Software-Defined Manufacturing Cells for Fast Automation Reuse
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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 uses modular robotic cells, computer vision, auto-calibration, and recipe-based programming to automate the design, engineering, and deployment 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 to future products is not supported
Solution Approach 1:
The automation system is divided into modular, reusable components (robotic cells, modules, and standardized interfaces) that can be independently designed, tested, and assembled. This segmentation allows the same modular components to be reused across different manufacturing projects, reducing engineering time while maintaining automation effectiveness through standardized integration protocols.
Solution Approach 2:
The patent implements universal robotic cells with standardized interfaces and configurations that can perform multiple manufacturing tasks across different product lines. These universal modules are designed to be adaptable to various applications through software configuration rather than hardware redesign, enabling reuse across future products while maintaining project-specific customization capabilities.
2Productivity
If simulation models are used to develop automation programs, then the development speed is improved, but the simulation models often differ materially from the real world requiring manual calibration
Solution Approach 1:
The system implements automated feedback loops where actual sensor data from the physical robotic cell is continuously compared with simulation model predictions. Discrepancies are automatically detected and used to iteratively refine and calibrate the simulation model parameters, enabling the simulation to converge toward real-world accuracy without extensive manual calibration while maintaining fast development cycles.
Solution Approach 2:
The patent employs pre-calibrated standardized modules with known characteristics and pre-validated simulation models for common manufacturing tasks. These preliminary preparations reduce the gap between simulation and reality from the outset, allowing faster development while maintaining higher initial accuracy compared to custom-built simulation models.
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.