An Easy-to-Use and Customizable Data Science Tool for Predictive Maintenance in Manufacturing

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Published Sep 4, 2023
Naoki Sugawara

Abstract

Even if many manufacturing companies have attempted to utilize data analytics for predictive maintenance but have not been able to do so. This is because predictive with data requires both knowledge of equipment in production site and knowledge of data science, and such workers are scarce. Another problem is that it takes time and effort to apply the created machine learning models on site and to develop applications for monitoring the diagnosis results.

Therefore, we developed “MELSOFT MaiLab”. The application has an intuitive interface and functions to automatically create machine learning models, making it possible for workers with no knowledge of data science to easily create machine learning models for predictive maintenance. The application also has functions for deploying the created machine learning models to the production site and monitoring the diagnostic results.

Abstract 93 | PDF Downloads 96

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Keywords

smart manufacturing system, predictive maintenance, facility maintenance, data science, AI

References
H2O.ai, 2023, H2O Driverless AI, https://h2o.ai/platform/ai-cloud/make/h2o-driverless-ai/

RapidMiner, 2023, RapidMiner | Amplify the Impact of Your People, Expertise & Data, https://rapidminer.com/
Section
Special Session Papers