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2024-03-21
AI: Powering the Engine of Tomorrow's Manufacturing Landscape
Shan
Wu, editor
In the journey towards digital transformation in manufacturing, AI (Artificial Intelligence) stands as an indispensable element. The utilization of AI trends to bolster Taiwan's manufacturing industry and foster international competitiveness is currently a focal point of attention.
Taiwan's industrial technological prowess has long held a significant position in global industry chains, spanning from information technology, consumer electronics, precision machinery, to the research and development of general consumer goods. It boasts abundant international competitive advantages. However, in recent years, factors such as the rise of emerging nations and political changes worldwide have led to the movement of global manufacturing sectors. Taiwan's previous model of mass production with low profit margins no longer serves as the most competitive profit model. For the manufacturing industry, quality, flexibility, and speed are now the keys to success. Through the integration of AI into manufacturing, achieving a mode of production characterized by small quantities and high diversity can enhance operational efficiency or service quality, thereby achieving transformation and upgrading.
Challenges for the manufacturing
industry are increasingly mounting Enterprises now
face the practical situation where customer demands shift from mass
customization to personalization, production methods transition from mass
customization to customization, production lines struggle to cope, and
scheduling flexibility must be increased. Economic visibility is low, making
demand prediction difficult. Capacity planning is not easy, leading to not only
labor shortages but also skill gaps due to technological advancements outpacing
existing employee capabilities. New employees lack experience, leading to a gap
between academia and industry, necessitating more in-house training. Equipment
is becoming increasingly precise and complex, resulting in higher costs for
failure and OEM repairs. Thus, the challenges facing the manufacturing industry
are growing.
AI empowers equipment with learning
capabilities
The
greatest help AI brings to manufacturing lies in predictive maintenance,enabling machine
equipment to have judgment capabilities akin to humans. Not only can it
automatically complete various manufacturing processes, but through the
training and learning of big data, it can also make judgments, predictions, and
take appropriate actions. Predictive diagnosis of manufacturing equipment is a
major advantage of AI in the manufacturing industry. Predictive diagnosis
should include equipment life cycles, part life cycles, maintenance and repair
management, decision support management, real-time operation monitoring, and
other systems. By collecting real-time data and utilizing AI learning
techniques to establish predictive models, unplanned failure losses can be
reduced, ensuring stable operation of production lines.
Improving yield
is a key indicator for reducing production costs and enhancing product quality.
Integrating AI algorithms to enhance process analysis techniques can optimize
product quality, rapidly predict product quality characteristics, effectively
shorten the R&D cycle, improve yield, and accelerate time to market.
Introducing AI enables equipment to have visual learning capabilities. When
encountering product defects, there is no longer a need for manual reinspection
or adjustment of judgment criteria.
Machine arms learning autonomously The challenges
of manufacturing with low variety and high-volume force manufacturers to
frequently change production line content. However, factory retooling relies on
time-consuming adjustments by professional engineers. Currently, with the
application of AI technology, machine arms can autonomously learn how to grip
and place objects. By combining machine arm simulation software, they can learn
autonomously in a simulated environment, thereby overcoming the bottleneck of
human adjustment of machine arms. AI enables line change tasks to be faster and
more flexible in responding to rapidly changing market demands. By 2025, 30% of
enterprises are expected to adopt generative AI. Currently, generative AI is
applied in business services, content creation, R&D, manufacturing, and
operations and supply chain management. In the future, Taiwan's manufacturing
industry is expected to seize opportunities in layout and entry under the
existing AI foundation, particularly in terms of AI technology, AI industry
development, and AI talent cultivation, to reduce costs, enhance enterprise
confidentiality, and thereby increase industrial competitiveness. More information on exhibitors for
intelligent and digital services:
CHUNG YI-
EZiFASS: https://www.tmts.tw/en/product/2194
HOLDING ELECTRIC- RFID for smart Tool
Management
https://www.tmts.tw/en/product/1710
LNC- Articulated Robot Controller: https://www.tmts.tw/en/product/1724
BLUM- LC50
Digilog: https://www.tmts.tw/en/product/1692
EVERMORE- Industrial Robotic Arm: https://www.tmts.tw/en/product/50
DOWELL- ESPRIT CAM:
https://www.tmts.tw/en/product/1459
YCM- NH500A - High Production 2-Pallet
Horizontal Machining Center: https://www.tmts.tw/en/product/923
Sources：ITRI / https://www.itri.org.tw/ListStyle.aspx?DisplayStyle=18_content&SiteID=1&MmmID=1036452026061075714&MGID=1035141040456274172
Taiwan International Machine Tool Show | March 4th - 7th, 2026
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