It’s now almost impossible for a person to maintain an overview of a complex production plant where dozens of motors, valves, and pumps are interconnected. As a result, it has become customary to use large software systems to link different components during planning and to automatically control them during operation. Until now, however, simulation has not been commonly used to test an entire production plant before it enters service.
Simulation: Providing a Path to Process Optimization
Simulation is slowly becoming established for the planning of production plants. This technology opens the door to preventing errors at an early stage that might otherwise result in substantial costs for plant operators. But simulation can do much more than that. Experts at Siemens are addressing the question of how it can be used to optimize a plant during ongoing operation. It’s very likely that in the future simulation will function much like a navigation system – by supplying various suggestions designed to optimize plant operations.
Virtual Testing of Complete Production Systems
The benefits of this kind of simulation are profound. During the planning phase – long before a single component has been installed – simulation can be employed to determine whether a facility may have any faults, particularly with regard to its automation systems. With this in mind, specialists at Siemens’ Process Industries and Drives (PD) have developed SIMIT – software that can virtually test a complete production plant before construction begins – including all associated components, technical data, motors, pumps, and gear units. “SIMIT maps the future plant as a kind of virtual twin, which can then be used to run through all of a plant’s automation steps in detail,” explains Dr. Mathias Oppelt, head of Siemens’ Simulation Center for process automation. This process can ensure, for example, that a valve is opened before a feed pump starts; otherwise, the pump or the line would run dry and be damaged.
“This illustrates that new plants can enter service on schedule and, most importantly, with full productivity because a virtual twin and a simulation procedure have tested them in advance,” says Oppelt. The absence of this kind of virtual commissioning with the help of simulation often results in costly downtime, because improvements and optimizations have to be performed. The virtual twin can also be used to train personnel, especially plant operators in the control room, before a plant becomes operational. An important aspect of this training is that operators learn how to manage critical situations that very rarely occur in reality – yet the simulation can be used to provide training for those situations as well.
Simulation: Vast Potential
Oppelt and other professionals see a much greater potential for simulation in the future. That’s because simulation can be used not only during planning but throughout a plant’s entire service life, for example, as changes are made to its production processes. “Simulation allows you to test all the various options for the latest change to a production process during ongoing operation, before you decide on the best option and implement it,” explains Oppelt. This is a bit like a trip planner that suggests several alternative routes in real-time based on current traffic information. Using simulation during operation also makes it easier to decide what to do in the event of faults. Here, within seconds, it’s possible to run through different solutions and select the best one. Realistically speaking, Oppelt feels that a real-time operational assistance system should be ready in six to eight years.
Working with scientists from the Dresden University of Technology and Pforzheim University of Applied Sciences, experts developed a study in which more than 200 specialists were asked to describe the extent to which simulation is already being used in production plants. The results: In only 15 percent of all cases are changes being made during ongoing plant operation based on simulation results. In one-third of the cases, changes are made based on knowledge gained from experience. This can lead to problems when experienced employees leave a company. And people certainly don’t always make the right decision.