Should Mechanical System Design be “Try and See”?
Until recently, the only way to know whether a new mechanical system design would function as intended was to fabricate one and try it out. Intuition, training, and basic analysis could help, but ultimately, prototyping was an essential part of the mechanical system design process, and teams commonly made and tested dozens or sometimes hundreds of prototypes to get to a final design. The process was expensive, time-consuming, and wasteful, but there was simply no alternative.
Today, new digital tools allow us to simulate real-world conditions before a product is ever physically made. Using a range of algorithmic functions, forces like stress, temperature, material flow, particle behavior, and more can be replicated in a digital simulation. Based on the results, mechanical system designers can then iterate and optimize the design until they are satisfied with the performance, speeding time to market, reducing costs, improving safety, and ultimately accelerating innovation.
For those who make industrial machinery used by other manufacturers, simulation has proven to be especially important, since these machines tend to be large, complex, and expensive. Prototyping a plastic consumer toy won’t break the bank, after all, but prototyping a new conveyor belt or a cultipacker brings a steeper price tag. What’s more, industrial machinery needs to hold up under continued and sometimes continuous use for years—something difficult to test in the real world.
Diverse Types of Simulation Apply to Mechanical System Design
Just as there are various forms of artificial intelligence that can serve a range of purposes, there are numerous types of simulation. What these all have in common is that they use powerful algorithms and intensive processing power—more than you’re likely to have on a typical desktop computer. This makes access to storage and computing power in the cloud essential.
Autodesk Fusion 360 has a range of simulation tools available. Other tools like Autodesk CFD, Rocky DEM, and a suite of tools from Ansys provide additional simulation possibilities. It’s all about what you need to replicate and how complex your product or system is.
As with autonomous cars and other AI-driven functions, advanced simulation seemed closer to science fiction just 10 years ago. But with advances in processors and cloud-based data management, simulation is an option that every manufacturer of industrial machinery needs to consider in order to remain competitive.
Discrete Element Modeling
For machines that produce or process particulate matter, like the machines used in the agriculture, food processing, mining, and pharmaceutical industries, discrete element modeling (DEM) has proven to be an important tool. DEM simulates the behavior of large quantities of particles and predicts how all these elements will really react to each other and with the surrounding equipment. Whether you want to analyze how vegetables or grains will behave during picking and packaging with your industrial machine, how rocks will behave in a crusher, how powders behave in a mixer, or how tablets will behave during coating, DEM tools like Rocky DEM can help. With recent advances, you can even replicate the behavior of complex shapes like hay and hair.
Finite Element Analysis
But what about the machine itself? How much weight can a frame handle? Is the operating frequency close to the natural frequency? You can simulate the response of materials and objects to forces such as stress, displacement, and temperature using Finite Element Analysis (FEA). FEA works by breaking down a design or object into tiny finite elements, like little cubes. Then it uses mathematical equations and algorithms to predict the behavior of each little element, adds up all the individual behaviors, and makes a prediction on the behavior of the whole piece, allowing you to optimize your part or component without having to prototype it.
Electrical System Simulation
If your industrial machine design includes electrical or electromechanical systems, being able to experiment with various electrical architectures can be a real advantage, ensuring machine longevity and preventing burnout. Electrical system simulation is a game-changer for fuel economy, energy management, and power consumption analysis. You can also simulate the cooling of electronics based on the shape and airflow around a circuit through computational fluid dynamics.
Computational Fluid Dynamics
If you need to simulate fluid flows such as a liquid or a gas in your machine design, you can use Computational Fluid Dynamics (CFD). Commonly used to simulate combustion in engines, wind flow around an object, or component temperatures, CFD predicts how liquids and gases will perform, helping you reduce energy consumption and boost efficiency in your industrial machinery products. Considering fluid and air affect the performance of just about every kind of device you can build, and that the mathematics involved are too complicated to do by hand, CFD is a critical type of simulation.
As additive manufacturing takes hold, additive simulation offers the ability to move faster, prototype less, save money, and address common problems such as distortion and residual stress. With simulation programs like Ansys Print, you get a layer-by-layer analysis of stress accumulation and high-strain regions. Running additive simulation provides previously impossible diagnostic information, allowing engineers to discover the optimal machine process parameters, and ultimately, the best part design.
Simulation is a powerful tool in its own right and can also play an important role in other tools and processes, such as generative design. Generative design uses artificial intelligence, machine learning, and algorithmic problem-solving to generate solutions to design challenges based on parameters, constraints, and requirements set by the designer. It generates thousands of possible solutions, then uses simulation and input from the designer to evaluate and refine those solutions. It’s an important way to collaborate with computation, accelerate the design and optimization process, and improve performance using solutions that a human designer would never think of alone. Without simulation, it would be significantly less useful.
Digital twins are another process where simulation can be helpful. Digital twins create a digital replica of a real-world system or facility, bringing together model design data and real-time data from sensors and machines. With that data, you can then run simulations to predict what might happen and use the results to make better decisions. The digital twin market is growing fast, almost 60% every year, and is predicted to reach $48 billion by 2026. You can simulate the entire life cycle of a product and use the data to improve future versions, bringing optimization to a new level.
Simulate, Iterate, and Explore
Prototyping will remain an important method of developing and testing new equipment and designs. But by moving some amount of trial-and-error into the virtual world with digital simulation, engineers can explore, experiment, and discover new ideas while reducing waste and cost.
Simulation is a remarkably powerful tool for mechanical system design, and when used properly it can help you produce innovative, energy-efficient, high-performing products in the most efficient way possible. When you’re ready to incorporate simulation into your workflow, KETIV is ready to help.