Hierarchical Feed-Forward Process Model for Complex System Design
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Solution Overview
Problem
Existing methods for constructing complex processes, such as those in aerospace or power plant development, are difficult and expensive due to the lack of analytical validation and visibility into internal dynamics, leading to poor performance, extended development time, and cost overruns.
Innovation Solution
A method and system for constructing scalable feed-forward processes by identifying and ordering process segments into a hierarchical feed-forward network, constraining component creation, and determining inputs and outputs to ensure predictability and manageability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If a complex process model is constructed to produce complex systems, then the process can provide multiple layers of planning and progress visibility, but constructing such a process model is difficult and expensive
Solution Approach 1:
The process model is divided into hierarchical segments representing different levels of abstraction. Each segment captures specific process aspects at its level, allowing detailed visibility where needed while maintaining overall simplicity. The hierarchy enables progressive refinement from high-level overview to detailed operational steps.
Solution Approach 2:
The patent introduces a hierarchical dimension to the process model, organizing segments across multiple levels. This dimensional approach allows the model to provide comprehensive visibility without linear complexity increases, as each hierarchical level manages a specific scope of process details.
2Ease of operation
If existing graphical methods are used to model processes, then the model can be visually represented, but there is no analytical foundation to validate the representation or determine its feasibility
Solution Approach 1:
The patent incorporates analytical validation mechanisms that provide feedback on process model feasibility. The system evaluates whether the visually represented process can actually achieve its objectives, identifying gaps between intended and achievable outcomes. This feedback loop ensures both visual clarity and analytical rigor.
Solution Approach 2:
The patent replaces purely graphical visualization with a hybrid approach combining visual representation and analytical computation. Mathematical models and algorithms supplement the visual elements, providing objective validation criteria and feasibility assessment without eliminating the visual interface.
3Ease of manufacture
If processes are not modeled with proper structure, then modeling is simpler, but dissimilar characteristics are not recognizable resulting in over-simplification
Solution Approach 1:
The patent applies different levels of detail and structural complexity to different segments of the process model based on their specific characteristics. Critical segments receive more detailed modeling and validation, while less critical areas use simplified representations. This local differentiation maintains accuracy where needed without unnecessarily complicating the overall model.
Solution Approach 2:
The system dynamically adjusts modeling parameters such as detail level, segmentation granularity, and validation depth based on the specific process being modeled. This flexibility allows the model to adapt its complexity to match the requirements of each process domain, maintaining simplicity where possible and precision where necessary.
4Productivity
If large-scale complex processes are executed without proper integration, then development can proceed, but unnecessary rework, inappropriate concurrency, and duplicative work occur resulting in extended development time
Solution Approach 1:
The patent performs preliminary analysis and validation of process segments before full execution. The hierarchical structure allows identification of dependencies and potential conflicts early in the modeling phase, enabling proactive resolution of integration issues. This preliminary work prevents rework during implementation by ensuring proper concurrency and eliminating duplicative tasks beforehand.
Data Source
AI summary
Methods and systems for constructing a scalable feed-forward process are provided. The method includes identifying a plurality of segments of the process wherein the segments define a feed-forward network which is used to constrain the creation of more detailed segment components. The method also includes modeling each component by defining component outputs and determining component inputs that are combinable using the model to produce the defined output, ordering the components hierarchically based on the respective component outputs and inputs, determining segment inputs and outputs based on the component outputs and inputs, and ordering the segments hierarchically based on the respective segment outputs and inputs.