Unified Refinery Planning Model Integrating Scheduling
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Solution Overview
Problem
Current planning tools in the petrochemical industry, such as PIMS, RPMS, and GRTMPS, separate raw material purchase and product sales decisions from production scheduling, leading to suboptimal solutions due to the lack of integration with scheduling considerations, and fail to account for inventory dynamics and transportation costs effectively.
Innovation Solution
A method that uses a computer-based mathematical model to optimize feed material selection, transportation scheduling, and production planning as a unified problem, incorporating asynchronous production schedules and inventory management, allowing for the determination of operational plans that minimize costs and maintain inventory levels within specified ranges.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If production planning and production scheduling are performed as two separate sequential steps, then the planning process is simpler and more manageable, but the optimization model does not reflect scheduling considerations leading to non-optimal overall solution
Solution Approach 1:
The patent merges production planning and production scheduling into a single integrated optimization model. The model simultaneously determines raw material purchase decisions, production schedules, and transportation schedules over a time horizon, eliminating the need for separate sequential steps and ensuring that scheduling considerations are reflected in the optimization from the beginning.
2Ease of operation
If period-average models are used for raw material purchase and production decisions, then the planning is more straightforward, but the model assumes uniform process operation which leads to planning results that cannot be converted into equivalent schedules
Solution Approach 1:
The patent transitions from static period-average models to dynamic time-dependent models. The optimization model incorporates time-dependent variables that capture variations in process operations, raw material deliveries, and product shipments across different time periods, enabling the planning results to be directly converted into feasible schedules that reflect actual operational dynamics.
3Device complexity
If transportation costs and inventory dynamics are not considered in production planning, then the planning model is simpler, but significant transportation costs are not minimized and inventory fluctuations within each period are not managed
Solution Approach 1:
The patent combines production planning with transportation scheduling and inventory management into a unified optimization framework. The model simultaneously optimizes raw material purchases, production schedules, transportation schedules, and inventory levels, ensuring that transportation costs are minimized and inventory dynamics are properly managed within and across time periods.
4Device complexity
If the optimization model does not include scheduling considerations, then the model is easier to formulate and solve, but when scheduling considerations have significant impact on purchase and sales decisions, the solution becomes non-optimal
Solution Approach 1:
The patent formulates a dynamic optimization model that explicitly includes scheduling considerations as time-dependent decision variables. The model determines not only what to produce and purchase but also when to do so, capturing the temporal aspects of production, transportation, and inventory management to achieve truly optimal solutions that reflect the significant impact of scheduling on purchase and sales decisions.
Data Source
AI summary
A modeling tool for determining the operation of a production facility. A variety of different activities can be modeled, including (a) feed material selection, including quantity and timing, (b) product sales, including quantity and timing, (c) process operations, including process conditions and timing, (d) blending operations, including process conditions and timing, and/or (e) inventory management. The modeling tool may represent time using continuous-time, discrete-time, asynchronous time periods, synchronous time periods, and combinations of these various approaches.