Flexible Ordering Process Model for Multi-Task Efficiency
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Solution Overview
Problem
Traditional process modeling tools are inflexible and inefficient in capturing the variability of task execution orders, leading to inefficiencies in multi-tasking activities and rigid constraints, which limits productivity and resource scheduling in processes.
Innovation Solution
The development of flexible ordering techniques that allow for the identification and consolidation of equivalent process representations, enabling tasks to be performed in various orders while maintaining constraints, and merging flexible-order process flows to optimize task execution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional process models use rigid total-order encoding for task execution, then process flow control is simplified and easier to manage, but productivity and efficiency are reduced due to inability to perform multi-tasking in flexible orders
Solution Approach 1:
The patent introduces dynamic ordering capabilities where tasks can be executed in flexible orders rather than rigid sequences. The system allows task execution orders to adapt based on resource availability and process conditions, enabling multi-tasking while maintaining control. This is achieved through the flexible order encoding that permits out-of-order execution while preserving necessary constraints.
Solution Approach 2:
The patent changes the fundamental parameter of task ordering from fixed sequential to flexible variable ordering. By modifying how task orders are encoded and interpreted in the process model, the system enables tasks to be performed in different orders based on current state, thereby improving productivity without sacrificing controllability.
2Reliability
If process models enforce strict task ordering constraints, then process correctness is ensured, but adaptability and flexibility in task execution are reduced
Solution Approach 1:
The patent segments the process model into distinct components: flexible order groupings that allow variable ordering and strict ordering constraints that ensure correctness. By dividing tasks into those that can be flexibly ordered and those that must maintain strict sequences, the system achieves both reliability and adaptability simultaneously.
Solution Approach 2:
The patent applies different ordering qualities to different parts of the process. Some task groupings are designated as flexible where order can vary, while others maintain strict ordering requirements. This local differentiation allows the process model to be adaptive where appropriate and reliable where constraints are necessary.
3Ease of manufacture
If multiple equivalent process representations are maintained separately, then each representation can be optimized independently, but system complexity increases and merging becomes difficult
Solution Approach 1:
The patent provides mechanisms for merging multiple equivalent process representations into a unified flexible order model. By consolidating separate representations while preserving their optimization benefits, the system reduces complexity and enables automated merging of process flows without losing the advantages of independent optimization.
Solution Approach 2:
The patent creates a universal flexible order model that can represent multiple equivalent process representations in a single unified structure. This multi-functional model serves both as an optimization target and as a consolidated representation, eliminating the need to maintain separate models while preserving their individual optimization benefits.
Data Source
AI summary
A plurality of equivalent representations of a process are identified. The process has a plurality of tasks. Each of the representations specifies a different order of the tasks. The plurality of equivalent representations are consolidated into a single representation. The single representation captures, in at least one flexible order grouping, at least two of the tasks that may be performed in more than one order. At least one constraint is specified for the at least one flexible order grouping. Techniques for merging two or more flexible representations are also provided.