Plants and Machinery

DigitalTwin, application to avoid machine and plant downtime.


DigitalTwin, application to avoid machine and plant downtime.

DigitalTwin, applicazione no fermi macchina e impianti


Description:

Digital twins, or "digital twins", are virtual representations of machinery or physical systems that allow the simulation of their operation.

Unlike predictive analysis, through the use of advanced Generative Artificial Intelligence models appropriately trained on technical and design information, it is possible to carry out behavioral analyzes and "what-if" scenario simulations to understand how the machinery would react to different situations of malfunction and in general support the analysis and resolution of specific malfunction problems.

Methodology

In detail, the macro-project phases and the logical reference architecture:

.: Data Collection and Training: Begin by collecting a large dataset of technical drawings and information on their components and malfunctions. This dataset will be used to train artificial intelligence models.

.: Development of Artificial Vision Algorithms: Develop and optimize algorithms capable of recognizing and classifying mechatronic components in drawings, distinguishing between different categories and identifying their specifications.

.: Implementation of Machine Learning Models: Use Natural Language Processing (NLP) techniques to process user queries and deep learning models to correlate malfunction symptoms with possible causes and solutions.

.: Intuitive User Interface: Design a user interface that allows engineers and technicians to easily upload technical drawings, ask specific questions, and receive clear, detailed answers.


DigitalTwin, application to avoid machine and plant downtime. By AI_Garage.