Digital Manufacturing System with Product Tracking and Social Media Analysis
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Solution Overview
Problem
Manufacturing companies face challenges in adopting digital technologies, leading to difficulties in mass production, lack of end-to-end visibility, and minimal quality control assurance for customers, with manual processes and limited automation.
Innovation Solution
Integration of digital manufacturing systems with ERP, MES, IIoT, AR, and machine learning to provide agile manufacturing, improved governance, and human-machine collaboration, enabling real-time visibility and quality control through cloud-based platforms and AI-driven decision-making.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If manual background processes are used for planning and component procurement, then the manufacturing process can be executed, but end-to-end visibility for the customer is lost and quality control assurance is minimal
Solution Approach 1:
The patent replaces manual mechanical processes with digital automation systems. Specifically, it implements an automated planning system that uses algorithms to optimize component procurement and production scheduling, replacing the manual background processes described in the contradiction. This digital substitution enables real-time tracking and visibility while maintaining process execution.
Solution Approach 2:
The patent implements comprehensive feedback mechanisms throughout the manufacturing process. It uses sensors and monitoring systems to collect real-time data on production status, component quality, and logistics, then feeds this information back to both the control system and customers. This feedback loop restores end-to-end visibility and enables continuous quality control assurance.
2Reliability
If traditional manufacturing processes are used, then production can proceed, but quality control issues are not identified until after manufacturing is completed
Solution Approach 1:
The patent implements preliminary quality control actions by integrating inspection systems at multiple stages before final product completion. It uses automated visual inspection, dimensional measurement, and material property testing during the manufacturing process itself, rather than waiting until after production. This preliminary detection prevents defective products from proceeding to later stages.
Solution Approach 2:
The patent establishes continuous quality monitoring throughout the entire manufacturing process. Instead of periodic or end-of-line inspection only, it implements continuous sensing and measurement that tracks quality parameters in real-time across all production stages. This continuous action ensures quality issues are detected immediately when they occur.
3Productivity
If digital technologies like intelligent robots, sensor technology, artificial intelligence, and 3D printing are adopted, then manufacturing capability improves, but implementation difficulty increases for traditional manufacturing companies
Solution Approach 1:
The patent segments the digital manufacturing system into modular functional units that can be independently implemented and integrated. It divides the system into distinct modules for robotic automation, sensor networks, AI analytics, and 3D printing, allowing companies to adopt technologies incrementally rather than requiring complete system replacement. This modular segmentation reduces implementation complexity.
Solution Approach 2:
The patent implements universal digital platforms and control systems that can manage multiple types of manufacturing technologies through a common interface. The system is designed to work with various robotic systems, sensor types, and 3D printers using standardized communication protocols, reducing the complexity of integrating diverse digital technologies into traditional manufacturing environments.
Data Source
AI summary
A digital manufacturing system includes a web portal to receive product configuration information. An enterprise resource planning subsystem generates a production order based on the product configuration information, and determines a manufacturing resource plan and production steps for manufacturing the product.A manufacturing execution subsystem generates an identifier for the manufacturing resource plan, and communicate the manufacturing resource plan and the production steps to a production control subsystem controlling machines performing the manufacturing of the product according to the manufacturing resource plan and the production steps. A production control subsystem stores the identifier in a near field communication chip attachable to the product during the manufacturing to provide real-time tracking of the manufacturing throughout the steps. An empirical analysis subsystem connects to different social media applications to determine sentiment of the manufactured product.