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ASUS expands into smart manufacturing solutions
- June 16, 2020
ASUS is expanding its AI and IoT business unit to focus on smart manufacturing and Industry 4.0. The Taiwanese computing and telecoms equipment maker has established a new business group within its organisation, which will be devoted to the development of smart manufacturing technologies. The new business group will develop industrial solutions based on the integration of AI with IoT technologies. The new AIoT group is the fourth major division in the company, after telecoms, computers, and components.
The new group will combine cloud, edge, mini, workstation, and industrial motherboard platforms, as well as solutions. The AIoT group will offer solutions that build on ASUS’s own experience in implementing AI and IoT in its own manufacturing plants. In particular, it will develop new manufacturing processes supported by AI and big data that reduce defects that can go unnoticed by human inspection.
By investing in smart manufacturing solutions that use AI for producing metal peripherals, fans, printed circuit boards and other computer components as well as for system assembly, ASUS was able to remove efficiency bottlenecks and reduce losses resulting from misjudgement of manufacturing defects by factory employees.
In the future, ASUS says that it will use artificial intelligence and big data to statistically classify different types of quality defects, determine their causes and improve processes at the source of defects to further improve and push the boundaries of manufacturing quality.
“ASUS currently has hundreds of suppliers, and whenever we are able to improve quality-inspection processes, suppliers are receptive and willing to make changes,” said Jackie Hsu, Senior Vice President, Co-Head of Open Platform BG and AIoT Business Group said. “This is a win-win situation for ASUS and the entire industry, which has always attached great importance to product quality.”
Optical inspection is one of the core technologies of AIoT Business Group, which uses machine learning, deep learning and artificial neural network technologies to train the AI detection model correctly. “Automatic optical inspection accuracy in general is about 80–90 percent, which means that more than 10 percent of defects may be misjudged, and manual visual inspection accuracy is about 90 percent,” said Albert Chang, Corporate Vice President, Co-Head of AIoT Business Group. “At present, ASUS has enabled AI to greatly improve its accuracy to 98 percent after learning.”
Fans are a key part of many computers and consumer electronics, cooling components and helping to extend product life. To ensure fan quality, manufacturers relied on inspectors who were able to detect problems with fans just by listening to them. Training highly skilled personnel for this important position took from three to six months, and inspectors would occasionally experience short- or long-term ear fatigue and other occupational factors that negatively impacted worker health and reduced the problem detection rate.
To solve this problem, ASUS introduced the AI Wave Signature System, which analysed the sounds of correctly operating fans and used them to develop a sound signature. This sound signature was then used to train AI models to quickly identify high-quality fans. The AI Wave Signature System can be combined with testing of a product’s electric current, voltage, vibration and other characteristics during inspection to ensure overall product quality. Additionally, the system can be applied to monitor production equipment in real-time to avoid factory downtime. For example, by monitoring equipment motors in the factory using the AI Wave Signature System, operators will be notified immediately if a motor begins behaving abnormally. The motor can then be repaired before it fails completely, avoiding production halts and accompanying losses.
“The original intention and top priority of the business group is to promote common upgrades in the industry and assist the improvement of the supply chain to face international competition and continue to accumulate experience,” said Jackie Hsu, Senior Vice President and Co-Head of the Open Platform and AIoT business groups.
Commenting on the introduction of smart manufacturing and AI detection solutions by major factories, Albert Chang, Corporate Vice President and Co-Head of the AIoT business group said, “In the past, AI algorithms and models were highly customised, improving the potential for AI detection solutions. Reproducibility is the goal of the next stage, enabling quick popularisation and adoption along with scalability. Finally, the ultimate vision of the ASUS AIoT business group is to focus on ‘full quality analysis.'”
The target of ASUS AIoT for the next three to five years will be data analysis. By investigating causes of defects, assisting the supply chain to find fundamental solutions for high yields, creating a formula for success, and accumulating long-term value, data analysis will become an important pillar of the ASUS brand.