Motor Performance Prediction Using AI Data Analytics｜Knowledge Studio

Software used : Knowledge Studio、 Rapid Miner 

【 Background 】

       The customer is a motor manufacturer. To reduce the time spent on product design modifications, they hope to use AI data analytics tools to transform a large amount of valuable historical design data into a tool that can predict the performance of the next new design, while continuously accumulating design experience and know-how.
       Based on this, Richin used the motor-related data provided by the customer to build an AI big-data prediction model, enabling rapid prediction of motor-related performance.

【 Results 】

• The AI model trained with big data can accurately predict motor performance, including temperature, torque, structural strength, etc., thereby accelerating the development process of new products.

• By using AI to analyze the motor big-data database, engineers can quickly understand the relationship between motor structure and performance from the analysis results, and in turn accumulate design experience.

【 Technical Features 】

• Using AI machine learning methods to quickly organize, summarize, and cluster the data reduces the time spent on data preparation, allowing engineers to spend more time on further analysis and research.

• Knowledge Studio provides a no-code and visual user interface, so that engineers without programming or data science backgrounds can quickly get started and use machine learning methods such as automated machine learning, deep learning, decision trees, and clustering analysis, allowing AI big-data tools to greatly accelerate their work.

【 Youtube – Technical Deep Dive 】