Production Planning Model Tracking Across Refinery Control Layers
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Solution Overview
Problem
In large-scale petroleum refineries, existing systems operate independently for enterprise resource planning, manufacturing execution, and process control, making it difficult to track and optimize production plans effectively across different departments and sites, leading to inefficiencies and unclear benefits from updating planning models.
Innovation Solution
A system that integrates enterprise resource planning, manufacturing execution, and process control layers, using a linear programming model to generate and update production plans, tracks improvements by comparing updated and unupdated plans, and calibrates simulation models to reflect actual operations, ensuring accurate and efficient data processing across departments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If independent systems are used for enterprise resource planning, manufacturing execution, and process control, then each system can operate autonomously, but it becomes difficult to track and optimize production plans effectively across different departments and sites
Solution Approach 1:
The patent integrates enterprise resource planning, manufacturing execution, and process control into a unified system that uses a common planning model. This merging allows the system to maintain autonomous operational capabilities while enabling comprehensive tracking and optimization of production plans across all departments and sites through centralized model management and performance tracking.
2Productivity
If planning models are updated frequently to improve production plans, then production efficiency can be enhanced, but it becomes difficult to objectively measure the impact of updates
Solution Approach 1:
The patent establishes a baseline performance metric before updating the planning model. This preliminary action creates a reference point that enables precise measurement of the impact subsequent model updates have on production efficiency, allowing organizations to objectively quantify improvements.
Solution Approach 2:
The patent implements a feedback mechanism that tracks performance metrics before and after planning model updates. This feedback loop provides objective measurement of update impacts by comparing actual performance changes against the established baseline, enabling data-driven decisions about model improvements.
3Productivity
If comprehensive integration of multiple systems is implemented, then production optimization can be achieved, but system complexity increases
Solution Approach 1:
The patent employs a universal planning model that serves multiple functions across enterprise resource planning, manufacturing execution, and process control. This multi-functional approach enables comprehensive production optimization without requiring separate complex systems for each function, thereby reducing overall system complexity while maintaining integration benefits.
Data Source
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AI summary
When operating a production site, it is preferable to be aware of the degree to which a production plan is improved as a result of performance improvements being reflected in a model which is used to generate the production plan. Provided is a system including a planning section that generates a production plan for controlling a production site during a target interval, using a planning model that has been updated to a newest state; a base planning section that generates a base plan to serve as a base of the production plan, using an unupdated planning model; and a tracking section that tracks improvement in the production plan caused by the update of the planning model, based on the production plan and the base plan.