Modular Process Network Execution for Adaptive Business Workflows
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Solution Overview
Problem
Existing business systems lack plasticity and stability, making it difficult to adapt to rapidly changing business environments, and RPA processes are often complex and not easily understood or maintained by on-site personnel, leading to potential disruptions in business operations.
Innovation Solution
A process execution system comprising a process network generation unit, a process network state management unit, and a process network execution unit, which generates, manages, and executes process networks with hierarchical relationships and transcription processes, using transcription factor models to adapt to environmental changes and ensure stability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If business systems are developed using traditional business process modeling methods, then system stability is maintained, but plasticity and adaptability to business environment changes deteriorate
Solution Approach 1:
The system segments business processes into modular components that can be independently configured and executed. The process execution system divides complex business operations into discrete process nodes and networks, allowing flexible recombination and adaptation without requiring complete system redesign, thus improving plasticity while managing complexity through structured modularity.
Solution Approach 2:
The system implements dynamic process configuration capabilities where business process models can be modified and reconfigured in response to changing business environments. The execution environment supports runtime adjustments to process networks, enabling the system to adapt its behavior dynamically rather than requiring static pre-defined workflows, thereby enhancing adaptability.
2Adaptability or versatility
If execution environments with unique specifications are introduced to improve plasticity, then adaptability improves, but learning cost and accessibility deteriorate
Solution Approach 1:
The system employs a universal execution environment that can interpret and execute multiple types of process models through standardized interfaces. Rather than requiring separate execution environments for different process types, the system provides a single multi-functional platform that handles diverse business processes through unified process network management, reducing learning costs and improving accessibility.
Solution Approach 2:
The system introduces standardized process network models as intermediaries between business requirements and execution mechanisms. These standardized models act as a common language that bridges the gap between business users and the execution environment, allowing on-site personnel to create and modify processes using familiar concepts while the system handles the technical execution details, thereby reducing learning requirements.
3Productivity
If RPA processes are implemented to automate business operations, then productivity improves, but process complexity and maintainability deteriorate
Solution Approach 1:
The system segments automated RPA processes into discrete, manageable process nodes within a process network. Each node represents a specific automation task or sub-process, making the overall complex automation workflow divisible into smaller, more maintainable units. This segmentation allows on-site personnel to understand, modify, and troubleshoot specific automation components without being overwhelmed by the entire complex process.
Solution Approach 2:
The system implements feedback mechanisms that provide visibility and monitoring of RPA process execution. By tracking the status and outcomes of automated processes, the system enables continuous improvement and easier maintenance. The feedback loops allow stakeholders to monitor automation performance, identify issues, and make informed adjustments to process configurations, thereby reducing the maintainability burden despite high automation efficiency.
Data Source
AI summary
A process execution system contains: generating a process network, including a plurality of process nodes, from a process network model that includes a plurality of process master nodes having process generation information and representing relationships between the process nodes generated by the plurality of process master nodes; making a specific process node executable based on the state of the process nodes included in the process network and predetermined process state transition rules; and executing the process defined by the process definition information of the executable process node by sending an execution request for an action, based on the information related to actions included in the process definition information, to an action execution system that executes predetermined actions upon request.