Industrial Skill Interface for Autonomous Machine Customization
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Solution Overview
Problem
Current industrial automation systems rely heavily on human interaction for customization and machine-to-machine communication, limiting their robustness and efficiency, especially in manufacturing environments where MES processes require manual intervention for customization and production planning.
Innovation Solution
The implementation of a skill interface that standardizes and simplifies machine interactions by defining 'skills' as machine-independent descriptions of workpiece transformations, enabling cyber-physical production systems to autonomously communicate and execute processes, optimize resource allocation, and dynamically select machines for product creation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual customization is performed by operators for machine-to-machine interactions, then the system can handle complex production scenarios, but the productivity and automation extent are reduced
Solution Approach 1:
The system enables machines to autonomously perform customization tasks through self-learning and self-configuration. Operators define high-level production goals, and the system automatically generates and adjusts production plans, allowing the manufacturing system to serve itself without continuous human intervention for customization.
Solution Approach 2:
The system pre-defines standardized machine interfaces and communication protocols before production begins. By establishing these frameworks in advance, the system enables automatic adaptation to different production scenarios without requiring manual customization during operation, thus maintaining both versatility and productivity.
2Extent of automation
If standardized machine interfaces are implemented, then the extent of automation increases, but the adaptability to custom production scenarios decreases
Solution Approach 1:
The system employs dynamic production planning that automatically adapts standardized machine interfaces to custom production scenarios. The planning system continuously adjusts production schedules, resource allocation, and machine coordination based on real-time conditions and specific production requirements, maintaining automation while achieving customization.
Solution Approach 2:
The system modifies operational parameters of standardized machine interfaces through software configuration rather than physical reconfiguration. By changing control parameters, communication protocols, and process variables digitally, the system maintains automated standardized interfaces while adapting to diverse production scenarios.
3Adaptability or versatility
If human operators perform machine-to-machine interactions, then the system handles complex scenarios with flexibility, but the loss of time increases
Solution Approach 1:
The system replaces manual operator actions with automated digital communication and control systems. Machine-to-machine interactions are handled through standardized digital interfaces and automated planning algorithms, eliminating the time-consuming manual processes while maintaining the ability to handle complex production scenarios.
4Adaptability or versatility
If manual customization is required for each production scenario, then the device complexity increases, but the ease of operation decreases
Solution Approach 1:
The system implements universal standardized machine interfaces that can handle multiple production scenarios through software configuration rather than physical reconfiguration. A single standardized interface design serves multiple functions across different production scenarios, reducing operational complexity while maintaining flexibility.
Data Source
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AI summary
A cyber-physical production system includes a plurality of cyber-physical units configured to collectively produce a product comprising one or more workpieces. Each cyber-physical units comprises one or more automation system devices, a network interface and a processor. The network interface is configured to receive one or more skill instances. Each skill instance provides a machine-independent request for transformation of a workpiece by the one or more automation system devices. The processor is configured to execute each of the one or more skill instances by applying behaviors that control the automation system devices.