Simulation software acts as an insurance policy against costly mistakes because it enables manufacturers to understand how a product or component will behave before it’s put into use or how it will affect the production line.
ABI Research forecasts that manufacturer spending on simulation software will surpass US$2.6 billion in 2030. Spending will accelerate over the forecast period (growing by CAGR 7.1% between 2022 and 2030) as the user base of simulation software expands in aerospace, automotive, heavy machinery, and the consumer-packaged goods sectors.
Drivers of adoption
Michael Larner, principal analyst, industrial & manufacturing at ABI Research, noted that in the past, manufacturers would create prototypes and test under certain conditions.
He explained that simulation software provides more flexibility by enabling manufacturers to examine how, for example, components in aircraft and automobiles respond to heat and vibration, or how to optimize the layout of a printed circuit board in an electronic device.
“Also, manufacturers’ production lines are moving from batch to continuous manufacturing, so they need the ability to anticipate and alleviate bottlenecks relating to switchovers,” he continued.
Growing use
Simulation software solutions from the likes of Siemens, Dassault Systèmes, and Hexagon help manufacturers not only to create robust products but also expand usage of simulation software by specialists as well as individuals in product development and on the factory floor.
Simulating software now supports a wide number of decision-makers, such as plant managers, systems engineers, and maintenance teams.
Caution ahead
However, vendors of simulation software for industrial applications face some challenges.
Larner warns, however, that there is also a persistent tribal knowledge within some facilities where staff is hostile to change and so suppliers will need to overcome their lack of trust in simulation results.
“Suppliers will also need to work with their customers to understand the performance parameters and the acceptable trade-offs in different verticals so that findings are based on reality and users trust the results,” Larner concluded.
