Process Model Optimization via Simulation Quality Gates
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Solution Overview
Problem
The complexity of projects in plant engineering and solutions business leads to inefficiencies due to subjective and manual updates of abstract models, resulting in inconsistencies and inability to objectively evaluate implementation processes, which hampers adherence to deadlines and cost optimization.
Innovation Solution
A method and system for optimizing process models through computer-aided simulation, where specifications and release criteria are defined for each work stage, allowing for the creation of a reference run, introduction of interference variables, simulation of project implementation, determination of deviations, and analysis of release criteria's influence on budget and schedule compliance, enabling objective evaluation and adaptation of quality gates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If process models are updated manually based on subjective experience, then the models can be continuously maintained and updated, but inconsistencies easily creep in and objectivity is lost
Solution Approach 1:
The patent replaces manual subjective updates with computer-aided simulation systems that objectively evaluate process models. The simulation system automatically analyzes process models against specifications and release criteria, eliminating human subjectivity and inconsistency while maintaining the ability to continuously update models through automated feedback loops.
Solution Approach 2:
The patent implements automated feedback mechanisms where simulation results provide objective data on process model performance. The system continuously monitors deviations from specifications and uses this feedback to objectively update and optimize process models, replacing subjective manual updates with data-driven automated adjustments.
2Ease of operation
If abstract models of implementation process are used, then work stages can be structured with quality gates, but the complexity of projects with many data points and dependencies cannot be adequately managed
Solution Approach 1:
The patent introduces a computer-aided simulation system as an intermediary between the abstract process models and the complex project reality. This simulation intermediary automatically handles the complexity of many data points and dependencies by computationally evaluating all interactions, while maintaining the structured work stage framework through automated quality gate assessment.
Solution Approach 2:
The patent transforms the management approach by changing from manual tracking of complex parameters to automated computational analysis. The simulation system dynamically evaluates numerous parameters including budget, schedule, and quality criteria simultaneously, managing project complexity through computational parameter analysis rather than manual structuring.
3Reliability
If release criteria are made stringent to ensure quality, then project success is improved, but non-conformance costs and delays increase
Solution Approach 1:
The patent applies preliminary action by using simulation to predict the impact of release criteria before actual project execution. The system evaluates how different quality gate stringency levels affect project outcomes in advance, allowing optimization of release criteria to achieve the right balance between quality assurance and timely completion, preventing both excessive delays and insufficient quality control.
Solution Approach 2:
The patent optimizes release criteria parameters through simulation-based analysis. The system dynamically adjusts the stringency of quality gates based on simulated project outcomes, transforming fixed stringent criteria into optimized parameters that achieve project success while minimizing delays and non-conformance costs.
4Manufacturing precision
If more quality gates are implemented to control project stages, then compliance with specifications is improved, but over-engineering occurs and efficiency decreases
Solution Approach 1:
The patent uses simulation-based feedback to objectively determine the optimal number and placement of quality gates. The system analyzes which release criteria have the most significant impact on project success and removes or relaxes unnecessary gates, providing feedback-driven optimization that maintains specification compliance while eliminating over-engineering and improving efficiency.
Solution Approach 2:
The patent extracts and removes unnecessary quality gates through simulation analysis. The system identifies which release criteria are truly critical to project success and eliminates redundant controls, taking out excessive quality gates that cause over-engineering while retaining essential specification compliance checks.
Data Source
AI summary
Within methods and systems for computer-aided optimization of process models, defined specifications and associated release criteria (quality gates) are available for every work stage. The specifications include service documents, result features that are to be generated in a work stage, and budget details and the latest end time for a work stage. The release criteria (quality gates) can identify the results of a work stage as successful and can assess the fulfillment of a work stage. A reference for all work stages simulates the model based on a fictitious sample project, interference variables are introduced, the project implementation is simulated for each interference variable, respectively, the deviations from the reference run are automatically determined, respectively, for each interference variable, and an analysis of the influence of the release criteria (quality gates) regarding compliance with the budget and the schedule is performed based on the determined deviations from the reference run.