From the center
of production,
digital transformation
To achieve autonomous manufacturing in the sewing industry, we are transforming the center of production to digital.
Production monitoring IoT system
Real-Time
Production Monitoring
Monolog is a network of things (IoT) device leading the digitalization of clothing manufacturing. By analyzing patterns of sewing work, we produce tens of millions of pieces of process data per day.
By collecting work patterns with various variables in the sewing field, transform them into quantifiable digital data.
Data Collection
Dataization of sewing
machine work
Data is extracted from the point where humans and machines meet. By stepping on the pedal and vibrating the machine, the sewing work is analyzed in detail by separating the time the machine was moving and the time the fabric was cleaned.
Real-Time Monitoring
Data visualization
It calculates data in real time and visualizes the exact amount of production.Bottleneck processes can be identified immediately through Andon andKanban installed at each field plant.
Andon
Production Traffic Lights
By installing a lamp on site that indicates real-time production volume for each process, immediate confirmation is possible when a problem occurs.
Kanban
Real-time Monitoring
Electronic signboard system using real-time production data
Volume, Variety, Velocity, Varacity
Quickly and accurately collects vast amounts of data and diverse variables from the field. Tens of millions of process data points are generated daily without altering the behavior of sewing workers.Using Victor Eater, data is calculated in real time to visualize and display accurate production status.
Industrial digital transformation requires a neural network that connects the real and virtual realms.
SMV
Standard work time:
Time focused on production
Efficiency
Production efficiency:
Standard time tolerance
Loss Rate
Non-productive time:
Time wasted during work hours
Production Efficiency
We carry out effective improvement activities to increase production efficiency using data. By quantifying estimated efficiencies, you can establish strategies to increase efficiency for each process, line, and factory.
Transmitted data is provided as real-time indicators so that problems can be resolved immediately through on-site monitoring.
The data analyzing the actual production time is saved in the DB and becomes Monolis's process analysis data.
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