Process industries rely heavily on advanced process control software to achieve efficiency and realize optimal performance across their operations. These software solutions leverage real-time data analytics, predictive algorithms, and operator experience to help process plants run at their full potential.
Why is Advanced Control Necessary?
Traditional control schemes utilize proportional-integral-derivative controllers that maintain process variables within predefined limits. However, system dynamics are becoming increasingly complex with tight constraints on quality, output and costs. Advanced control is needed to address these challenges and take advantage of untapped opportunities.
Model Predictive Control
Model predictive control or MPC is one of the most widely used advanced control techniques. It uses an internal process model to predict how the plant will respond to different control actions over a future time horizon. An optimization algorithm then selects the optimal control moves to achieve the desired targets while satisfying operating constraints.
MPC enables multivariable control where the interactions between process variables are considered. This helps maximize throughput without compromising product quality or running into constraints. Regular model updates also make MPC robust to process drifts and disturbances. Areas like refining, chemicals and power generation see significant benefits with MPC.
Advanced Regulatory Control
Regulatory control forms the bottom layer of advanced control structures. Solutions like Fuzzy Logic and Adaptive Model Algorithmic Regulators help achieve setpoints more precisely despite process non-linearities or variability. They automatically self-tune regulator parameters without relying on manual tuning.
Fuzzy logic control applies concepts from fuzzy set theory to map process inputs to control outputs. Membership functions and if-then rules represent the vaguely defined relationships between process variables. Adaptive model regulators continuously update an internal model of the plant to compensate for changes and optimize control performance over time.
Optimization and Data Analytics
Advanced Process Control Software packages also include optimization modules. Discrete optimizers recommend optimal set points to maximize production rate, yield or equipment utilization given available resources and operating constraints. Continous optimizers dynamically optimize the plant in real-time.
Powerful historian databases in these platforms store tag data from controllers and other plant systems. Analytics tools generate insights by mining this time-series data. Applications include detecting abnormal situations, identifying optimization opportunities, and predicting maintenance requirements through trend analysis.
Operator Interaction
Despite advanced capabilities, human expertise and judgment remains invaluable. Advanced control interfaces provide operators visualization of optimal targets, deviations, constraints and predicted impacts of actions. Operators can then choose to implement automatic recommendations or fine-tune them based on experience.
Alerts also help operators focus on critical deviations and take corrective actions quickly. Mobile access further enhances responsiveness. With the right role-based displays and alarms, operators are empowered to realize full benefits while also preventing potential issues.
Implementation Considerations
Successful advanced control implementation requires careful planning, modeling work and commissioning support. Skills like system engineering, modeling, optimization and data analysis are important. A step-wise rollout strategy starting with regulatory control upgrade and then rolling out MPC or optimization solutions module-by-module is recommended.
Standard engineering procedures ensure high quality models, robust controllers and proper configuration. Testing covers different scenarios to eliminate surprises. Operators also need training to understand new interfaces and responsibilities. Ongoing support then helps refine configurations based on plant experiences. With a well-executed plan, advanced control delivers significant and sustained gains across multiples areas of a plant’s operation.
Today’s complex production facilities require elevated levels of process optimization, variability management and constraints handling to stay competitive and maximize value. Advanced process control technologies address these needs by taking a system-level, analytical view of operation. When implemented through a strategic roadmap, they enable dramatic improvements in throughput, product quality, flexibility, energy use and asset utilization. Leveraging both advanced capabilities and human strengths, these solutions will continue powering operational excellence across process industries.
*Note:
1. Source: Coherent Market Insights, Public sources, Desk research
2. We have leveraged AI tools to mine information and compile it