Sustainability Action Plan Simulation for Real-Time Enterprise Tracking
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Solution Overview
Problem
Challenges exist in tracking and improving sustainability parameters across enterprise operations, particularly in hydrocarbon enterprises, to achieve net zero carbon emissions and reduce waste while optimizing resource usage.
Innovation Solution
A sustainability platform system that utilizes sensors to measure operational parameters, generates sustainability models, and develops action plans to adjust operations, simulates performance, and continuously updates plans based on real-time data to enhance sustainability efficiencies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional manual tracking methods are used for sustainability parameters, then implementation complexity is low, but measurement precision and tracking efficiency are insufficient
Solution Approach 1:
The patent replaces manual tracking mechanisms with an automated sustainability platform that uses sensors, data processors, and simulation models to automatically measure, track, and analyze sustainability parameters. This substitution of mechanical/manual systems with automated computational systems resolves the contradiction by providing high measurement precision while managing complexity through software-based solutions.
Solution Approach 2:
The sustainability platform performs self-service by automatically collecting data from sensors, processing sustainability metrics, generating action plans, and updating models without requiring manual intervention for each measurement and analysis cycle. This automation maintains high precision while reducing the operational complexity burden on users.
2Loss of information
If comprehensive sustainability tracking across all enterprise operations is implemented, then measurement completeness improves, but device complexity and computational requirements increase
Solution Approach 1:
The patent segments the enterprise operations into distinct operational units (upstream, midstream, downstream) and tracks sustainability parameters for each segment separately. This segmentation allows comprehensive data collection across all operations while managing complexity by organizing data and processing requirements into manageable segments rather than treating the entire enterprise as a single complex system.
Solution Approach 2:
The sustainability platform is designed as a universal system that handles multiple sustainability parameters (carbon emissions, energy consumption, water usage, waste generation) across diverse operational types using a common architecture. This multi-functionality approach ensures complete data coverage while avoiding the complexity of separate specialized systems for each parameter or operation type.
3Adaptability or versatility
If static action plans are used for sustainability improvement, then implementation simplicity is maintained, but adaptability to changing operational conditions deteriorates
Solution Approach 1:
The patent implements feedback mechanisms where the sustainability platform continuously monitors operational parameters and sustainability metrics, compares actual performance against targets, and automatically updates action plans based on the feedback loop. This dynamic feedback-driven approach enables adaptability to changing conditions while managing complexity through automated control algorithms rather than manual plan revisions.
Solution Approach 2:
The action plans transition from static documents to dynamic, living plans that automatically adjust based on real-time data. The system dynamically modifies action plan parameters, targets, and recommendations as operational conditions change, ensuring adaptability while using computational automation to manage the complexity of continuous plan optimization.
4Measurement precision
If detailed simulation and analysis of action plans are performed, then prediction accuracy improves, but computational cost and time consumption increase
Solution Approach 1:
The patent applies partial simulation by focusing computational resources on simulating and analyzing only the most critical action plans and key sustainability parameters rather than performing exhaustive simulations of all possible scenarios. This selective approach maintains sufficient prediction accuracy for decision-making while significantly reducing computational time and resource requirements compared to complete exhaustive analysis.
Data Source
AI summary
An enterprise system may include one or more devices with sensors that measure operational parameters of the devices. The enterprise system may also include a sustainability platform system that obtains a sustainability model representative of a state of operations of the enterprise based on the measured operational parameters and receives sustainability target data that includes one or more threshold limits, one or more ranges, or both for one or more sustainability parameters. The sustainability platform system may also obtain one or more action plans for adjusting respective operations of the devices based on the sustainability model and the sustainability target data, simulate a performance of the action plans over a period of time relative to the sustainability parameters, and determine whether the simulated performance of the action plans is effective.