AIOT - KORISDA

With the development of automation, many enterprises are increasingly facing challenges from equipment management.

We hope to reduce downtime...

30%
Reduce unnecessary maintenance behaviors

70%
Existing regular maintenance saves time
We need to extract greater value from data...

82%
Equipment failures occur randomly

99%
Data collected from device sensors is not utilized
We are losing our most experienced employees...

30%
The workforce is facing retirement

37%
Average labor conversion rate

We use powerful AIOT technology to help customers solve problems

Equipment Management EAM

Asset monitoring, preventive maintenance to reduce downtime losses.
Equipment data collection

Supports devices with a scale of millions, only requiring linear expansion of servers
Equipment Health Management

360 ° health management of devices, pre-set AI models for monitoring device health
Predictive equipment maintenance

Real-time equipment characteristic parameters calculation, persist daily databases, historical databases, and alarm databases generation
Digital-twin of equipment

Establish a 3D model of the equipment, obtain the change pattern of equipment status, and predict the development trend of equipment operation.
AR intelligent operation and maintenance

Realize remote collaboration/digital virtual factory, quickly and efficiently complete operation and maintenance tasks.

We use AI technology to help customers solve device management problems

By monitoring the real-time operation status of the equipment and using algorithms to predict possible failures, measures can be taken in advance to prevent unexpected shutdowns.

Analyze historical maintenance records and equipment performance data, accurately identify vulnerable components, and implement targeted maintenance to reduce maintenance costs.

Apply advanced data analysis techniques to evaluate the health status of equipment, develop scientific and reasonable maintenance strategies, and effectively extend the service life of equipment.

Implement full process quality monitoring, optimize production process parameter settings using predictive models, and ensure stable improvement of product quality.

Seamless integration of generative AI and AIOT

Rich pre trained models

Pre built support for models such as GpT, VT/MAE, BERT, BLOOM, LaMA, GLM, etc;
Support TB level recommendation models.
High performance deployment

Support distributed and incremental inference for billions of models, with an average performance of 30ms/token;
Support multiple optimization features: automatic parallelism, graph optimization, incremental inference, distributed inference, AOE optimization, and multilingual interfaces.
Rich Northbound Domain Suite

Integrate mainstream SOTA models, easy-to-use data/model interfaces, out of the box:
By utilizing key technologies such as A+M affinity training strategy, mixed precision, and data sinking, the accuracy of key models in NLP, OCR, CV, and other fields is leading.

Customer Cases

Shenyang Min IoT Integration Platform

Project benefits:

Effectively improve the production efficiency of the production line;

Effectively improve product qualification rate and reduce overall costs;

Reduce equipment maintenance costs;

Reduce equipment failure rate and improve equipment integrity rate.

Business pain points:

Unclear management of equipment assets;

Inadequate timely maintenance of equipment poses a potential risk of malfunction;

The equipment status cannot be obtained in real time, and the effectiveness of equipment operation is difficult to guarantee, which poses uncontrollable risks to production progress and quality control;

Solution:

We provide end-to-end digital transformation IoT integration services, which combine intelligent devices with intelligent management software and big data analysis systems to achieve efficient information transmission, machine monitoring and diagnosis, big data analysis and decision-making, intelligent control of production lines, intelligent operation and maintenance of equipment, predictive maintenance of equipment, visualization, and more in all aspects of intelligent manufacturing.

Guangqi New Energy

Project benefits:

Reduce equipment failure rate and improve equipment integrity rate; Preventive maintenance: Improve equipment availability;

Predictive maintenance: reduce spare parts consumption;

Reduce equipment downtime and improve resource utilization.

Business pain points:

Unable to execute maintenance plans based on equipment conditions and supplier recommendations;

Unable to correlate and predict the actual production situation;

Inspection is based on manual paper-based management.

Solution:

The Internet of Things (IoT) platform promotes the close integration of IT and OT, from consulting and design to technology and services, providing end-to-end digital transformation IoT integration services. Through the combination of intelligent devices and management software, and then to big data analysis systems, it achieves efficient information transmission, machine monitoring and diagnosis, big data analysis and decision-making, intelligent control of production lines, intelligent operation and maintenance of equipment, predictive maintenance of equipment, and visualization in all aspects of intelligent manufacturing.