Embedded Workpiece Intelligence for Customized Assembly Routing
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Solution Overview
Problem
Conventional manufacturing systems with centralized intelligence are inadequate for diverse production environments, as they cannot optimize individual products in terms of cost, delivery time, and quality, as they focus on overall production line optimization rather than workpiece-level optimization.
Innovation Solution
An intelligent workpiece system with an embedded computing system that communicates with machines and automated guided vehicles to select the most suitable machines and paths for assembly based on product requirements, enabling individualized optimization and customized production.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If centralized intelligence (MES or PLC) is used to control production lines, then overall production optimization is achieved, but individual workpiece-level optimization cannot be realized
Solution Approach 1:
The patent segments the centralized control intelligence into distributed intelligence embedded in each workpiece. Each workpiece is divided into components including a microcontroller, sensors, and communication modules, enabling independent decision-making at the workpiece level while maintaining system-wide coordination.
Solution Approach 2:
The patent introduces an intermediary communication layer (wireless communication system, RFID tags) that mediates between the workpiece-level embedded intelligence and the centralized MES/PLC system. This intermediary enables bidirectional information flow, allowing workpieces to report status and receive instructions while maintaining autonomy for real-time decisions.
2Loss of information
If RFID tags are added to workpieces for decentralized intelligence, then workpiece identification and tracking are improved, but decision-making capability remains limited
Solution Approach 1:
The patent implements self-service by embedding autonomous decision-making capabilities directly in the workpiece through microcontrollers and embedded software. The workpiece independently monitors its own status, selects appropriate machines, and manages its production journey without requiring constant centralized control, thereby achieving both information tracking and automated decision-making.
Solution Approach 2:
The patent transforms the static RFID tag into a dynamic embedded computing system that can adapt its behavior based on real-time conditions. The workpiece dynamically adjusts its production path, machine selection, and process parameters based on sensor feedback and communication with the manufacturing environment, enabling genuine decision-making capability.
3Productivity
If production automation systems focus on overall line optimization, then mass production efficiency is maximized, but customized production for individual products is not achievable
Solution Approach 1:
The patent applies local quality by enabling each workpiece to have customized production parameters, quality requirements, and process preferences stored in its embedded memory. Each workpiece can specify its unique requirements (e.g., priority delivery, specific material standards, quality thresholds) that are locally enforced during processing, allowing mass production infrastructure to support customized production simultaneously.
Data Source
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AI summary
An intelligent workpiece system includes a workpiece comprising a portion of a product; and an embedded computing system attached to the workpiece. The embedded computing system is configured to communicate with machines in a manufacturing environment to facilitate assembly of the workpiece into the product at a plurality of assembling areas.