Democratization of Simulation and Modeling Software
Many businesses utilize simulation and modeling to accelerate the development of new products, continuously improve existing products, and of course, reduce costs. The process creates a digital prototype of physical products and analyzes their potential real-life performance. This allows design engineers to optimize products early in their development, and reduce the need for expensive and time-consuming physical prototyping.
However, developing a test simulation requires the creation of computer models using specialized software, such as the commercially-available CAD, FEA, and CFD, as well as custom-developed tools. Ideally, these models could be leveraged by various staff within a range of departments such as design, engineering, manufacturing, and even sales and marketing. However, the technical nature of the models means they are typically only utilized by industry experts or experienced software users. This reduces the leverage these tools can provide to well below their potential, reducing their ROI and potentially impacting the organization’s competitiveness.
Democratize access by creating a web portal to your workflows
EASA eliminates this obstacle, allowing an immediate upscale of usage—and thus return on investment—of all of your company’s modeling and simulation activities. With our software, you can quickly create custom enterprise-grade web apps to drive your most valuable and frequently used models and workflows. These web apps can dramatically simplify and streamline complex models, enabling non-experts to safely utilize them, even if they are completely unfamiliar with the various software that might be in the overall workflow. EASA democratizes simulation so a far greater number of users can benefit from them, and also increase the efficiency by which experienced users are able to conduct modeling.
Engineering workflows are traditionally executed through their respective user interfaces or front ends by manually operating each individual piece of software. EASA replaces these multistep, manual processes with customized, intuitive user interfaces, in the form of web apps or portals. With minimal user input, the process can be largely automated, and run securely on back-end servers rather than end users’ local machines. This provides a flexible environment for the users—desktop or mobile—who only require a device with a web browser and internet connectivity.
Advanced aids for knowledge capture
Making software easier to use is a key requirement for democratization, but it is equally important that designs are feasible and correct. This ensures that democratized modeling will be “safe” to use, whether the users are experts or not. EASA enables practical knowledge and design rules to be automatically leveraged within a sequence of simple steps. Elements such as best practices, design rules, and constraints can be easily embedded into these custom web apps to allow any user to create models, no matter their level of seniority. Less experienced, or junior-level, employees will be able to safely conduct simulations with no prior training, and minimal input from senior members of staff, saving time and money.
Embedding your business’s design rules into a web app is a very useful defense against the common issue of senior staff leaving the company, which historically, left a big gap in knowledge and experience.
EASA facilitates the use of Machine Learning models and Digital Twins
Engineering analysis tools can model a number of problems, but they aren’t ideal in every scenario. Most notably, the struggle to predict fatigue, lamination failures, quality “drift” in a production line, and anticipating the critical angle of attack.
The application of machine learning is still a relatively new approach to computing tasks where designing and programming rigid algorithms with complete accuracy may not be feasible. Models which integrate machine learning allow researchers, scientists, engineers, and analysts to generate reliable and repeatable predictions by learning from historical trends in experimental data. The more data there is for the machine to learn from, the more accurate the predictions will be.
EASA can be used to build digital twin apps, making machine learning much easier to execute. These apps allow users to easily import and process huge amounts of data, which is passed to advanced machine learning algorithms to generate predictions of a component lifetime. This eliminates the need for experienced data scientists, and saves time and money for your business.
Contact EASA today
Contact EASA today to find out more about how it works and request a demo. We can demonstrate the benefits of democratizing simulation and modeling workflows, and explain how our software can help your business.