We know it quite well, industrial simulation is used for reducing the risk of making mistakes when it comes to modifying existing systems, or conceiving new ones, by realizing virtual experiments.

But let’s see more concretely the kind of problems it is supposed to solve.

Testing investments

Investments are where a company takes the biggest risks, with the highest financial impact: it is always an important event for the company and it is crucial to balance exactly the investment (we won’t mention now the need to support and exploit it at best…).

"When we have at last the super powerful Rolls-Royce in our system, everything will be done more smoothly and more rapidly!" Maybe the new equipment will reduce delays, provide more capacity or enhance customer service. Unless it mostly clogs the machines downstream, produces stock or monopolizes operators… In a complex system, one cannot dissociate the physical equipment from the behavior and logics linked to the flows that go through it! It’s like wanting to play chess with a chessboard and pieces, but not the rules of the game.

The physical side and the operational side are strongly linked: simulation will show that the investment can meet its goal and will also indicate which peripheral actions to take to help its application. Nowadays, engineering companies are often the first ones to suggest using simulation, because it has become a tool for their credibility and even for the promotion of their offer.

But the conclusions of the simulation study may imply to reduce or distribute the investment, or to concentrate it on a single element of the system, or to postpone it for now, since the study may bring to light other sources of improvement leading to the same gains…

Anticipating

In the real system, it is almost impossible to do tests: the museum cannot be closed, hundreds of extras cannot hired to play what will happen when the new exhibition aisle is inaugurated. The only possibility for a "dress rehearsal" is simulation: won’t the entrance checkpoint create a long queue that will discourage visitors? Will the elevator at the base of the building prove sufficient? Will there be enough tables at the cafeteria at the rush hour? In case everybody has to evacuate, are emergency exits located at the spots allowing for a good distribution of visitors? All these installations are a bit irreversible, a good anticipation of problems helps taking early the best decisions…

For the next exhibition, eight months from now, the visitor tour will be different, the public too as many school children are expected, and the conference room on the ground floor will be used as a projection room: all this will be simulated!

Controlling an existing system

In managing production workshops where things seem to go smoothly, simulation will help detect if there is too much work in progress, intricate handling decisions to satisfy confusing circulation of parts, inappropriate batch sizes, overcapacities. When working on a manufacturing system that has until now developed without simulation, in reaction to contextual pressure but with no consistency or dynamic testing, the performance and profitability of the global system can be enhanced, with sometimes impressive gains.

On the contrary, in a system where the performance is not as good as expected, instead of first rushing to buy some new material (machines, conveyors etc.) to get things better, it is often wiser to invest in a simulation study, that will show that a better balancing of flows will avoid stopping/restarting machines, or that better calculated servo control between handling machines and packing machines will absorb everyday shutdowns and maintenance without impacting the global effectiveness.

 

And without simulation?

 

It does work too, of course… One will notice only the big mistakes, the major malfunctions: the production line blocked, the new product manufactured in twice the time expected, the queue of car that jams even the roundabout, the systematic supply failure, etc.

But industrial simulation is not only an insurance against very big errors. By not studying a system through its dynamic flows, without no possible benchmark with other solutions, we just know that we wasted an opportunity of lesser costs, of better customer satisfaction or higher profit, ignoring this potential for progress that simulation is.