Requirement Management System Using Fuzzy Logic for Uncertainty
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Solution Overview
Problem
Current requirement, compliance, and resource management systems lack the ability to effectively handle inherent approximation, variability, and uncertainty in process steps, and they do not provide real-time collaboration and optimization across all relevant processes.
Innovation Solution
The methodology incorporates mathematical algorithms such as fuzzy logic, statistics, and weighting logic to manage approximation and uncertainty, and enables near real-time and real-time collaboration through a scalable system with modular components, including a question/answer format, fuzzy logic algorithm module, statistical algorithm module, and weighting logic algorithm module, integrated with enterprise and cloud storage systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional requirement management systems are used, then basic requirement tracking is achieved, but they cannot handle inherent approximation, variability, and uncertainty in process steps
Solution Approach 1:
The patent applies parameter changes by transforming rigid binary requirement states into continuous fuzzy logic states. Requirements are represented with membership values between 0 and 1, allowing gradual transitions and capturing uncertainty. This enables the system to handle approximation and variability while maintaining manageable complexity through mathematical formalization.
Solution Approach 2:
The patent introduces fuzzy logic algorithms as an intermediary layer between traditional requirement management and uncertainty handling. This intermediary enables the system to process approximate and variable information without requiring complete system redesign, bridging the gap between simple tracking and sophisticated uncertainty management.
2Productivity
If comprehensive process optimization is implemented, then productivity improves, but real-time collaboration and optimization across all processes becomes difficult
Solution Approach 1:
The patent implements a unified requirement management system that serves multiple functions simultaneously: requirement tracking, compliance verification, resource management, and real-time collaboration. This universal platform enables process optimization across all these areas without requiring separate systems, improving productivity while maintaining ease of operation through a single integrated interface.
Solution Approach 2:
The system incorporates real-time feedback mechanisms that continuously monitor requirement status, compliance levels, and resource allocation. This feedback enables dynamic optimization of processes and facilitates real-time collaboration by providing all stakeholders with current system state information, allowing them to make informed decisions without complex coordination.
3Manufacturing precision
If detailed verification of all process steps is performed, then manufacturing precision improves, but loss of time increases due to excessive verification
Solution Approach 1:
The patent applies partial action by implementing risk-based verification strategies. Not all requirements require the same level of verification detail - critical requirements receive thorough verification while less critical ones receive streamlined checking. The fuzzy logic system prioritizes verification efforts based on requirement importance and risk levels, achieving adequate precision without excessive time consumption.
Solution Approach 2:
The system changes the verification parameter from binary (verified/not verified) to continuous (degree of verification confidence). This allows the system to adjust verification depth based on requirement criticality and available time, maintaining acceptable precision while reducing overall verification time through intelligent parameter adjustment.
Data Source
AI summary
A system and/or a method based on a scalable requirement, compliance and resource management methodology for designing a product/service, optimizing relevant processes and enhancing real time and/or near real time collaboration between many users is disclosed. Utilizing, a learning (self-learning) computer, a requirement, compliance and resource management methodology is further integrated with (a) a machine learning/fuzzy/neuro-fuzzy logic algorithm and/or (b) statistical algorithm and/or (c) weighting logic algorithm and/or (d) game theory algorithm and/or (e) a blockchain and enhanced with a graphical user interface/chatbot interface.