The growing adoption of digital
technologies such as industrial Internet
of Things (IoT), autonomous robots,
and big data analytics, are all part of
the fourth industrial revolution and
are the primary driving factors for the
growth of smart manufacturing. As
part of the industrial IoT, machines
with connectivity and integrated with
automation systems are critical. SEYI
has developed our Smart Stamping
Solution with the foundation of smart
machinery to help customers further
realise smart production and smart
management based on their needs.
Utilising a central control system
deployed through the press line via
IoT, all the data on the conditions
of the presses and peripherals can
be collected and organised in the
database. Additionally, tonnage
monitoring, die protection, the status of
motors, temperature, lubrication, and
power consumption can all be traced.
This automatic monitoring reduces the
likelihood of human error. Using remote
diagnosis or an after-sales application,
service troubleshooting can be less
time-consuming and less expensive,
whilst improving production efficiency.
Furthermore, the system is able to
generate multiple reports, such as
Overall Equipment Effectiveness
(OEE) and yield rate, allowing the
management team to compare actual
data with planning. This can help
users move toward a more accurate
decision-making process and optimise
production scheduling.
The growing adoption of digital
technologies such as industrial Internet
of Things (IoT), autonomous robots,
and big data analytics, are all part of
the fourth industrial revolution and
are the primary driving factors for the
growth of smart manufacturing. As
part of the industrial IoT, machines
with connectivity and integrated with
automation systems are critical. SEYI
has developed our Smart Stamping
Solution with the foundation of smart
machinery to help customers further
realise smart production and smart
management based on their needs.
Utilising a central control system
deployed through the press line via
IoT, all the data on the conditions
of the presses and peripherals can
be collected and organised in the
database. Additionally, tonnage
monitoring, die protection, the status of
motors, temperature, lubrication, and
power consumption can all be traced.
This automatic monitoring reduces the
likelihood of human error. Using remote
diagnosis or an after-sales application,
service troubleshooting can be less
time-consuming and less expensive,
whilst improving production efficiency.
Furthermore, the system is able to
generate multiple reports, such as
Overall Equipment Effectiveness
(OEE) and yield rate, allowing the
management team to compare actual
data with planning. This can help
users move toward a more accurate
decision-making process and optimise
production scheduling.
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