What is Advanced Process Control Software?

Advanced process control software utilizes advanced control methods, process models, and optimization techniques to enhance process performance beyond traditional process control capabilities. APC software can help process manufacturers drive higher efficiencies, produce higher quality products, reduce energy usage and emissions, and increase overall equipment effectiveness (OEE).



Model Predictive Control

One of the most common advanced control techniques employed by Advanced Process Control Software is model predictive control (MPC). MPC uses an internal process model to predict how the system will respond to changes in inputs such as setpoints. The controller then optimizes plant operation over a future time horizon by selecting a sequence of manipulated variable adjustments. This allows MPC to actively optimize plant performance while respecting operating constraints. A calibrated process model is required, but MPC can then handle multivariable control scenarios that are difficult with traditional PID control. MPC techniques can improve yields, throughput, and product quality while reducing variability.



Constraint Management

Process constraints such as maximum/minimum limits for temperatures, flows, pressures and compositions must be respected to ensure safe and stable operation. Traditional controllers can have issues accommodating constraints, which can lead to constraint violations and upsets. APC software uses the process model and optimization techniques within MPC to explicitly manage constraints. This allows plants to operate closer to constraints for improved efficiency without incurring violations. Tight, automatic constraint management enables improved control and optimization with fewer manual adjustments required from operators.



Optimization

While MPC focuses on setpoint tracking and constraint handling, the optimization component of advanced process control software is designed to maximize or minimize an objective such as production rate or energy usage. Linear programming (LP) and mixed-integer linear programming (MILP) are commonly used to continuously search for the optimal steady-state operating point. Periodic dynamic optimization over a future horizon can also be applied. Optimization leverages the process model, current measurements and constraints to determine how to best adjust control variables for improved performance. Areas that can be optimized include yields, throughput, energy usage, emissions and raw material usage.



Batch Process Control

Batch and semi-batch processes in industries like specialty chemicals, food and beverages, and pharmaceuticals pose unique challenges for process control due to time-varying recipes, sequences of unit operations and quality objectives. APC software specifically designed for batch processes fills a need beyond conventional PID control. Features like nonlinear model predictive control (NMPC), experimental frame-based control using prior runs as models, and quality checks allow closer regulation to targets during dynamic recipe steps. Overall batch quality, yields and operational efficiency can be enhanced.



Return on Investment

While advanced process control software solutions require an upfront investment, they have the potential for considerable return on investment through improved operational performance. Common benefits that enhance ROI include:



- Increased production rates and throughput - Optimized operation lets plants produce at maximum capacity. MPC tracking closer to constraints enables higher yields.



- Reduced raw material and energy usage - Optimization actively finds the most efficient operating points and trajectories for lower consumption per unit of production.



- Improved product quality and consistency - Tighter, automated control and optimization keeps processes closer to targets throughout. This increases on-spec production and reduces rework.



- Elimination of costly upsets and deviations - Constraint management avoids violations that cause long upsets or waste. Fewer unplanned excursions improve reliability.



- Extended equipment lifetimes - Smooth, optimized operation reduces thermal and mechanical stresses on equipment.



- Reduced manual oversight needs - Automated advanced control handles scenarios beyond PID and decreases manual tuning requirements.



The quantitative financial benefits are plant-specific, but payback periods of 1-3 years are commonly cited. High ROI makes APC a worthwhile investment for competitiveness and profitable growth over the long-term for process manufacturers.



Implementation and Integration

rollout of advanced process control software does require careful planning and execution. Process models must be built and validated using plant automation system data. Advanced controllers are then implemented through configuration and deployment. The systems integration aspect is particularly important, as APC leverages real-time measurements, setpoints other automation system elements for closed-loop control and optimization. Standards like OPC make integration straightforward, but use of consultants experienced in your specific plant scenarios is recommended. A phased approach starting with simple, high-impact use cases can help de-risk initial deployments. Overall, well-executed APC projects deliver step-changes in performance while paying for themselves quickly.



Advanced process control software provides manufacturing plants a powerful set of optimization, constraint handling and control techniques to drive new levels of efficiency and profitability beyond traditional process control capabilities. Model predictive control, optimization, batch control features and tight integration unlock significant financial benefits through improved yields, quality, throughput and reduced costs. When implemented properly with a rigorous focus on process models, automation systems integration and clear objectives, APC delivers rapid ROI through step-improvements in key operational KPIs.

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