Most chemical companies view a dynamic process simulator as a valuable training tool that helps operators reduce errors in the control room, thus avoiding potential upsets and unplanned downtime. Keeping production running smoother and longer clearly boosts profitability. However, the financial benefits of such a simulator don't have to stop — or for that matter, start — at operator training. In fact, they can begin much earlier than initial training and continue throughout the plant's lifecycle. Unfortunately, many plants overlook several uses of simulation technology that can greatly improve overall safety and process reliability while reducing capital and operating costs and environmental impact. [pullquote] Pre-Construction BenefitsTypically 60% of capital investments are made during a plant's early design phases. At these stages simulation models can help drive down project cost, sustain schedules and manage risk: Capital cost optimization. Steady-state process simulation enables evaluating various operating scenarios to solve equipment-rating problems. Benefits include minimizing investment and avoiding process bottlenecks. Dynamic simulation also can aid in cutting capital costs, by minimizing overdesign of equipment while still meeting the needs for process dynamics. For example, dynamic simulation was used to determine the optimal size of a water system providing dilution to batch digesters to accommodate sequencing. Control system development. Dynamic simulation helps create realistic operating scenarios that are better for assessing control system configuration than the traditional static checkout method. It allows engineers to evaluate whether: • operator station configurations present a clear picture of the process;• alarms effectively bring the operator's attention to a potential upset;• regulatory controls sustain reliable operating conditions; and• safety systems keep the plant from straying into risky scenarios.Engineering verification. Studies completed prior to capital investment and initial operations allow engineers to optimize equipment design, ensure that reliability and safety are considered, and confirm operational readiness. When combined with operator training, these studies can help identify any shortcomings with the distributed control system (DCS) or logic (interlocks and emergency shutdown systems) configuration. It's best to use the simulator to review plant startup or emergency procedures because weaknesses there can significantly impact production. This review might take a few weeks, with additional time likely required to enhance the system. The operations team should lead the effort — but process and control engineers also should be involved, as they will have to respond to operations' feedback. Improving behavior of complex systems may require some iterations. However, it's certainly better to invest time during earlier project phases rather than during initial operations. For example, many plants rely on large expensive compressor systems whose damage can quickly cost tens of millions of dollars in equipment and loss of profits during downtime. In addition, if a large compressor is severely damaged, replacement may require a two-to-three-year leadtime. It's therefore critical that compressor protection systems are properly designed and correctly operating. By dynamically modeling these systems, engineers can study potential trip events and identify any flaws, or ensure the systems are designed right and fully protected. Another valuable use of simulation is for checking whether an existing flare system will suffice for a plant expansion. Detailed studies of unit depressurizing, including dynamic models of the flare system, can determine the existing relief system's ability to handle new loads. In many cases such studies have shown the current relief system is adequate — thereby obviating expansion of the relief and flare system and thus providing savings that can amount to tens of millions of dollars. Developing optimal strategies. Dynamic simulation, with its ability to predict how the plant will behave during startup, is an effective way to create and validate layouts, procedures and control strategies. It can identify errors prior to capital investment — in the office and off the project's critical path, mitigating project risks, delays and the cost of on-site resolution. This step must involve design/control engineers and process engineers. Plants can apply different control strategies to achieve the same production results. But which strategy or combination of them won't undermine process stability? A liquefied natural gas (LNG) plant noticed strong interaction between its five LNG trains and steam-powered boilers after startup. When one train tripped the boilers the entire plant went down. Dynamic simulation enabled engineers to rectify the problem through decoupling and process redesign. Doing such a simulation before startup could have avoided the difficulty altogether. In another instance, a different company in the early design stages of an LNG project requested to see models for a refrigerant recycle loop. In less than 30 minutes, it realized there wouldn't be enough propane to top off the initial refrigerant inventory prior to production — and thus the startup procedure needed revision. This is a good example of a company improving its plans for startup before training a single operator. For a gas project in New Zealand, development and use of a dynamic model identified numerous opportunities for process improvement. Simulation also allowed thorough testing of initial process design, control, logic, graphics and operation procedures prior to commissioning. Operators used a replica of the actual DCS to control the simulator. Post-Training Process AnalysisUnfortunately, myriad factors can negatively impact even the most tightly designed processes. Material holdup is one such factor. Devices such as condenser drums, distillation columns and reactors that tend to have significant amounts of material holdup can pinch process flows. Dynamic simulation can effectively assess how these holdups will vary over time and therefore affect overall process stability. While steady-state simulation can indicate where a process should settle out when controls are adjusted, it can't account for how stable the process will be as it transitions. In contrast, dynamic simulation can predict how the process will behave as it moves from one operating state to another over a wide range of time. This can allow pushing values beyond normal operating parameters to potentially further increase production while staying ahead of process upsets. TroubleshootingDynamic simulation also can serve as a valuable tool for testing process workarounds, as a new methyl-mercaptan-producing facility discovered. Every time operations personnel there tried to draw water off the H2S-stripper overhead accumulator water boot the resulting sour water (H2S and water mixture) would immediately freeze downstream of the level control valve. So, operators used the custom model provided for training to assess what would happen if they restarted the unit and blocked the water draw from the overhead accumulator. They ran the model for 24 hours to see if the presence of excess water would affect downstream vessels. The model showed that the process remained "on spec" with no adverse reactions downstream. Continuous TrainingSimulators tend to fall into disuse after initial training. However, formal ongoing training programs can provide significant benefits. Analysis indicates that approximately 90% of plant incidents are preventable. And the majority — by some estimates the vast majority — result from the actions or inactions of people. Human beings always will figure in plant operations decision-making; therefore, opportunities will continue for human error to contribute to abnormal situations. Modern process automation systems have allowed operators to assume responsibility for a larger scope of a plant's operation. However, as systems become more comprehensive, we create the potential to place the operator in an untenable position. This "paradox of automation" arises because as systems become more complex they become more difficult to operate. One solution is to add more automation — but this increases complexity. Moreover, automation hinders operators' ability to maintain their expertise. The skills lost are precisely the ones most needed when automated systems can't handle a problem and the operator must intervene. That's why it's important to use simulators for training throughout the life of the process, not just at the initial startup phase. Practical tips for establishing a formal training process include: 1. Identify a simulator "champion." This person should be responsible for developing the actual training curriculum, scheduling operators for training, keeping records and ensuring the simulator is kept up-to-date. The champion should serve as a gatekeeper of sorts for the simulator and should be tasked with identifying opportunities to improve its accuracy. (We'll look more at the champion later.) 2. Develop training programs focused on the most critical processes. This requires prioritizing processes and plant operators for training. So: • Review and assess riskiest operations (for example, those with largest ripple effects throughout the plant)..> • Pinpoint processes with advanced control applications. Because some advanced controls essentially run the process, operators have less opportunity to put their knowledge and skills to work. Therefore, it's critical to keep these operators fresh via simulators. Best PracticesA simulator is just like any other critical subsystem within a plant: the better it's maintained, the more benefits it provides long-term. So, a company should adopt several best practices to maximize its simulation investment. The biggest reason why simulators fall into disuse after initial training is that companies fail to keep them up-to-date with the actual state of their plants. In other words, changes such as revised control configurations aren't incorporated into the simulator. Thus, operators find the simulators rather useless. So, it's crucial to implement a change-management system for the simulator. Its golden rule is quite simple: Incorporate all changes in the plant. The choice of simulator champion is a strategic decision. The champion should be (or report to) a senior-level person within the plant — a senior-level champion may carry more clout in justifying the cost of simulator upkeep and have a better perspective on balancing those costs against others needed to keep the plant running efficiently. The champion should at least have the ear of the plant manager, believe in the role of the simulator, and see the operational and financial benefits the technology reaps. The champion must ensure the simulator isn't simply thought of as a supporting tool that streamlines operations and helps operators practice their procedures — but is considered an asset that adds value by helping the plant reach production goals while keeping staff and equipment safe. That person's first critical task is making certain a mechanism is in place for recording all process changes — everything from piping replacement and control configuration alterations to basic control loop tuning. A plant with a change control board should utilize that group to approve changes as well as to ensure they're forwarded to the appropriate simulation engineer. It's best if both champion and simulation engineer sit on the board. Larger companies may be able to justify having the champion update the simulator. However, this approach requires the champion to possess extensive knowledge of the process and the simulator and be willing to make a longer-term commitment. Smaller companies instead may simply elect to purchase services from their simulation vendors. These arrangements typically call for annual visits specifically to update the simulator based on a running list compiled by the plant's simulator champion. (In an ideal world, though, sites would streamline this process by validating any changes in the simulator before implementing them in the plant. The benefits here are two-fold: confidence in implementing changes and an up-to-date simulator.) Compelling EconomicsThere's a cost for maintaining a simulator and ongoing training programs. However, it pales against that of unexpected downtime, equipment replacement expenses and lost production from a plant incident. Indeed, in most cases, avoiding a single incident, especially if it carries worker safety consequences, provides a strong economic justification. Grant Stephenson is an engineering fellow and global simulation architect for Honeywell Process Solutions, London, Ont. Peter Henderson is senior product manager, simulation, for Honeywell in London, Ont. Henry Schindler is a principal consultant for Honeywell Process Solutions in London, Ont. E-mail them at[email protected], mailto:[email protected] and [email protected].