Shop Floor Connector for Decentralized Manufacturing Control
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Centralized manufacturing systems face inefficiencies due to complex data processing, inflexibility, and network latency issues, which hinder real-time production control and decision-making in manufacturing processes.
Innovation Solution
Implementing a connector, or generic shop floor connector (GSFC), that retrieves and stores production control data from a centralized system in proximity to the production site, reducing geographical distance and enabling decentralized manufacturing by linking virtual resources to physical resources, thus minimizing network latency and enhancing data retrieval efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If centralized manufacturing control system (MES) is used to manage entire system planning, then manufacturing coordination and control are improved, but network latency and data retrieval delays occur due to geographical distance
Solution Approach 1:
The patent segments the centralized MES functionality by deploying edge computing nodes at or near production sites. These edge nodes locally cache production control data and handle real-time decision-making, while the central MES retains strategic planning functions. This segmentation eliminates geographical latency by processing data locally rather than requiring constant remote communication.
Solution Approach 2:
The patent introduces an edge computing intermediary layer between the centralized MES and production resources. This intermediary caches production control data locally and mediates real-time control operations, reducing the need for frequent communications with the distant central system and thereby minimizing network latency.
2Reliability
If centralized system processes voluminous manufacturing data, then comprehensive production management is achieved, but processing time increases due to system complexity
Solution Approach 1:
The patent divides data processing responsibilities between central MES and edge computing nodes. Edge nodes handle real-time local data processing and filtering, while the central system processes aggregated and pre-processed data. This segmentation reduces the processing burden on the central system and enables faster local responses.
Solution Approach 2:
The patent implements partial processing at the edge by caching frequently accessed production control data and handling routine control decisions locally. This partial action at the edge level prevents the need for the central system to process every individual data point, thereby improving overall processing speed while maintaining comprehensive management.
3Adaptability or versatility
If centralized MES is deployed as cloud-based solution, then system accessibility and scalability are improved, but connectivity issues and network latency adversely affect manufacturing operations
Solution Approach 1:
The patent segments the cloud-based MES architecture by deploying edge computing capabilities at production sites. This creates a hierarchical structure where local edge nodes can operate autonomously with cached data, ensuring operational reliability even when cloud connectivity is interrupted, while maintaining cloud accessibility for strategic functions.
Solution Approach 2:
The patent implements beforehand cushioning by pre-caching production control data and operational parameters at edge nodes before connectivity issues occur. This local cache acts as a buffer that enables continuous manufacturing operations during network outages, protecting against connectivity-related disruptions.
4Reliability
If centralized control system is used, then unified production planning is achieved, but system flexibility and user autonomy are reduced
Solution Approach 1:
The patent segments decision-making authority between central MES and local edge nodes. The central system maintains unified production planning and strategic control, while edge nodes gain autonomy in real-time resource selection and local optimization. This segmentation enables both unified planning and local flexibility simultaneously.
Solution Approach 2:
The patent introduces dynamic autonomy where edge computing nodes can operate with varying degrees of independence based on local conditions and connectivity status. When connected, they follow central planning; when autonomous, they can independently select resources and adjust parameters, providing dynamic flexibility while maintaining overall planning unity.
Data Source
AI summary
In a process of transfer of production control in proximity to production site for enabling decentralized manufacturing, production control data and routing data are retrieved from a centralized system. The retrieved production control data and the routing data are stored within a connector installed at a proximity to a plant floor. An operation associated with the production control data of a purchase order is matched with the resource published in the connector. Upon determining the match between the operation and the resource, the resource is dynamically allocated to perform the operation. The control of manufacturing process of the plant floor is provided to the connector to realize de-centralized manufacturing.