This guest contribution is written by Renganathan Sekar, Research Engineer at MFRC, South Korea. MFRC is a member of the Altair Partner Alliance.

We all know that great things need a lot of time. No second thoughts about that. But what if we can reduce the time spent on CAE analysis without compromising the quality? It’s always important to have an eye for continuous growth to understand where there is room for improvement. Below is a software utility matrix to help engineers better understand the value of various CAE tasks, each critical for a sound product design.

Figure 1: Software utility matrix showing software utility versus the time it takes to learn.

The four quadrants of the matrix are:

1. Beginner - Some tasks take minimal time and do not require sophisticated CAE. Simpler analysis models that are repetitive and low impact tasks fall in this category. There is no need for advanced CAE at this stage and the time taken to learn this skill is low. Example: A static linear uncoupled FEM analysis.

2. Inevitable - These tasks are very specific and require a lot of time to learn and apply them. Inevitable tasks may not be productive as one cannot scale up or reuse them. Even so, these tasks are inevitably owing to their specific nature. Example: Customized sub-routines or constitutive equations.

3. Expert - The majority of commercial CAE falls in this category. We all know that sophisticated CAE analysis is time consuming and requires tremendous focus and iterative improvements. These tasks add a lot of value in the product development lifecycle. Every company develops this domain expertise by investing in both their employees and R&D. This is gradual and demands continuous improvement. In periods of technical crisis, it is the knowledge of these expert users that come to the rescue. Example: A crashworthiness analysis of an automobile.

4. Rockstar - This is a new category which is ideal yet difficult to achieve immediately. However, it can be done if one is able to learn a software, apply it to a process, and inform it with previously accumulated knowledge. This slashes the time to market and offers a big competitive advantage. The time it takes to learn and apply a software is a very important component to factor in decision making.

Let’s look at an example from the metal forming industry. Conventional forging process design is very time consuming. The complexity is further compounded by the multitude of influential process parameters. The ideal solution would be to have a tool that is easy to get started with minimal effort. This will ensure that a team spends their precious time on actual problem solving and not on learning the software. This is where AFDEX, an intelligent metal forming simulator available through the Altair Partner Alliance, can be applied. Reputed metal forming companies use AFDEX to evaluate their process design with minimal time to get started.

Organizations can also couple AFDEX with established optimization tools like Altair’s HyperStudy™, which can turbocharge the process design phase.

If your company has already accumulated knowledge in optimization techniques, isn’t it effective to use that along with AFDEX?

I can sense your heads nodding in agreement. Why wait? Become the Rockstar now.

Some examples of AFDEX simulations coupled with HyperStudy can be found here.