Distributed State Machine Reallocation for Adaptive Workflow Control
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Solution Overview
Problem
Traditional process automation systems lack flexibility and scalability, struggling to dynamically manage and reconfigure workflows in response to changing operational conditions, external failures, and performance metrics, leading to inefficiencies and manual intervention requirements.
Innovation Solution
The implementation of a Distributed Finite State Automata (DFSA) system that collects performance metrics, analyzes them to determine key performance indicators, and automatically reconfigures computing resources and workflow paths to meet operational conditions, enabling real-time adjustments and error recovery without manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If traditional process automation systems use statically compiled process definition languages, then system stability and predictability are improved, but flexibility and adaptability to changing operational conditions deteriorate
Solution Approach 1:
The patent implements dynamic workflow reconfiguration by allowing process definitions to be modified at runtime without recompilation. The system transitions from static, pre-compiled process definitions to dynamic, adaptable workflows that can respond to changing operational conditions, external failures, and performance metrics in real-time.
Solution Approach 2:
The system changes the fundamental parameter of process definition from static code to dynamic data structures that can be modified during execution. This allows workflow paths, computing resource allocations, and process parameters to be adjusted based on real-time conditions while maintaining system stability through controlled modification mechanisms.
2Device complexity
If traditional process automation systems use fixed computing resource allocation, then resource management simplicity is improved, but scalability and performance optimization deteriorate
Solution Approach 1:
The patent implements dynamic resource allocation by changing computing resources based on real-time performance metrics and operational conditions. The system monitors key performance indicators and automatically adjusts computing resource allocation, workflow paths, and process configurations to optimize productivity while maintaining manageable complexity through automated decision-making.
3Manufacturing precision
If traditional process automation systems require manual intervention for out-of-range conditions, then control precision is improved, but productivity and response time deteriorate
Solution Approach 1:
The patent implements self-service automation where the system automatically detects, analyzes, and responds to out-of-range conditions without requiring manual operator intervention. The automated system monitors process conditions, identifies deviations from specifications, and executes corrective actions or workflow reconfigurations autonomously, maintaining control precision while dramatically improving response time and productivity.
Solution Approach 2:
The system implements continuous feedback loops that monitor process conditions, compare them against specifications, and automatically trigger corrective actions when deviations are detected. This closed-loop control mechanism maintains manufacturing precision while enabling rapid automated response to out-of-range conditions, eliminating the bottleneck of manual intervention.
4Adaptability or versatility
If traditional process automation systems use disparate control and automation technologies, then specialized functionality is improved, but system integration and reconfiguration capability deteriorate
Solution Approach 1:
The patent implements a universal workflow management architecture that can accommodate multiple specialized technologies and control systems through a common framework. The system uses a standardized process definition language and unified control mechanism that can manage diverse processes, external systems, and specialized functionalities while enabling seamless integration and dynamic reconfiguration across the entire system.
Data Source
AI summary
The systems and methods described provide improved process control operating range and capabilities and integrate process control monitoring and management with broader process automation (PA) systems process management, extending the real-time operation and control of a process control system to process handling of a PA system, and extending PA-style process management by adding real-time process controls and monitoring, and adding new functionality by permitting management of these processes to externally defined completion goals. This combination provides new functionality in dynamically determined process flexibility, extended operating range and extended process recipe definition capabilities for process control systems using this technology, and provides improved error recovery and exception handling of traditional PA systems.