Key Performance Indicators for Monitoring and Evaluation of PID and APC Strategies at Manufacturing Operations Management Level in a Natural Gas Processing Unit
(2015) 12th International Symposium on Process Systems Engineering and 25th European Symposium on Computer Aided Process Engineering- Abstract
- Monitoring and control of proper Key Performance Indicators of plant performance have high correlation with business performance. So it is very important at plant-wide level to ensure that process control developments are being developed aligned with business strategy as Advanced Process Control projects have as ultimate goal to help achieving gains in this direction. The ISO 22400 “Key Performance Indicators (KPIs) for Manufacturing Operations Management” is an international standard currently under development. This new standard defines KPI as quantifiable level of achieving a critical objective derived from measurements, data and/or other key performance indicators. The common performance parameters used for assessment of PID and... (More)
- Monitoring and control of proper Key Performance Indicators of plant performance have high correlation with business performance. So it is very important at plant-wide level to ensure that process control developments are being developed aligned with business strategy as Advanced Process Control projects have as ultimate goal to help achieving gains in this direction. The ISO 22400 “Key Performance Indicators (KPIs) for Manufacturing Operations Management” is an international standard currently under development. This new standard defines KPI as quantifiable level of achieving a critical objective derived from measurements, data and/or other key performance indicators. The common performance parameters used for assessment of PID and multivariable controllers has been discussed in literature but they don’t translate the loop performance into manufacturing operations level concepts.
The Tower of stabilization is responsible for removing light components of crude oil that reaches the tabs and desalt tanks at the entrance of the plant. The operation of the tower is to ensure that the pressure of the residual steam stabilized oil output at low levels, thus decreasing its flammability and avoiding the formation of gas during storage. Due to the large number of production wells and its various operating conditions, the inlet of the plant presents high variability in terms of flow rate, composition, temperature and pressure throughout the day. In this scenario, the traditional PID control strategy does not show satisfactory performance in temperature control of the stabilization tower. This is because the PID control can not adequately handle the different feeding conditions, the high dead time inherent in the process and the adverse conditions as the arrival of PIGs. The instability of this tower leads to problems for downstream processes (as NGPUs), interfering with the profitability of the plant and the storage conditions.
In this work, the advanced control strategy applied in Tower Stabilization Unit is developed and KPI for manual, PID and APC operations are determined. The advanced control employed is based on the type Predictive Process Models. Dynamic models considering supply disruptions in the tower and process response were identified. The implementation aimed to promote a low temperature variability tower, stabilizing the supply of NGPU. The predictive controller action employee can be seen in correct anticipation of control actions to prevent disturbance input promote future impact on the process conditions. It was verified that the predictive control action was effective even in extreme conditions such as PIG. These performance gains are mapped to plants KPI indexes.
This paper is about selecting and using PID and APC Key Performance Indicators to help performance evaluation and comparison at plant-wide level. In this work we explain what Key Performance Indicators are suitable to use and their illustration of the impact of the new control strategies in the plant through an example of how they have been implemented in an industrial application Oil and Gas Processing Unit is presented. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/7760581
- author
- Farias, Felix ; Johnsson, Charlotta LU ; Ramminger, Guilherme and Lima, Luiz
- organization
- publishing date
- 2015
- type
- Contribution to conference
- publication status
- published
- subject
- keywords
- key performance indicators, process control, apc, pid
- pages
- 2 pages
- conference name
- 12th International Symposium on Process Systems Engineering and 25th European Symposium on Computer Aided Process Engineering
- conference location
- Copenhagen, Denmark
- conference dates
- 2015-05-31 - 2015-06-04
- language
- English
- LU publication?
- yes
- id
- d53bfaa1-fe45-4eda-8371-235b670d5b15 (old id 7760581)
- date added to LUP
- 2016-04-04 14:25:01
- date last changed
- 2018-11-21 21:20:11
@misc{d53bfaa1-fe45-4eda-8371-235b670d5b15,
abstract = {{Monitoring and control of proper Key Performance Indicators of plant performance have high correlation with business performance. So it is very important at plant-wide level to ensure that process control developments are being developed aligned with business strategy as Advanced Process Control projects have as ultimate goal to help achieving gains in this direction. The ISO 22400 “Key Performance Indicators (KPIs) for Manufacturing Operations Management” is an international standard currently under development. This new standard defines KPI as quantifiable level of achieving a critical objective derived from measurements, data and/or other key performance indicators. The common performance parameters used for assessment of PID and multivariable controllers has been discussed in literature but they don’t translate the loop performance into manufacturing operations level concepts.<br/><br>
The Tower of stabilization is responsible for removing light components of crude oil that reaches the tabs and desalt tanks at the entrance of the plant. The operation of the tower is to ensure that the pressure of the residual steam stabilized oil output at low levels, thus decreasing its flammability and avoiding the formation of gas during storage. Due to the large number of production wells and its various operating conditions, the inlet of the plant presents high variability in terms of flow rate, composition, temperature and pressure throughout the day. In this scenario, the traditional PID control strategy does not show satisfactory performance in temperature control of the stabilization tower. This is because the PID control can not adequately handle the different feeding conditions, the high dead time inherent in the process and the adverse conditions as the arrival of PIGs. The instability of this tower leads to problems for downstream processes (as NGPUs), interfering with the profitability of the plant and the storage conditions. <br/><br>
In this work, the advanced control strategy applied in Tower Stabilization Unit is developed and KPI for manual, PID and APC operations are determined. The advanced control employed is based on the type Predictive Process Models. Dynamic models considering supply disruptions in the tower and process response were identified. The implementation aimed to promote a low temperature variability tower, stabilizing the supply of NGPU. The predictive controller action employee can be seen in correct anticipation of control actions to prevent disturbance input promote future impact on the process conditions. It was verified that the predictive control action was effective even in extreme conditions such as PIG. These performance gains are mapped to plants KPI indexes.<br/><br>
This paper is about selecting and using PID and APC Key Performance Indicators to help performance evaluation and comparison at plant-wide level. In this work we explain what Key Performance Indicators are suitable to use and their illustration of the impact of the new control strategies in the plant through an example of how they have been implemented in an industrial application Oil and Gas Processing Unit is presented.}},
author = {{Farias, Felix and Johnsson, Charlotta and Ramminger, Guilherme and Lima, Luiz}},
keywords = {{key performance indicators; process control; apc; pid}},
language = {{eng}},
title = {{Key Performance Indicators for Monitoring and Evaluation of PID and APC Strategies at Manufacturing Operations Management Level in a Natural Gas Processing Unit}},
year = {{2015}},
}