What is Computer Aided Engineering (CAE)?

Computer-Aided Engineering (CAE) is the broad usage of computer software to aid in engineering analysis tasks. It encompasses simulation, validation, and optimization of products and manufacturing tools. CAE covers a wide range of applications, from finite element analysis (FEA) and computational fluid dynamics (CFD) to multibody dynamics (MBD) and more. By leveraging CAE, engineers can predict the behavior of products in a virtual environment, allowing for more efficient and effective design processes.

How can CAE add value?

• Cost Reduction: By simulating and optimizing designs virtually, CAE helps reduce the need for physical prototypes, saving both time and money.

• Improved Product Quality: CAE tools enable thorough analysis and validation, leading to better-performing and more reliable products.

• Enhanced Innovation: Engineers can explore more design alternatives and innovative solutions using CAE tools.

• Faster Time-to-Market: Virtual testing and optimization accelerate the development cycle, helping bring products to market more quickly.

What is Finite Element Analysis (FEA or FEM)?

Finite element method (FEM) is a method for numerically solving differential equations arising in engineering and mathematical modeling. Computers are used to perform the calculations required to simulate real-world forces, vibration, heat, fluid flow, and other physical effects defined by boundary conditions.

How can FEA add value?

Finite Element Analysis (FEA) is a one of the many tools that allows us to simulate and analyze the behavior of structures and components under various conditions. By applying FEA, we can predict how a solution will perform under a wide range of loads, ensuring reliability and durability prior to the development of a Minimum Viable Product (MVP). Through simulating real-world conditions early in the development process, FEA allows us to detect potential issues and weaknesses within the design before they become costly problems. This proactive approach not only reduces development time but also minimizes material waste and costs associated with trial-and-error testing.

What is Computational Fluid Dynamics (CFD)

Computational fluid dynamics (CFD) is a method for branch of fluid mechanics that uses numerical analysis and data structures to analyze and solve problems that involve fluid flows. Computers are used to perform the calculations required to simulate the free-stream flow of the fluid, and the interaction of the fluid (liquids and gases) with surfaces defined by boundary conditions.

How can CFD add value?

Computational Fluid Dynamics (CFD) is a powerful tool that allows us to simulate and analyze fluid flow, heat transfer, and related phenomena in complex systems. By applying CFD, we can predict how products will perform in real-world fluid environments, ensuring optimal design and performance. This approach not only reduces development time but also enhances product reliability and efficiency prior to the development of a Minimum Viable Product (MVP). CFD enables us to optimize designs by providing detailed insights into fluid dynamics and heat transfer. Through such simulations, we can design solutions that maximize energy efficiency and minimize environmental impact. This provides a virtual testing environment where we can validate product performance under various operating conditions. This significantly reduces the need for physical prototypes, saving time and resources while further helping us create sustainable solutions that are both cost-effective and environmentally friendly.

What is Multibody Dynamics (MBD)?

The multibody dynamics (MBD) generally refers the study of mechanical systems that consist of a set of rigid bodies and links connected each other by joints to restrict their relative motion. Computers are used to perform the calculations required to simulate motion, loads, and forces in mechanical systems.

How does MBD add value?

Multibody Dynamics (MBD) is a powerful tool that simulates the dynamic behavior of interconnected rigid or flexible bodies. By applying MBD, we can predict motion, loads, and forces in mechanical systems, ensuring optimal design and performance. This approach not only reduces development time but also enhances product reliability and efficiency before creating a Minimum Viable Product (MVP). MBD enables us to optimize designs by providing detailed insights into mechanical interactions and system behavior. Through such simulations, we can design solutions that maximize performance and durability. This provides a virtual testing environment where we can validate product performance under various operating conditions. This significantly reduces the need for physical prototypes, saving time and resources while helping us create solutions that are both cost-effective and reliable.