Product Assurance Runtime

The Product Assurance Runtime component focuses on ensuring product quality through data obtained in the manufacturing process and quality inspections. It consists of two tasks: Product Quality Prediction and Product Quality Supervision, both utilizing AI and Big Data techniques. This documentation specifically covers the Quality Prediction Designer, which allows the design and training of machine learning models for predicting product quality. The component integrates machine learning libraries and analytical tools to prepare and select trained models.


  • Dataset management

  • Friendly user interface to train and optimize a model

  • Experiments tracking

  • Visualization tools to analyse the model

  • Save results from experiments

  • Export the model for run-time prediction

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Product Quality Prediction Task

  • Objective: Provide real-time predictions of product quality variables in a manufacturing process using Machine Learning Models and Big Data techniques.
  • Function: Predicts product quality variables through the integration of a ML engine and the Quality Prediction Designer web UI.

Training Component

  • Purpose: Build and train Machine Learning models for product quality prediction.
    • Data Manager and Pre-processing
    • Model Configuration and Run Experiment
    • Analysis Tools

Inference Component

  • Objective: Use trained models to make predictions in real-time scenarios.
  • Process: Export the trained model as a archive, upload it using the Model Deployment Manager sub-component, and deploy it through the AI Analytics Runtime component.

Model Deployment Manager

  • Function: Manage the deployment of trained models by handling the upload and integration process.
  • Role: Allows users to export and deploy trained models for making predictions in real-time scenarios within the AI Analytics Runtime component.

Additional resources

Learn more about i4FS by visting the project website for general information, the wiki for information about the core components, the Technical Manual for API documentation, and downloading the repository’s source code.

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Source code

Our source code is opensource and available on our Gitlab repository.

Software Documentation

Read our easy to follow documentation to learn how to use the i4 Components.

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