Industrial Data Acquisition and Visual Analysis Based on IMS Edge Computing Gateway

1、 Programme background
The traditional factory equipment data is scattered and isolated, relying on manual inspection and paper records, resulting in delayed operation and maintenance response, opaque production efficiency, and lack of data support for decision-making. Through the integration of Ames edge computing gateway and cloud platform technology, the real-time collection of equipment data - edge computing - cloud analysis - visual presentation is realized, and the factory is transformed to digital and intelligent.

2、 Core function module
Industrial equipment data acquisition

Multi protocol compatibility: connect PLC, CNC machine tools, sensors and other equipment through the RS485/Ethernet/DI interface of Ames Gateway, and support industrial protocols such as Modbus, OPC UA, Profinet, etc.

High frequency acquisition: millisecond level acquisition of equipment operating parameters (such as temperature, vibration, current), production count, fault code, etc.

Edge computing and data standardization

Local pre-processing: complete data filtering, outlier elimination and timestamp alignment in the gateway to reduce cloud load.

Protocol conversion: unifies heterogeneous device data into MQTT/HTTP format for cloud integration.

Edge alarm: real-time computing equipment OEE (comprehensive efficiency) and local audible and visual alarm will be triggered immediately when the energy consumption exceeds the standard.

Data cloud management and analysis

Dual channel upload: data is synchronized to the workshop board (low latency) and the group cloud platform (long-term storage).

AI model analysis: the cloud platform trains the model through historical data to predict equipment failure (such as bearing wear trend).

Visualization and decision support

Workshop Kanban: real-time display of equipment status (shutdown/operation/alarm), production progress and quality qualification rate.

Cloud platform big screen: group level view summarizes multi workshop data, and analyzes KPIs such as capacity utilization and energy consumption ranking.

Mobile terminal push: send fault work orders and energy efficiency optimization suggestions to operation and maintenance personnel.