Dual-Horizon Plant Optimization for Demand and Inventory Balance
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Solution Overview
Problem
Existing optimization processes for processing plants, such as oil refineries, fail to effectively manage demand fluctuations and other disturbances, leading to inventory imbalances and suboptimal performance.
Innovation Solution
A dual-horizon optimization process that combines long-horizon and short-horizon optimization techniques to balance supply-and-demand dynamics, minimizing the impact of disturbances on target parameters like profitability by generating optimized operational parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a single optimization process is used for processing plants, then the optimization process is simple to implement, but it cannot effectively manage both long-term strategic planning and short-term operational adjustments, leading to suboptimal performance under demand fluctuations
Solution Approach 1:
The optimization process is segmented into two distinct horizons: long-horizon optimization for strategic planning (production rates, inventory levels, maintenance schedules) and short-horizon optimization for tactical adjustments (blender operations, product blending ratios). This segmentation allows each horizon to be optimized with appropriate time scales and decision variables, improving overall adaptability while managing complexity through modular design
2Reliability
If demand fluctuations are not managed effectively, then the optimization process remains simple, but inventory imbalances occur and plant performance deteriorates
Solution Approach 1:
The long-horizon optimization performs preliminary actions by pre-planning production rates, inventory levels, and maintenance schedules in advance. This anticipatory planning prepares the system to handle upcoming demand fluctuations, ensuring inventory balance is maintained while optimizing profitability before disturbances occur
3Adaptability or versatility
If the number of blenders is limited relative to concurrent products, then plant configuration is simpler, but the ability to respond to demand changes and maintain optimal performance is reduced
Solution Approach 1:
The short-horizon optimization introduces dynamic adjustment capabilities by optimizing blender operations in real-time based on current demand conditions. Even with a fixed number of blenders, the system dynamically adjusts product blending ratios, feed rates, and operational parameters to respond to demand changes, effectively increasing adaptability without adding physical equipment
Data Source
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AI summary
Embodiments of the present disclosure provide for generating at least one optimized operational parameter associated with a processing plant, such as an oil refinery. Embodiments of the disclosure utilize a multi-horizon optimization process, for example that generates optimized operational parameter(s) based on at least a long-horizon optimized plan and a short-horizon optimized plan. Some embodiments utilize the multiple horizons to generate the optimized operational parameter(s) via different process(es) based on configuration(s) and/or characteristic(s) of a processing plant. The resulting optimized operational parameter(s) enable operation of the processing plant during the immediate term in a manner that is optimized specifically for the processing plant in its particular configuration.