The Autonomous Process Plant: Utilizing Digital Twins to Optimize the Process Plant of the Future

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Brad Carlberg

Consulting Control Systems Engineering at BSC Engineering

Session Description
Brad Carlberg, a licensed Control Systems Engineer with BSC Engineering, has 39 years of expertise in Process and Control Engineering. He specializes in DCS, PLC, and HMI with a focus on hardware and software design, implementation, and commissioning. Having led 47 automation projects across four continents, including 25 pulp and paper mills, Brad is well-equipped to discuss “The Autonomous Process Plant: Utilizing Digital Twins to Optimize the Process Plant of the Future.”

Brad Carlberg will delve into the Autonomous Process Plant concept, running with minimal human intervention through a Digital Twin that merges Process and Control Models. Optimization spans from basic PID to advanced APC and MPC methods. Essential to this are smart sensors for data collection and rigorous asset maintenance, echoing the path of autonomous vehicles. Secure communications enable data transfer between plant floors and control systems. Software integrates this with DCS and ERP data to guide optimal production and profitability. The Digital Twin serves as a dynamic virtual plant model, addressing design deficiencies and transforming process design.
Key Topics
  • The Autonomous Process Plant is “a plant that runs itself with little or no human intervention” utilizing a Digital Twin coupling the Process Model with the Control Model
  • The various areas of the plant MUST be optimized (tuned) so that they are operated in the highest level of control, whether that be
  • basic regulatory (PID), 2. advanced regulatory (Cascade, Ratio, Feedforward), 3.or Advanced Process Control (APC) or Model Predictive Control (MPC).
  • First, smart sensors and instruments were required to reliably collect data. The plant assets, including instrumentation & electrical, pumps, valves, & pumps, MUST be maintained. The development of the Autonomous Process Plant is following the same path as that of the autonomous auto.
  • First, smart sensors and instruments were required to reliably collect data. The plant assets, including instrumentation & electrical, pumps, valves, & pumps, MUST be maintained. The development of the Autonomous Process Plant is following the same path as that of the autonomous auto.
  • Next came secure and robust communications methods to move the data from the mill floor to a control computer, and back. And finally comes the software and human expertise to combine equipment data with data pulled from process computers (DCS) and data mined from a mill’s enterprise- wide computer (ERP) to “navigate” the best path for production and profits.
  • Digital Twin: A model in software of a physical object including at least one of:
  • a form model describing what it looks like in three dimensions;
    a functional model which represents how it behaves dynamically
  • The Digital Twin is a virtual plant, a dynamic model that contains the process, mechanical and electrical/control design information in one place. Utilizing an advanced control loop system for optimized operation of various area, difficulties of traditional PID control are overcome by similar utilization of a model predictive controller. Utilizing a dynamic model of the process, design deficiencies can be corrected. First, the ability to create and embed knowledge into precompiled objects that represent common equipment. Second, to have design decisions communicated to all engineering disciplines through a database. Third, the ability to communicate via OPC (OLE for Process Control) to any control system. The virtual plant has now changed how the process is designed

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