Service platform
core advantage
Order Tracking
Inquiry of Dies products, order generation and real-time tracking of production status and logistics status of related products in the order.
Dies Tracing Source
Collect dies usage management data, automatically generate dies resume and dies life cycle
Life Management
Data collection is carried out according to the customer's usage scenarios, and the platform automatically calculates the remaining life of the dies, gives early warning to the over-life production tasks, and guarantees the product yield
Productivity Analysis
The actual check of production order and dies capacity is realized through modeling and analysis of production data such as molding cycle and opening probability
Dies Life Cycle Services
Dies service life cycle is a large enterprise relies on refined shared dies asset management solutions,combined soft ware and hard ware, including data acquisition, man-machine interaction as one of the intelligent terminal equipment, large data IoT platform is responsible for data display and analysis, automatic counting, accurate positioning IoT assets, high degree of automation, the dies management combined with the production data, provide big data support for production decisions.
Enhance Enterprise Delivery Capability
To ensure the production plan as the goal, related production orders, assigned work plan tasks according to predetermined conditions, predicted future capacity load in advance, improved capacity and resource utilization rate, quickly and effectively responded to the needs of different scenarios, and helped enterprises to improve delivery capacity.
Business Case
Traditional Dies Management Challenges:
1. Extensive management relies on manual labor, resulting in reduced timeliness and accuracy.
2. The production schedule cannot be obtained in time.
3. The manual statistics of production quantity, qualified rate and production cycle data can not stand scrutiny.
IoT mold management scenario
1. Transparent dies production data, high timeliness and accuracy.
2. Monitor the production progress in time to avoid the wrong or missing delivery.
3. Obtain true and complete dies history and one-day production information through the platform, with accurate data.
Business Case
Traditional Dies Management Challenges:
1. Relying on the statistical information of traditional manual reports results in poor accuracy and high labor cost.
2. The loss of report data is difficult to trace, and the loss of historical data cannot be made up.
IoT Dies Management Scenario:
1. Through digital production data management, it can automatically generate reports and give automatic warning of dies life and dies position abnormality.
2. The platform data is ready-to-use, safe and reliable, and can be traced back to the whole life cycle of the dies.