An LG Chem employee takes a seminar on an artificial intelligence analytic platform in this undated promotional photo. Courtesy of LG Chem
LG Chem is accelerating a company-wide transformation into artificial intelligence (AI), applying it across manufacturing and nonmanufacturing operations to improve customer value and operational efficiency.
As part of its AI transformation strategy, the company is using AI to overhaul workforce development, introducing a new AI-powered career development system that analyzes individual competencies. Employees can assess required capabilities for their roles and receive curated learning resources and execution plans based on AI insights.
In legal operations, LG Chem has implemented an AI contract review solution that automatically analyzes agreements against standard templates and internal compliance rules. It reduces contract processing time by up to 30 percent, the company said.
Across its workflow systems, the company is leveraging various AI tools, including a chatbot integrated with its own systems and translators that can handle up to 24 languages.
LG Chem has launched a company-wide AI analytics solution, called citizen data scientist, to enable employees without analytics expertise to generate insights using their own data. In a three-month pilot involving about 40 employees, more than 20 projects were made with the platform.
AI is also driving tangible improvements in product performance. The company has successfully used AI to predict material properties and optimize absorption rates in superabsorbent polymers, a key material used in hygiene products such as diapers.
On the manufacturing side, LG Chem is deploying digital twin technology that replicates real-world machines and systems in a virtual environment to predict equipment anomalies in advance.
At its Yeosu plant in South Jeolla Province, the company is integrating its manufacturing processes with the Internet of Things, AI and big data. It recently implemented a deep learning-based image analysis system that detects anomalies in flare stacks to safely burn off by-products generated during production.
AI is also used in product quality inspection, where AI analyzes images captured by inspection systems to automatically detect contaminants to improve efficiency and quality consistency.
Source: Korea Times News
