STS-IAP10 Product Positioning
STS-IAP10 is an intelligent manufacturing execution and edge computing platform designed for Industry 4.0 environments. It integrates PLC control, edge computing, a low-code platform, data acquisition, predictive equipment maintenance, cloud-based visual analytics, energy management, network communications, device positioning, and security management, helping enterprises achieve the digitalization, visualization, and intelligent transformation of their production processes.
It can function as an industrial data hub that connects PLCs, sensors, controllers, production equipment, and other field-level units. It can also serve as a smart manufacturing platform that stores, analyzes, and models collected data to support decision-making. The platform is suitable for manufacturing, energy, transportation, the Internet of Things, edge computing, and other application scenarios.
Core Value
The core value of STS-IAP10 lies in connecting field equipment, edge computing, and upper-level management platforms to create an integrated closed loop—from data acquisition to intelligent analytics, from equipment operation to predictive maintenance, and from production management to safety and security control.
It helps enterprises address common problems in traditional production environments, including isolated data silos, limited visibility into equipment status, reliance on manual experience for maintenance, difficulty in managing energy consumption, complex network communications, and insufficient safety and security controls. This improves production efficiency, equipment reliability, operational management, and decision-making responsiveness.
Product Functions
1. PLC and Industrial Control Integration
STS-IAP10 supports PLC integration in industrial environments and is compatible with multiple industrial buses and communication methods. According to the product brochure, it supports PROFINET, EtherCAT, MODBUS, and other industrial bus protocols, as well as dual-system hot-standby redundancy for mid- to high-end industrial control applications.
This enables the platform to connect reliably to field control systems, providing the foundation for equipment data acquisition, production control, status monitoring, and subsequent intelligent analytics.
2. Intelligent Production Management
The platform provides digital and intelligent management of factory equipment, production lines, and production processes. By connecting sensors, controllers, PLCs, AR devices, cameras, RFID devices, and other equipment, it enables production process visualization, production plan optimization, production scheduling management, quality monitoring, and intelligent scheduling.
In production management, STS-IAP10 supports equipment self-monitoring, self-diagnosis, and automatic adjustment, helping enterprises extend equipment service life. It can also optimize production plans and resource scheduling based on order, inventory, logistics, and other data, thereby improving production efficiency.
3. Predictive Equipment Maintenance
STS-IAP10 provides predictive equipment maintenance capabilities covering the entire equipment lifecycle, including data acquisition, data cleansing, data analysis, model development, model training, model validation, fault prediction, maintenance recommendations, and model updates.
The platform can collect data such as temperature, pressure, vibration, current, and PLC operating data. Through big data analytics and machine learning models, it can predict potential equipment failures and provide maintenance recommendations in advance, reducing unexpected downtime and the workload associated with manual inspections.
4. Data Acquisition and Data Governance
The platform can acquire data from endpoint devices through OPC UA, MQTT, MODBUS-TCP, MODBUS-RTU, TCP, HTTP, and other communication methods, aggregating data from production equipment, sensors, PLCs, and other devices within the platform.
For data processing, the platform supports data cleansing, duplicate data removal, missing data imputation, outlier handling, data transformation, data normalization, and feature selection. These capabilities provide a more reliable data foundation for subsequent data analysis, fault prediction, and intelligent decision-making.
5. Data Analytics and Intelligent Modeling
STS-IAP10 supports descriptive, exploratory, and predictive analytics. It can be used to identify equipment operating patterns, analyze correlations among equipment failures, and predict equipment status and potential faults.
At the modeling level, the product brochure states that regression analysis, decision trees, random forests, K-nearest neighbors, fully connected neural networks, convolutional neural networks, recurrent neural networks, autoencoders, and LSTM models can be used for different types of data analysis and prediction tasks.
6. Cloud-Based Visual Analytics
The platform supports image recognition, object detection, facial analysis, scene understanding, image quality assessment, image search, video content analysis, and security monitoring.
In industrial environments, these capabilities can be applied to equipment inspections, quality inspections, abnormal behavior detection, personnel safety monitoring, and image-based defect detection. They help enterprises extend conventional data monitoring to intelligent image and video analysis.
7. Energy Management System
STS-IAP10 can monitor electricity, water, gas, and other forms of energy consumption in real time and optimize energy use through data analysis and predictive models.
The platform supports energy monitoring, energy optimization, energy management, report analysis, energy forecasting, energy consumption diagnostics, and solution generation. These capabilities help enterprises identify energy waste and inefficiencies, improve energy-use efficiency, and reduce operating costs.
8. Network Communication Capabilities
The platform supports 5G, NB-IoT, Industrial Ethernet, and other communication methods for industrial data transmission, remote monitoring, edge computing, and IoT device connectivity.
These communication capabilities are suitable for industrial automation, IoT applications, remote monitoring, and security monitoring. They improve device connectivity efficiency, data transmission reliability, and remote management capabilities.
9. Device Location and O&M Management
The platform can display the locations and distribution of edge computing modules and related devices. It supports device address and location visualization, fault location, network planning and optimization, as well as data analysis and decision support.
When a device or edge node fails, the platform can use location data to identify the affected area quickly, narrow the troubleshooting scope, and improve operation and maintenance response efficiency.
10. Security Management
STS-IAP10 supports access control, data encryption, security monitoring, vulnerability management, security training, and security auditing.
The platform can control the scope of user access through identity authentication and permission management. Encryption protects data during transmission and storage. Security monitoring identifies abnormal behavior, abnormal network traffic, and system log issues. Security auditing tracks operation records to improve overall system security.
Technical Specifications
The server configuration supports third-generation Intel Scalable processors, dual-socket PGA-4189, a maximum TDP of 270 W, UPI speeds of up to 11.2 GT/s, and up to 40 cores. It supports up to four double-width GPUs or six single-width GPUs. Memory capacity is 64 GB and expandable. Storage capacity is expandable up to 128 TB. The server uses redundant power supplies and supports Linux and Windows operating systems.
The network controller supports expandable Gigabit and 10-Gigabit interfaces. Computing capacity is expandable to 32T, with power consumption of approximately 2.1 kW and an AC 220 V power supply. It supports both IPv4 and IPv6.
For edge nodes, the product brochure indicates support for approximately 1,024 edge devices. Supported cloud types include public cloud, private cloud, and hybrid cloud. Application areas include AI, AI modeling, predictive equipment maintenance, big data analytics, cloud-based visual analytics, intelligent video, the Internet of Things, distributed applications, and edge device management.
