A well trained and skilled operator is one of the key elements in increasing the plant's safety and productivity. Enabling quality training for operators is becoming more and more important as they nowadays need to handle increased load of information and duties while the lack of operators' training is the major reason for their inadequate performance. 
Conventional training methodologies are not enough to train an operator for seldom-occurring dangerous situations, therefore the operator training simulator (OTS) has become inevitable part of their training where they are able to learn without actually endangering the plant and personnel (Patle et al).

Why OTS is needed, what are typical applications and challenges for its application in process industry, and what strategies to apply?

An increasing number of companies are using OTS to train the operating staff on handling different malfunctions, startup, shutdowns and infrequently occurring modes of operation.

The components of OTS by Ayral et al include:

• Same equipment, distributed control system configuration, tags and logic as the actual plant,
• Training environment nearly identical to the control room,
• High level of realism due to reasonably accurate dynamic process models,
• Realistic process models to provide the sense for urgency in reacting to training exercise events,
• Used in teaching operators to recognize and react to plant-specific events and scenarios, with an instructor console,
• Ability to run exercises without an instructor,
• Maintained to remain consistent with the actual process and controls.

The main role of an OTS is to replicate process dynamics behavior over a wide range of operations including startup, shutdown, and critical situations.
Main functionalities of OTS reported by Dudley et al. include:

• Scenario creation and imparting malfunctions/upsets into the process model,
• Monitoring and trending of any plant variable,
• Training of operators and evaluation of operators’ performance,
• Run/pause/resume and load/save capabilities,
• Snapshots, backtracks, and speed control,
• Storing of data on plant variables, which can be used for postscenario reviews.

Why Operator Training Simulators are needed?

Many industrial accidents occur because of improper training on automation and process equipment, instrumentation, or in safety procedures for operations and maintenance. Operators must be trained for emergency situations so that they know how to respond to process malfunctions and other abnormal events. Operator training simulators offer one of the best methods to provide this training.

Reported benefits from OTS include faster startup, improved operations, reduced upsets, and reduced operator errors. Skilled operators are essential for safe plant operation, maximum process performance, reduced environmental impact, and reduction of accidental losses in the complex chemical processes. Hence, there is a need for continuous developing of their skills as their performance has a direct influence on the safety, productivity, profitability, stability, and controllability of the process.

An OTS takes care of this gap by combining the theoretical training and hands-on practice. Manenti stated that a real plant is no place for training, and prior experience based on dynamic simulation may be fundamental in reducing the impact/damage of accidents or even in preventing them.
Glaser described the need for a systematic approach for implementing operator training simulation to obtain maximum training benefits. He discussed a systematic, five-step approach for implementing operator training simulation over the long term (viz., identification, normal operation, start-up and shut-down, troubleshooting, and optimization) along with feedback from OTS users, and use of operator training simulation to develop applied skills (viz., cooperation, communication, supervision, and situational awareness). To ensure that operators retain the requisite knowledge and the skills, and that they remain competent to control processes in emergency conditions, companies should provide them with opportunities to develop and sustain their capabilities. The plant operators receive plant-specific and realistic hands-on training ahead of plant start-up and complete plant operation through proper use of the OTS. The reliable OTS can also be helpful in other functions such as troubleshooting, and developing new operating and control strategies. Thus, the simulator can be a useful tool not only for training but also for the process and control industry (Dasgupta).

The basic requirements for application of OTS in process industry

According to the survey conducted by ARC Strategies among industry professionals, the most important requirements for OTS can be summarized in this list:

1. Simulating startup and shutdown, heating up the plant
2. Simulating incidents
3. Describes the dynamics of the process
4. Simulating normal operation
5. Simulating process/product transitions and changes
6. Simulating external disturbances
7. Describes steady state
8. Simulator uses 2D
9. Free choice of simulation speed compared to real-time
10. Model the plant behavior qualitatively
11. Simulating energy consumption
12. Simulating long-term trends (catalyst deactivation, heat exchanger fouling etc.)
13. Simulator uses 3D visualization
14. Simulator uses 3D immersive

The priorities are changing dependant on the process involved. However, industry professionals agree that they want to train their operators for the situations with the most risks and those are startup’s, shutdown’s and abnormal situations because major plant accidents are more than five times more likely to occur during abnormal operations (Yang et al.). After those priorities, focus comes to the operations related to process efficiency and optimization.

The challenges in the development and implementation of operator training simulators

An adequate dynamic model requires details of equipment size and shape, process responses, controller tuning etc.

The chemical reactors and distillation columns are the most complex part of the process to model because of the large number of variables influencing each other and many complex equations describing those interactions.

The chemical reactors are the key elements in many processes and complicated unit to model as each reactor has a unique geometry, flow arrangement, and reaction kinetics. Consequently, detailed knowledge of the reactor is necessary for developing the model for an OTS. As reactors are usually proprietary, their developers are often reluctant to share details about reaction kinetics and reactor design with OTS developers. Under such circumstances, a simplified model or a black box models are often used (Cameron et al.). Special consideration should be given to the degree of accuracy, calculation speed, convergence, and robustness of a model to be used for operator training.
The model equations should be structured carefully as establishing an accurate steady-state solution for the initialization of the dynamic model is very critical. The process dynamic model and the emulated/stimulated control system should run on a compatible platform in order to interface them with minimum cost and effort (Patle et al).

Accuracy
Both the model and modeling tool should be sufficiently accurate to ensure fidelity and consistency of results. Stawarz and Sowerby used standards of <2% and 10% errors for critical and noncritical parameters, respectively, in a model developed for OTS. Considering this, surprisingly simple models can yield sufficient fidelity for operator training needs.

Zhiyun et al. also stated that, when the ultimate goal of the simulation work is to build OTS, requirements of modeling accuracy are not so strict. Required accuracy depends on two important issues: firstly, the modeling, where sufficient details should be introduced to obtain reasonable accuracy, and secondly, the solver in the modeling tool (error estimates, tolerance values, etc.), which determines the accuracy of the numerical solution of the model (Laganier).

Robustness

The modeler should be able to deal with process issues efficiently without having limitations of issues like convergence, tear streams, solver’s incapability, especially, in case of unavailability of good initial guesses.

“In some cases, companies had to delay their projects due to unavailability of good initial guesses”, Cox et al. reported. For a variety of disturbances (including shut down of a unit), the model should be able to provide a solution. This is essential especially when the end user does not have the background to comprehend what is going on in the simulator and thus cannot fix any numerical problem that may arise (Laganier).

Strategies for success

Strategies for success need to carefully address all the challenges stated above through all the phases of the project and those include (Magarini et al):

• OTS scope-of-work. Definition of appropriate scope of work is a critical step at which the project can easily take a wrong path. The step is entailing definition of the OTS process models’ scope and size, boundaries and accuracy , installed functionalities and simplifications that do not negatively affect core simulations such as the emergency shutdown (ESD) sequences. The final OTS scope is a balanced trade-off between content, performance functions and cost, and has the consensus of the plant owner’s operations managers.
• OTS vendors. These are accurately screened for in-house design expertise, reference projects of similar complexity and magnitude, reference experience of current design staff and competitive pricing.
• Functional design specification (FDS). This is developed by the OTS vendor and details the agreed OTS design basis comprising custom process models, simulated or emulated operator stations, instructor facilities and supporting software. The EPC contractor reviews and approves the FDS for accuracy and compliance with the OTS purchase order (PO) and technical specifications.
• OTS engineering in compliance with plant process, equipment and I /C design. The project deliverables schedule ensures OTS ready- for-use in line with the operator training schedule.
• OTS factory and jobsite acceptance testing. End-user training in correct OTS use, maintenance, and configuration and OTS as-built updating, along with end-user training in correct OTS use, maintenance and configuration, and OTS as-built updating. The OTS ready-for-use schedule is crucial. The project OTS engineer must ensure that all design and control  system inputs needed to complete process models and control simulations are available enough in advance to have the OTS up and running per the operator training schedule at the plant jobsite (Magarini).

To offer an overview, costs estimations according to Ayral et al for a standard refinery process unit, like a fluid catalytic cracking unit, including the various software, hardware and service components, will cost approximately $700,000 or more, depending on overall complexity of the unit and the type of control integration that is required.
However, author's opinion is that the prices are still highly overrated and that future activities in the field will be decreasing them or give another added value to operators' training.

Simulation software packages for developing OTS

A suitable process model and its simulation are at the heart of OTS. The computer-aided process design and the simulation tools have been successfully implemented in chemical and oil industries since the early 1960s, aiming for the development and optimization of integrated systems. The commercial process simulation software packages enable convenient development of very complex models with numerous equations.

However, no model is completely accurate. It is important to note the admonition of Box: “All models are wrong, but some are useful”. 

Komulainen et al. reported that there is an increasing interest in the use of commercial process simulators in chemical engineering education. Commercial simulators include Aspen Plus and Aspen HYSYS (Aspen Technology, Inc.), ChemCAD (Chemstations, Inc.), UniSim Design(Honeywell International Inc.), PRO/II, and DYNSIM (Schneider Electric Software), PetroSim (KBC, Yokogawa).

In making the choice of the most appropriate modeling tool, the capabilities of the simulation software should be estimated in accordance with the above-mentioned challenges and requirements for OTS development. 
Among all commercial software packages/tools available for the simulation of chemical processes, those commonly used for OTS development are: 

• Aspen Dynamics & HYSYS, Aspen Technology (www.aspentech.com)
• AZprocede, Azprocede (www.azprocede.fr)
• ChemCad Dynamics, Chemstations (www.chemstations.com)
• DYNSIM, Schneider Electric Software (software.schneider-electric.com)
• INDISS Plus, RSI (www.simulationrsi.com)
• JADE, GSE Systems (www.gses.com/simulators)
• K-Spice, Kongsberg Oil&Gas Technologies (www.kongsberg.com)
• Mobatec Modeller, Mobatec (www.mobatec.nl)
• Petro-SIM, KBC owned by Yokogawa (www.kbcat.com)
• TSC Sim, TSC Simulation (www.tscsimulation.co.uk)
• UniSim, Honeywell (www.honeywell.com)
• VMGSim, Virtual Material (www.virtualmaterials.com)
• VisSim, Visual Solutions (www.vissim.com)
• Visual Modeler, Omega Simulation (www.omegasim.co.jp)

OTS key benefits

Reduction in planned turnaround time. One of the key benefits that OTS is a reduction in planned turnaround time. This benefit includes planned startup and shutdown time before and after scheduled maintenance. It is not intended to include benefits for unplanned shutdowns and maintenance (Ayral).

Reduction in abnormal situations. OTS are also useful when addressing the reduction in abnormal situations or incidents caused by human error.

Optimization of APC utilization. APC utilization can also be optimitized. This benefit is estimated as a 1 5% improvement in total plant APC benefits because operators understand and utilize the APC better, and therefore have higher utilization factors.

Future directions

The process simulators are valuable both in engineering studies and in operator training. However, they are also considered to be a tool for specialists. It is essential for the simulation tools to be more general and user friendly. For this, simulation tools need to be continually developed and improved to meet the increasing demands. The cooperation between simulator suppliers and process engineers in performing studies and further developing the models will play a key role in OTS development. 
Some of the future suggestions discussed by Patle et al that we found very well defined are:

• Realistic and robust model development: For OTS to be effective, models should represent the process behavior as accurately as possible. Models should be robust to measurement and modeling errors. Proper equation-oriented model formulation is necessary for this.
• Modeling more classes of processes: In addition to the traditional unit operations/processes, membrane separations, micro-reactors, biological reactors, crystallization, etc. must be studied and included in the simulators as they are increasingly becoming part of the chemical processes. Enhancing the database of thermodynamic properties, components, and reaction kinetic parameters is also vital.
• Flexible modeling: Models should be developed with the aim of facilitating their interface with other commonly used software packages/tools as this will lead to the increased usage for different purposes.
• Robust solvers: Solvers should be robust and capable of coping with the drawbacks associated with them

OTS is a highly valuable system not only for training purposes and therefore has the potential for increased usage. So far, OTS has been used most in oil and gas, hydrocarbon and power and energy industries, where the associated risk is higher. Development of cost-effective OTS is essential to increase the usage of OTS in other fields such as bioprocess engineering. As well, OTS has the ability to be used more in process optimization, research and development and operations planning.

Reference:

1. Ayral T, De Jonge P. Operator training simulators for brownfield process units offer many benefits. Hydrocarb Process;
2. Manenti F. Natural gas operations: considerations on process transients, design, and control. ISA Trans;
3. Patle D., Gande P.R., Zainal A., Operator training simulators in the chemical industry: Review, issues, and future directions, Reviews in Chemical Engineering, 2014
4. Glaser DC. A systematic approach to implementing operator training simulators. AIChE Spring Meeting and 7th Global Congress on Process Safety, Conference Proceedings
5. Dasgupta S. Use operator training simulators for FCC units. Fuel Technol Manage, 
6. Box GEP. Robustness in scientific model building. New York: Academic Press, 
7. Balaton MG, Nagy L, Szeifert F. Operator training simulator process model implementation of a batch processing unit in a packaged simulation software. Comput Chem Eng 
8. ARC strategies, Strategies for Operator Training Simulators, 
9. Magarini, A ., Knowledge transfer: A primer for major capital projects, Hydrocarbon Processing