IoT Solution J-WiSe®
J-WiSe® is a general term for IoT solutions developed by us.
With four pillars (Production management, Service / Maintenance, Production support, Production automation system) for injection molding machines, we aim to provide solutions that contribute to customer productivity improvement.
J-WiSe® : JSW Worldwide IoT Solutions of Enhancement
NET100【Production Management】
It "visualize" the problems (alarms, stopped states) that occur daily in the molding factory, and support problem solving based on quantitative data.
"Visualization" of operation
By analyzing the cause of the decrease in the operating rate from the operating history and making fundamental defect improvements, the equipment operating rate can be increased.
Stabilization of molding quality
By analyzing the measured value data, the stability of molding is evaluated and the optimization of conditions is assisted.
NET100 function example
・Molding data collection
・Molding data analysis
・Operation status collection
・Remote console
Production Manager【Production Management】
By accumulating and analyzing production schedule and actual data, it identify issues in production and support the formulation of more efficient production plans.
Accumulation and management of molding process information
It is possible to manage the production schedule and actual results of the molding machine in an integrated.
Automation of management
It can create work order and result reports for molding sites from production schedule and result data.
Production Manager function example
・Operation status collection
・Order registration
・Production plan
・Work instructions
・Production performance management
・Data link to Upper System
・Work report
・Inspection result report
Team Network PLC Communication【Production Automation Systems】
The PLC communication function cooperates with automatic machines and peripheral devices to support the automation of production.
Digitalization to operation record
By converting the operation record management to digital data, it becomes easier to analyze the operation rate etc.
Efficiency of production setup
Peripheral device can be set automatically at the same time as the molding conditions are loaded on the molding machine controller screen, which contributes to shortening the setup time.
Team Network function example
・Modbus communication
・Serial communication
・PLC communication
・I/O signal output
Team Network OPC UA Communication Server Function
【Production Automation Systems】
By complying with international communication standards, it accelerates the transformation of smart factories further.
Regardless of the molding machine manufacturer, unified data collection and management is possible
For MES (Manufacturing Execution System) that supports OPC UA communication, this function provides some of the items specified in OPC 40083 and OPC 40077, as well as JSW's own extended items consisting of molding condition settings and measurement values for each molding cycle.
As a result, it is possible to manage production lines with a mixture of molding machines from different manufacturers using the same communication protocol, making it easier to build a customer’s system.
As a result, it is possible to manage production lines with a mixture of molding machines from different manufacturers using the same communication protocol, making it easier to build a customer’s system.
Integration with PLCs and no-code/low-code development platforms
Molding machine information can be easily imported into PLCs and no-code/low-code development platforms that support OPC UA communication.
This allows you to create your own dashboard display and quality analysis systems.
This allows you to create your own dashboard display and quality analysis systems.
Main communication items
・Machine Status
・Number of Shots
・Molding condition setting value
・Measurements per shot
AI Molding Navigator【Operation support】 [In Preparation for sale]
automatically correct molding conditions and keep good molding before molding defects occur due to changes in the environment, variations in material lots, aging deterioration of parts, etc.
Features of the system
Molding defects that can be detected and corrected by molding conditions are automatically corrected by our unique AI algorithm (reinforcement learning).
Our J-AD and J-ADS series machines can be applied to existing machines.
Our J-AD and J-ADS series machines can be applied to existing machines.
Expected effects
・Improvement of production yield by reducing defective rate.
・Reduction of downtime to fix molding defects.
・Labor saving by increasing the number of managing molding
machines per operator.
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