“AI
Impulse 2019: Catalyst to Business Succes” was organized by Hong Kong
Productivity Council (HKPC) on 17th - 18th Jun 2019. Artificial Intelligence (AI) is technology
that significantly enhances productivity and operation efficiency. There are two day event in which day 1 is
summit and day 2 is visit & AI workshop. I would like to summarize day 2 visit
to Foxconn and TCL on 18th Jun below. In the morning, we visited
Foxconn Industrial Internet Center.
The
Foxconn representative introduced their industrial internet platform named “BEACON
Industrial Cloud Platform”. They
employed six flow named People Flow (人員流),
Cash Flow (資金流), Tech Flow (技術流), Info Flow (信息流),
Process Flow (過程流) and Things Flow (物品流).
Some
demonstrated robot arms from packaging were showed.
Then
the “All-in-one Container Data Center” model was briefed and it was easy to
move and on-demand increment.
The
control center was visited.
After
that we walked outside to visit “All-in-one Container Data Center”.
Insider the Container, many service in both side and HFC-227ea Fire Suppression System (FM200) was observed at the end.
I took a photo insider for memory.
The
second location was Foxconn Agritech (http://www.foxconnagritech.com/
). I took a photo with the Foxconn boss
poster.
Why
Foxconn extended industrial technology into Agricultural field? It is because the flood disaster in 2009 in
Taiwan.
After that we visited the farm in which had twelve layers.
It
called i3 Farming.
I
also visited the demonstrated laboratory.
The
last location we visited was Intelligent Manufacturing – Lights off factory.
We
firstly visited the demonstration room for their products. We found that they used high technology to
develop tools and then through CNC to develop iPhone case.
We
visited one of Lights off factory and they performed automatically without
human operation.
Finished
the morning visit, we tasted Foxconn Agritech product during lunch. I took a photo with Ir. Eric MH Wong (Senior
Workshop Services Engineer, CLP) (middle) and Mr. CP Tsui (Managing Director,
Enterprise Consulting Limited) (right).
The
food and vegetable was very good.
Foxconn VP gave welcome speech to us during lunch.
The
second visit location was TCL and the factory named “China Star Optoelectronics
Technology Co., Ltd.” in which TCL owned 87%. So it seemed as TCL subsidiary.
I
took a photo in front of the CSOT for memory.
I
also meet Ms. Sheron Sit (Senior Manager, Advanced Manufacturing, HKSTP) and Mr.
Fung Wah Cheong, Vincent (Executive Director, Kin Yat Holdings Limited).
Firstly,
the representative introduced the development history of the factory.
The
glass product size was showed in the display panel.
The
center overview, major achievement and technical roadmap were briefed. And then we visited the factory but photo
taking was not allowed. It is a very
large factory with length 370m, wide 226m and the area was 83,000 m2 that was
equal to 12 football field! It operated
under class 1000 clean room.
Physical
vapor deposition (PVD) and Chemical vapor deposition (CVD) were employed for
glass coating and each machine cost 840,000 TWD. AI inspection was employed. After that we visited the product
demonstration room.
The largest TV in the world was showed.
The
monitoring scene for manufacturing was demonstrated.
I
observed the CNAS certificate.
Finally,
we went to the hall and Mr. Wang presented their intelligent manufacturing
practice.
CSOT
invested huge resource to build several factories in China.
Then
Mr. Wang told us their challenges included variety, short life cycle, high
standards, customization, high efficiency and low cost.
And
then he briefed four stages from automation / digitalization to IoT to Big Data
and to AI.
They
employed AI for self-classification.
Other
applications of AI in the factory were discussed such as label recognition,
face recognition, defect identification, etc.
Finally,
the whole value chain of smart manufacturing was showed and they named
Intelligent Brain.
During
Q&A, one of participants asked what is the most difficult for employing AI
and i4.0. Mr. Wang said we needed to
find the pain point first. Most department colleagues didn’t want to say they
had pain points because they afraid something wrong. We needed to guide them for improvement not
failure finding. Those pain points
should link with business. Another
difficulty was machines’ data collection.
Because the machine manufacturer didn’t disclose the data. Sometime we needed to add sensors for data
collection.
After
one day visit, we learnt a lot of advanced manufacturing and AI application. We
come back to Hong Kong through Shenzhen Bay Port.
Reference:
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