Simulations have become an integral part of each and every domain today. From product
design to strategy development, simulations give the user an end-to-end understanding of
how each scenario would play out. The insight that simulations offer can help kickstart and
reinforce future iterations of the product or strategy.
As the types of simulations are as vast as the applications themselves, we will be talking
about computer simulations. This century has been a good one for computers. The past
decade has seen massive improvements in the processing power of computers. This
enables industries across the board to run complex simulations without having to invest
heavily in a capable system. Simulation software allows users to design, visualize and
interact with a digital version of the product. The user can also constrain the model and test
it’s limits without ever manufacturing a single component. This not only saves time and
resources, but also ensures a quality product from the get-go.
Simulations are just as important in Condition Monitoring. Condition monitoring is a practice
through which data from various machines is captured using sensors and analysed to
generate insights about the machine’s health. This data is key to not only understanding a
machine’s health, but also the health of the entire manufacturing plant.
So how exactly do simulations tie into condition monitoring? A digital model of the machine
or plant that is being monitored can be subject to different scenarios just as any other
product would. A digital version of the machine can draw its operating parameters from the
sensors that capture data from the machine and behave like it. This behaviour can be
expanded to see how each component is interacting with the other, how each component
functions under different conditions and also how it approaches the end of its life cycle.
Simulations can help mimic the behaviour of any machine thereby making it the base in
predicting how a machine will behave. Simulations combined with software algorithms can
give users the ability to not just understand their machines and their plant, but also to predict
if and when a machine is going to fail. Knowing when a machine is about to fail also presents
opportunities to simulate different load conditions and configurations to determine if the
machine’s life cycle can be extended. It can help determine when a machine will fail if it is
operated in its present condition, what might happen if a maintenance cycle is skipped, how
the failure of each and every component will affect its overall performance.
As the software algorithms evolve over time and the simulation models increase in their
fidelity, the overall productivity of a plant will peak.
Condition monitoring systems backed by simulations can drastically reduce that potential
unplanned downtime that an industry may face due to a catastrophic failure.
Internet of Things(IoT) or Industrial Internet of Things (IIoT) is just a simple but ingenious
combination of simulations and software development to not just connect machines to a user
but to give them the answers to the how, what, when, why and where of the plant at any