LG Innotek Becomes Industry's First to Use AI to Prevent Input of Defective Raw Materials in Production
Tuesday, October 15, 2024
-- Achieved early detection of cause of defects in raw materials through
AI, becoming "first to overcome this challenge in the industry"
-- Applied to high-value semiconductor substrates, analyzing raw material
defects in only one minute
-- Reduces defect analysis time by up to 90%
SEOUL, South Korea, Oct. 7, 2024 /PRNewswire/ -- Today, LG Innotek (CEO Moon Hyuksoo) announced the development and application of the industry's first "Artificial Intelligence (AI)-based inspection system for incoming raw materials", designed to detect defects at the point of receipt and prevent the use of substandard raw materials in the process.
LG Innotek applied its AI-based inspection technology, developed by combining material information and AI image processing technologies, to the RF-SiP (Radio Frequency System-in-Package) process. Recently, the technology was also introduced for the FC-BGA (Flip Chip Ball Grid Array), and is expected to further enhance the competitiveness and quality of LG Innotek's high-value semiconductor substrate products.
Previously, incoming raw materials underwent only a visual inspection before entering the production process. However, the continued advancement of semiconductor substrate technology changed this. Even after improving all in-process defect causes, failures in reliability evaluations continued to rise. This led the quality of incoming materials to gain attention as a decisive factor affecting reliability evaluations.
The core raw materials (i.e. Prepreg (PPG), Ajinomoto Build-up Film (ABF), and Copper-Clad Laminate (CCL)) that comprise semiconductor substrates arrive as a mixture of glass fibers, inorganic compounds, and other components. In the past, air voids (gaps between particles) or foreign particles generated during the material mixing process did not significantly impact product performance. However, as substrate specifications, such as circuit spacing, have become increasingly stringent, the presence of air voids and foreign particles, depending on their size, has started to cause defects.
As a result, it is virtually impossible to identify which part of the raw material is responsible for the defect using traditional visual inspection methods, which has become a significant challenge for the industry.
If we were to compare one lot of raw materials mixture (unit of raw materials with the same characteristics that goes into the production process) to a batch of cookie dough, it is impossible for the eye to perceive the concentration of salt or sugar in a certain portion, the number of air holes in the dough, or the number of foreign particles.
LG Innotek has found a way to overcome this industry challenge with AI. Its "AI-based Inspection System for Incoming Raw Materials" has been trained with tens of thousands of pieces of data on the composition of materials that are either suitable or unsuitable for a product. Based on this, it analyzes the components and defective areas of semiconductor substrate raw materials in only one minute, with an accuracy rate of over 90%, and visualizes quality deviations in each lot of raw materials.
By using AI machine learning to visualize, quantify, and standardize material configurations optimized for quality, LG Innotek has been able to prevent defective raw materials from entering the production process. The company can change the material design based on the quality deviation information visualized by the AI system, allowing it to ensure that the quality of the raw materials lot is uniform at a suitable level before entering the process.
An LG Innotek official commented, "With the "AI-based Inspection System for Incoming Raw Materials", the time required to analyze defects has been decreased by up to 90%, and the cost of resolving the causes of defects has been significantly reduced."
LG Innotek plans to enhance the AI system's detection capabilities by sharing raw materials-related data with customers and suppliers in the substrate sector through digital partnerships.
Additionally, the company aims to expand the system's application to optical solutions, such as camera modules, where the image-based detection of material defects can play a crucial role.
LG Innotek CTO S.David Roh said, "With the "AI-based inspection system", we will complete LG Innotek's unique AI ecosystem, which delivers exceptional customer value by identifying causes of product defects early in the production process." He added, "We will continue innovating in digital production technology to create top-quality products at the lowest cost and in the shortest time."
View original content to download multimedia:https://www.prnewswire.com/news-releases/lg-innotek-becomes-industrys-first-to-use-ai-to-prevent-input-of-defective-raw-materials-in-production-302268523.html
SOURCE LG Innotek
|
|
|
|
|
 |
4BY4 to Showcase AI Video Solution 'PIXELL' at NAB 2025 with 8K Association | Mar 28, 2025
|
|
Halfpricesoft.com Launches ez1095 ACA Software: Streamline 1095 Efiling | Mar 28, 2025
|
|
SonicWall's Zero Trust Network Access (ZTNA) Solutions Driving Success Tackling 2025's Biggest Cybersecurity Challenges | Mar 28, 2025
|
|
Innovative Control Systems Introduces New AI-Powered License-Plate Recognition Solution | Mar 28, 2025
|
|
AI Demand Fuels Server and Storage Component Revenues to Record $244 Billion in 2024, According to Dell'Oro Group | Mar 28, 2025
|
|
TerraMaster Launches D4-320U Ultra-Short 4-Bay Rackmount USB3.2 10Gbps Expansion Enclosure, Enabling Easy Expansion for NAS and Servers | Mar 28, 2025
|
|
QuickLogic Announces the Amendment and Extension of Credit Facility | Mar 28, 2025
|
|
Crypto4A Technologies Submits PQC-Capable QASM for FIPS 140-3 Level 3 Certification | Mar 28, 2025
|
|
365 Retail Markets Unveils Refreshed 365Pay App, Enhancing User Experience and Streamlining Operations | Mar 28, 2025
|
|
Introducing PDW SIM, a Next-Generation Flight Simulator for Tactical Small Unmanned Aircraft Systems | Mar 28, 2025
|
|
|
