How To Optimize The Value Of An Operator Training Simulator

ARC Advisory Group Insight provides general guidelines.

By Rick Rys, Senior Consultant, ARC Advisory Group

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When assessing the value of an investment in training simulator technology for your plant, it's important to first consider how and in what type of facility the training simulator would be used. For example, would the simulator be used to train plant managers, engineers, and/or maintenance technicians as well as operators? Would the simulator also be used to test control strategies in a safe, offline environment? And, perhaps most importantly, is the target plant a new, grassroots facility, or an existing brownfield facility?

All models are wrong; some are useful.

The answers to these questions will help end users determine the best types of technology to implement for simulating both the process itself and the control system. Depending on what the end user hopes to accomplish, the relative fidelities of both the process and the control system simulations should be aligned to optimize the value of the technology and, ultimately, the return on investment.

Why does it make a difference whether the plant is a new or existing facility? In a new facility or a plant expansion, the cost of the operator training simulator (OTS) can often be budgeted as part of the overall project, for which it would typically represent a very small percentage and thus not be overly difficult to justify. The need to train operators in a new facility is also usually more obvious than in an existing plant, in which the operators have already gained a consider-able amount of operating experience. Furthermore, in established plants that have often been in operation for decades, the, "We've managed fine without one so far," mentality often dominates.

Unless there has been an obvious pattern of operator errors leading to "near-misses," requiring operator qualification and/or re-qualification, it can often be difficult to justify the investment required to purchase, implement, and maintain an OTS in an existing plant. This is particularly true if the plant goes the high-fidelity route for both the process and control system simulator models. On the other hand, an OTS can add obvious value in existing plants when a new or significantly upgraded control system is installed with which the operators do not have experience.

To optimize the value of an OTS, it's important to match the plant requirements to the available technology solutions. This ARC Advisory Group Insight provides some general guidelines for doing so.

Options for Control System Simulation

In the past, before simulators were available, both training and engineering for control systems (DCS and PLCs) were typically performed right on the actual control system. Once the control system was installed, training occurred while controlling the plant processes. This limited the scope and effectiveness of operator training and left the control engineer without any development or test system.

Basic Configuration for a Control System Simulator

As ARC consultants learned during a number of recent visits to process plants, many plants and mills today have only the running control system in place for training and testing new control schemes. This is unfortunate, because a wide variety of options for both simulating the process control system and simulating the actual process are available today. These range from generally low-cost, generic off-the-shelf control and process simulators to highly customized high-fidelity simulators that represent exact models of both the control system and the process and further enhance the learning experience using 3-D virtual immersive plant environments; with many alternatives in between. This ARC Insight will focus on those “in between” alternatives that can often be easier to cost justify in existing plants.

ARC has written extensively about the exciting advances being made today in immersive-type training simulators that simulate actual plant environments in amazing detail (often down to the vibrations, sounds, and smells one would encounter in the actual plant) and employ avatars that place the trainee in this highly realistic immersive environment. While research indicates that this can enhance the learning experience and improve retention significantly, this type of technology is often too costly and sophisticated for the majority of today’s brownfield plants unless they are undergoing a major capital plant expansion or technology upgrade.

Control System Development and Checkout

In years past, control system software for greenfield projects was developed on the actual staged control system. One hundred percent of the control system I/O was tested to make sure it was operational. Test panels were wired to the I/O points. These test panels had switches to drive digital inputs and potentiometers to drive analog inputs. They used lights to read digital outputs and gauges to see analog outputs. At the same time the hardware was being tested, engineers would be able to check HMI graphic displays, alarm settings and certain control functions like controller action, trip settings and alarm functions. This open loop simulation represents the lowest level of fidelity because the simulation engineer, rather than actual process dynamics, sets the process behavior. The I/O can be set to any steady state value of the process and variables manually manipulated one at a time to test the control system software. As long as the system was being staged, it could be used for training operators and testing the control system; although any semblance of “simulation” took place in the minds of the engineers turning knobs and flipping switches.

Today, the control system software is developed by a team of engineers on offline personal computers, often using network servers and, increasingly, cloud computing. To support the control system development effort, most DCS suppliers and many PLC suppliers offer relatively low-cost PC-based control software configurators that create the run-time control software ultimately deployed in the actual control system. The best systems can both configure and execute the control functions in this virtual environment. The ability to execute the control functions in a virtual control system allows options for both operator training and control scheme development and testing.

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