Data Driven CAE

Data Driven CAE

Project Description

Problem Statement

Automotive OEMs have been using Computer-Aided Engineering for more than half a century to validate and optimize the vehicle design and development process. Even though CAE helps us to reduce product development costs and time-to-market by eliminating the need for testing multiple prototypes, the most accurate results are achieved only in the later stage of the design cycle after performing several iterations and optimizations.

In today’s era of Industry 4.0, manufacturers are required to design and develop vehicles by integrating new technologies including Artificial Intelligence, Machine Learning, Data Analytics, Digital Twin, and Cloud Computing. Instead of being physics-based, such an integrated vehicle design process should be data-driven and requires managing large volumes of data which is a major challenge with our current CAE approach.

Solution – EinNel’s Data-Driven CAE

Our EinNel’s Data-Driven CAE platforms transform automobile industries from Simulation-Driven Engineering to Objective-Driven Engineering. We incorporate machine learning and big data solutions into CAE to predict the system behavior with high accuracy at the beginning of the design cycle.

Our powerful predictive data analytic engines generate actionable insights by processing a great deal of simulation dump files from across a variety of CAE software applications. To make futuristic design decisions, both design and manufacturing constraints are considered, avoiding the possibility of iterations in the later stage of the design cycle.

Using our cloud-based CAE platform, organizations no longer need to rely on high-end computing hardware. By utilizing the cloud’s full potential, complex designs can now be validated with less computing power, allowing engineers to work from anywhere and anytime.

Benefits of Data-Driven CAE

  • Reduce the cost of design cycles and time to market by 50% compared to the traditional CAE approach.
  • The design quality and reliability are increased by almost 80% by using Machine Learning and Data Analytics.
  • Less human intervention and domain expertise is required to interpret the design results.
  • Our big data solutions allow you to access simulation data from any software you desire to save big on license costs.
  • Removing hardware barriers and associated costs by leveraging the full power of cloud computing.
  • Training ML models based on historical data and experience pave the way for continuous design optimization.

Big Data Solutions

Database development for organizing and storing simulation dump files in centralized cloud storage allows us to perform data analytics by processing large volumes of data in no time.

CAE Data Extraction

Extract CAE data from various FEA/CFD solvers to eliminate the need for different CAE software. Now, you can preserve and access your simulation data using any CAE software.

Machine Learning for CAE

EinNel uses custom supervised machine learning algorithms to model the system behaviors for future performance predictions with high accuracy and less processing time.

Design Data Visualization

Create interactive dashboards and get actionable insights for all design parameters. Change from contour-based observations to visual representations for quick design decisions.

Design Optimization & Decisions

Use our combined approach that incorporates analytical, numerical, and statistical methods instead of the classical approach to optimize and accelerate design decisions.

Design Sensitivity Analysis

Identification of critical components/parameters related to each response value, constraint, and objective with the help of machine learning models and data-driven analytics.

Design Twin Development

Develop design twins that replicate the behavior of the systems in real-time operating conditions simultaneously to CAE simulation for improved performance and accuracy.

KPIs Calculation

Calculate Key Performance Indicators based on design constraints along with manufacturing feasibility and real-time operational conditions to meet the demands of modern NPD.

CAE Cloud Application

Read-to-use cloud-native applications to speed up your complex simulations and overcome hardware limitations. It allows us to access CAE simulations on almost any device from anywhere.