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May 28, 2024

CAD Classification with Low-Code Machine Learning

Deep Dive into a machine-learning CAD classification with our Solution engineer Ram.

In this Deep Dive session, our Solution engineer Ram is utilizing our low-code platform to perform a machine-learning CAD classification. Through practical examples and a live demo, Ram will build ML classification tasks from scratch that can assist engineers.

The Current State of Engineering Tools and Processes

Before diving into solutions, let's address the current engineering tools and processes challenges. Despite the inherent nonlinear iterations, the workflow is often linear and sequential in hardware product development. Engineers are divided into silos based on their expertise and the tools they use, from CAD designers to simulation and manufacturing experts. This segmentation creates inefficiencies and hinders collaboration.

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Leveraging Automation with Low-Code Platforms

At Synera, a low-code language tailored for engineers can bridge these gaps. By automating repetitive and manual tasks, we can accelerate product development. Our tool includes a canvas, allowing engineers to build workflows visually, closely mirroring their traditional work methods.

One of our standout features is the powerful 3D visualization integrated into our low-code software. This allows users to design workflows with nodes and templates, making complex tasks more manageable. For instance, our customers, like EDAG Group, have reduced the time required to achieve their head impact coefficient values using our tool.

Applying Machine Learning in CAD Classification

The core of our discussion today is integrating machine learning into CAD classification. Machine learning is particularly useful when the relationship between inputs and outputs is complex and hard to define through conventional methods.

Common Machine Learning Tasks: Regression and Classification

Two fundamental tasks in machine learning are regression and classification. Regression predicts a continuous value, such as temperature, while classification categorizes data into discrete classes, such as weather conditions.

Let's consider a practical example. Suppose you're an engineer at a bearing company tasked with automatically identifying different parts. First, we generate a dataset by creating parametric models of various parts-housing, bearings, and bolts. Each part is labeled with a class index. Next, we extract geometric features from these models, such as volume, area, and dimensions, which serve as inputs for our machine-learning model. We generate multiple designs and corresponding feature datasets using Synera's design exploration capabilities.

After preparing the dataset, we move to the machine learning phase. Synera simplifies the process with pre-built nodes for model training and prediction. By connecting these nodes to our feature dataset, we train a classification model and use it to predict the class of new parts.

The Steps: Creating a Classification Model in Synera
  1. Generating the Dataset: We use parametric workflows to create diverse part designs and extract their geometric features.
  2. Training the Model: We preprocess the dataset, handle null values, and normalize the features. Using Synera's classification model node, we then train the model.
  3. Making Predictions: With the trained model, we classify new parts by extracting their features and feeding them into the prediction node.
Addressing Questions and Advanced Customization

During the demo, questions arose about handling null values and tuning hyperparameters. While our tool aims to simplify the process, advanced users can integrate custom scripts for more control over the models and hyperparameters. For instance, users can import their own (Python) scripts and automate optimization processes within Synera.

Synera's low-code platform offers engineers a powerful yet accessible way to integrate machine learning into their workflows. Whether automating classification tasks or exploring advanced regression models, our tool provides the flexibility and ease of use needed to drive innovation in CAD classification.

Discover the benefits yourself – Test Synera's Low-Code platform!

Would you like to experience the benefits of Connected Engineering and our Low-Code Platform firsthand? We invite you to test Synera's Low-Code Platform 14 days for free and discover how you can make your product development more efficient and agile. Experience the future of product development and explore the possibilities that our innovative solution offers. Click here to explore the Synera Low-Code Platform and optimize your development process for your use case today.


Or get a free demo from our CEO Daniel Siegel. Every first Tuesday of the month he will take you on a guided tour of our synera software. You will discover how to automate your workflow and how to speed up your development process. There will also be a Q&A session where you can ask all your burning questions. Register here for free.

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