Solution

Information

Enterprise

Information

Solution

Enterprise

Solution

Information

Enterprise

Monolog

To achieve the autonomous manufacturing of the sewing industry, we are transitioning to digital from the core of production.

Monolog

To achieve the autonomous manufacturing of the sewing industry, we are transitioning to digital from the core of production.

Monolog

To achieve the autonomous manufacturing of the sewing industry, we are transitioning to digital from the core of production.

Pressing the red button in every time it's compeleted will update the production quantity and average SMV in real time.

Pressing the red button in every time it's compelted will update the production quantity and average SMV in real time.

Productivity can be measured accurately by collecting 30 vibration datas per second of sewing machines while production.

Productivity can be measured accurately by collecting 30 vibration datas per second of sewing machines while production.

As using of batteries, it can reliably be collected data without any issue, even if there's a power outage at the factory or internet disconnects.

As using of batteries, it can reliably be collected data without any issue, even if there's a power outage at the factory or internet disconnects.

How the vibration of the sewing machine becomes data

Collecting Micro-vibrations on Site

Collecting Micro-vibrations on Site

Collection Production Vibration Data at Sewing machine

Collection Production Vibration Data at Sewing machine

Fine vibration + Production vibration

Fine vibration + Production vibration

Actual usage example

Industrial digital transformation requires a neural network that connects the physical area and the virtual area.

SIJE constructs a neural network of information that can be utilized in MES, ERP (Level 4, 5) for the current status of the factory (Level 1).

SIJE constructs a neural network of information that can be utilized in MES, ERP (Level 4, 5) for the current status of the factory (Level 1).

Digital
Neural Network Area

Level 1

Level 1

Field Device Status in the Factory

Field Device Status in the Factory

Import, Inspection, Cutting, Production, QC, Trimming, Export

Level 2

Level 2

Control Network Information Collection

Control Network Information Collection

RTU, PLC, Communication protocols, Parameter control

Level 3

Level 3

Process Network Information Transmission

Process Network Information Transmission

Database Management (SCADA, KANBAN)

Level 4

Manage & Operate Production Execution

MES

Level 4

Manage & Operate Production Execution

MES

Level 4

Manage & Operate Production Execution

MES

Level 5

Corporation System Resource Management

ERP

Level 5

Corporation System Resource Management

ERP

Level 5

Corporation System Resource Management

ERP

SMV calculated through vibration data, Production efficiency, Loss rate

SMV calculated through vibration data, Production efficiency, Loss rate

1

1

SMV

SMV

Standard Working Hours: Time dedicated to production

2

2

Efficiency

Efficiency

Productivity: Allowable time for standard time

3

3

Loss Rate

Loss Rate

Non-production time: Wasted time during working hours

  • Through data parsing (Parsing), we quickly find SMV.

  • Derive SMV from numerous cycle times performed in a single process.

  • Analyzed SMV compares actual production cycle time in real time.

  • Through data parsing (Parsing), we quickly find SMV.

  • Derive SMV from numerous cycle times performed in a single process.

  • Analyzed SMV compares actual production cycle time in real time.

Use data to make effective improvements to increase production efficiency. By quantifying estimated efficiencies, you can create process, line, and plant-specific efficiency improvement strategies.

We carry out effective improvement activities to increase production efficiency with data. By quantifying the approximate efficiency, we can establish efficiency improvement strategies for processes, lines, and plants.

Analysis of work patterns

Notify when abnormal patterns occur using repetitive patterns

Line Balancing

Indicate the imbalance of work balance per process

1

2

3

4

5

6

1

2

3

4

5

6

1

2

3

4

5

6

Individual management of worker

Human resource management as a quantitative measure of workers' productivity skills

The data sent is provided as real-time indicators through on-site monitoring to immediately solve the issues.

The analized data of the actual production time is stored in the database and it becomes Monolis' process analysis data.

Company name

Sije

Customer Service

+82(0)2-1644-4386

E-mail

sije@sijecorp.com

Address

Main Office: 12, Gaetbeol-ro, Yeonsu-gu, Incheon, Republic of Korea
R&D Center: 14-6, Teheran-ro 78-gil, Gangnam-gu, Seoul, Republic of Korea

CEO: Shin In Jun Business Registration No: 444-88-02133

Copyright© 2024, Sije. All right reserved.

+82(0)2-1644-4386

sije@sijecorp.com

Main Office

12, Gaetbeol-ro, Yeonsu-gu, Incheon, Republic of Korea

R&D Center

14-6, Teheran-ro 78-gil, Gangnam-gu, Seoul, Republic of Korea

CEO : Shin In Jun

Business Registration No : 444-88-02133

Copyright © 2024, Sije. All rights reserved.

Company name

Sije

Customer Service

+82(0)2-1644-4386

E-mail

sije@sijecorp.com

Address

Main Office: 12, Gaetbeol-ro, Yeonsu-gu, Incheon, Republic of Korea
R&D Center: 14-6, Teheran-ro 78-gil, Gangnam-gu, Seoul, Republic of Korea

CEO: Shin In Jun Business Registration No: 444-88-02133

Copyright© 2024, Sije. All right reserved.