circuits, and multi-layer circuits can be developed by combining
printing, coating, drilling, and VIA fabrication processes, Liou
says. The SAMMCERS process was originally applied to a
single substrate, but after further development, it can be used for
In addition to producing the circuit interconnections,
SAMMCERS system can be used to print resistors and
capacitors using commercial carbon and insulation paste, but
achieving consistent accuracy and stability remains challenging.
The system can also print organic light-emitting diodes (OLEDs)
onto the substrate. So far, the SAMMCERS process has only
been applied to producing discrete OLED devices (as opposed
to OLED displays).
In addition to serving as indicator lights in end products, the
printed OLED emitters are used by the manufacturing system’s
self-guidance mechanism to help optimize the outcome of each
product batch. According to ITRI, a time series operates on the
pilot line to prevent machine failure. This is comprised of alarm
prediction, failure time estimation by machine learning, and a
self-guidance mechanism. Before this real OLED light source
chamber excessive-temperature alarm occurs, SAMMCERS can
use previous patterns to predict subsequent temperature trends.
It can divide the pattern into different time points to predict this
alarm before it actually occurs and take preventative measures.
Since maintaining proper tension on the substrate is critical to
the SAMMCERS process, it uses ultra-fast sensors to monitor
the rolls in real-time and relay data to backend systems via cloud
computing for quick decisions on immediate adjustments. The
data generated by this process is also used by the system’s self-learning capabilities for better quality control.
SAMMCERS is designed to learn from the history data and
predict future production trends. “Our RD process is dynamic,
and we need to frequently change our materials because of our
research requirements,” Liou says. “So we created another [self-
learning] mechanism to dynamically adapt any new patterns and
make all these [things] into our computer program combining with
our alarm messenger system. By doing this, we can monitor our
production process even if it is dynamic.” Using these systems
to monitor and correct the manufacturing process in real-time
maximizes yields and minimizes work-in-process.
The flexible circuits produced by SAMMCERS are assembled
using a standard surface-mount technology assembly process.
The institute has developed its own low-temperature at less
than 150 degrees F for some cases. These low-temperature
processes are developed for plastic substrates like polyethylene
terephthalate (PET) and polyethylene naphthalate (PEN). The
temperature constraints depend upon the substrate properties.
The production method his applications in the industrial,
consumer electronics, and automotive industries. The process is
also used to make touch panels for a variety of end products like
lighting, solar cell energy storage, and optical film products, to
name a few.
“Increasingly intense competition in industry in recent years has
forced manufacturers to spare no effort in consideration smart
manufacturing processes to boost yields,” Liou says. “ITRI …
developed [SAMMCERS] to address this trend. SAMMCERS
reduces the number of defective products, which enables
manufacturers to achieve low-carbon manufacturing goals, with
emissions estimated to be cut by 50 percent, thereby creating a
more eco-friendly factory.”
Making a direct cost comparison between circuits produced
in a conventional manner and the SAMMCERS process can be
difficult because the savings depend upon the type of products
being made. But, for comparison’s sake, the material utilization for
touch panels can be improved from about less than 10 percent to
more than 90 percent using roll-to-roll direct printing, Liou says.
But what do designers who have worked specifically with
traditional roll-to-roll methods need to know before working with
the SAMMCERS system?
“The considerations are mainly in two aspects,” Liou says. “One
is resolution required for fabricating different modules. It might be
mm-level accuracy or μm-level accuracy. The other one is layer
number based on device structures. [The] high-resolution R2R
process involves technology innovations.” Machine learning predicts the machine failure to reduce downgraded or failed products.
SAMMCERS’s structure and key breakthroughs include device/process modeling,
real-time monitoring, analytic models, and self-guidance mechanisms.