Modular Manufacturing Cells With Auto-Calibration and Digital Twins
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Solution Overview
Problem
Current automation systems in manufacturing are often expensive and time-consuming to design, deploy, and configure, leading to inefficient reuse and high costs due to custom-tailored approaches, and they lack integration with workflow solutions, resulting in inaccurate simulation models and manual calibration needs.
Innovation Solution
A software-defined manufacturing system that utilizes modular robotic cells, computer vision, auto-calibration, and recipe-based programming to automate the design, engineering, deployment, and operation of manufacturing systems, enabling quick reconfiguration and standardization, and integrating simulation with real-world data for improved accuracy and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If custom-tailored automation solutions are designed for specific manufacturing projects, then the automation can be effectively implemented for that specific project, but the engineering time and costs increase and reuse of automation equipment is inefficient
Solution Approach 1:
The patent segments automation solutions into modular, reusable components that can be independently designed, tested, and deployed. This allows specific automation tasks to be broken down into discrete units that can be reused across different projects, reducing engineering time while maintaining effectiveness.
Solution Approach 2:
The patent creates virtual copies of automation systems through digital twins and simulation models. These virtual representations allow engineers to test and validate automation solutions before physical deployment, reducing the time and cost of custom-tailored engineering while ensuring reliability through virtual prototyping.
2Productivity
If simulation models are used to represent physical equipment, then development speed improves, but accuracy decreases due to geometric variations in physical equipment
Solution Approach 1:
The patent performs preliminary actions by creating and validating simulation models before physical deployment. Through pre-calibration and virtual testing, the system addresses geometric variations in advance, allowing faster development while maintaining accuracy through upfront virtual prototyping and validation.
Solution Approach 2:
The patent implements feedback loops between simulation models and physical equipment through sensor data integration. Real-world measurements feed back into the digital twin models, continuously refining their accuracy while maintaining fast development cycles through iterative validation rather than extensive manual calibration.
3Measurement precision
If manual calibration is performed to correct simulation-to-reality variations, then measurement accuracy improves, but time and expertise requirements increase
Solution Approach 1:
The patent enables systems to perform self-calibration through automated comparison of simulation models with sensor data from physical equipment. The digital twin technology allows systems to automatically adjust and correct variations without requiring manual calibration by experts, reducing both time and complexity while maintaining high accuracy.
4Manufacturing precision
If automation equipment is deployed with custom configuration data for each device, then the system can be precisely tailored to specific tasks, but deployment time and expertise requirements increase
Solution Approach 1:
The patent creates universal configuration frameworks and standardized interfaces that allow the same automation equipment to be deployed across multiple tasks with minimal reconfiguration. Through modular design and reusable configuration templates, the system maintains task precision while dramatically reducing deployment time and expertise requirements.
Data Source
AI summary
The present system is a software defined manufacturing (SDM) system that integrates several technologies and methods into a system that automates the process of engineering and operating automated manufacturing systems (aka “automating automation”). In one embodiment, some or all of the below aspects of the “automating automation” system are integrated: modular, configurable, reusable manufacturing cells; computer vision systems; autocalibration systems; a recipe-based programming environment; configuration management system; production analytics; and a marketplace for sharing recipes.