters based on real-time process analysis
Obviousness Reasoning
Predictable application of machine learning to existing robotic manufacturing systems, representing a known technique for process optimization
Source Patent Element
Method of curing liquid materials in customized molds
PTD Variation
Blockchain-based authentication module verifying printed article characteristics
Obviousness Reasoning
Logical extension of digital manufacturing techniques to include provenance tracking and verification, representing a finite solution to product authentication challenges
Source Patent Element
Depositing pigment-containing components into molds
PTD Variation
Material synthesis module creating customized materials with tailored properties
Obviousness Reasoning
Obvious progression from basic material variation to advanced material engineering, utilizing known techniques in materials science
Source Patent Element
Transferring partially cured material to substrate
PTD Variation
IoT-enabled sensor module monitoring and controlling molding process in real-time
Obviousness Reasoning
Straightforward implementation of sensor technologies to enhance existing manufacturing control systems, representing a predictable technological improvement
Source Patent Element
Digital molding method for creating articles
PTD Variation
Machine learning module predicting and optimizing molding processes using historical and real-time data
Obviousness Reasoning
Natural application of data analytics to manufacturing processes, representing an obvious solution for process improvement
35 U.S.C. § 103 Summary: Based on the teachings of US 11857023 and the disclosed technological variations, a person of ordinary skill in the art would find the proposed innovations obvious and lacking inventive step. The integration of AI, IoT, blockchain, and advanced material technologies represents a predictable evolution of existing digital molding techniques, thereby rendering potential patent claims obvious and anticipated by the prior art.

Original Patent Information

Patent NumberUS 11,857,023
TitleDigital molding and associated articles and methods
Assignee(s)Kornit Digital Technologies Ltd.