Process Plant Controller Using Transition Data for Grade Changes
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Solution Overview
Problem
Conventional control systems are inadequate for managing transitions in manufacturing processes, such as those in the cement, paper, and metallurgical industries, where shifts in operating points require effective control to produce different product grades efficiently.
Innovation Solution
A method and system that utilize process data from field devices to determine key performance indicators during transitions, calculate correction factors, and adjust set points based on comparisons with threshold values, employing a historian to store and analyze historical data and a server to determine and apply correction factors for efficient process control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional control systems are used to manage transitions in manufacturing processes, then the control of steady-state processes is effective and efficient, but the control performance during transitions is inadequate
Solution Approach 1:
The control system dynamically adapts its behavior based on the current process state. It identifies whether the process is in steady-state or transition mode and applies appropriate control strategies for each condition, making the system flexible and adaptive to changing operational requirements
Solution Approach 2:
The system changes control parameters based on the process state. During transitions, it uses transition-specific control parameters and setpoints rather than steady-state parameters, allowing optimal control performance across different operational phases
2Adaptability or versatility
If the process transitions between different steady states to produce various product grades, then product versatility is improved, but the control complexity increases
Solution Approach 1:
The control approach segments the operational space into distinct steady-states and transitions. Each steady-state has its own control parameters and setpoints, allowing the system to manage complexity by treating each operating condition independently rather than as a continuous complex problem
Solution Approach 2:
The system uses historical data from previous transitions to create models that predict and guide future transitions. By copying and learning from past transition patterns, the system manages complexity through data-driven insights rather than requiring complex real-time control algorithms
3Productivity
If conventional control systems attempt to control processes with multiple transitions, then comprehensive process control is achieved, but the control effectiveness during transitions deteriorates
Solution Approach 1:
The system continuously monitors process variables and compares them against expected transition patterns. This feedback mechanism allows the system to detect when a transition is occurring and adjust control actions accordingly, maintaining precision throughout the transition process
Solution Approach 2:
The system prepares for transitions by pre-calculating appropriate setpoints and control parameters based on the desired target steady-state. This preliminary preparation ensures that when a transition begins, the control system can execute it accurately without reacting to deviations in real-time
Data Source
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AI summary
The present invention discloses a method for controlling a process in a process plant using a controller. The method comprises receiving process data in relation to a first process variable associated with the process, determining a first value of at least one key performance indicator associated with the transition from the process data of the first process variable between the first steady state and the second steady state, comparing the determined first value of the at least one key performance indicator against a threshold value of the at least one key performance indicator; and determining a correction factor for modifying a set point of the process variable based on the comparison, for controlling the process.