LS Electric

Assembly Line

LS ELECTRIC and Sight Machine Collaborate to Build AI-Based Big Data Analytics Platform for Manufacturing and Energy

đź“… Date:

đź”– Topics: Partnership

🏢 Organizations: LS Electric, Sight Machine


LS ELECTRIC announced on September 18 that it has signed an MOU with Sight Machine to build an AI-based intelligent manufacturing and energy big data analysis platform at LS ELECTRIC Cheongju, Chungbuk, Korea. With this MOU, the two companies plan to conduct extensive collaboration in the field of integrated platforms aimed at the ESG market, including verification and analysis of manufacturing-energy big data connectivity using Sight Machine’s Manufacturing Data Platform, prediction of AI-based manufacturing process equipment control values, and construction of big data analysis platforms to help companies achieve smart manufacturing and power efficiency in the production process.

Read more at Korea IT Times

LS Electric, Microsoft to jointly develop smart factory

đź“… Date:

đź”– Topics: Partnership

🏢 Organizations: LS Electric, Microsoft


LS Electric Co., South Korean manufacturer of power and industrial automation equipment, has signed a partnership agreement with Microsoft to develop intelligent and autonomous factory solutions.

Both companies will focus on improving data connectivity in intelligent factories, generating data insights for production facilities, and conducting power efficiency analysis in production lines. LS Electric and MS will also explore the use of Azure Synapse Analytics and Azure Machine Learning services for advanced manufacturing environments and the development of new business models based on smart energy and power data. The collaboration will extend beyond smart factories to encompass digital transformation (DX) businesses.

Last year, LS Electric worked with Microsoft to enhance inspection and noise analysis in the production line of the Cheongju plant, which was recognized as a “lighthouse factory” by the World Economic Forum. The partnership resulted in reduced defect rates and increased productivity through the use of deep learning technology on the Azure platform.

Read more at Korea Economic Daily