IOT News

A certain LED manufacturing company specializes in LED packaging and luminaire production, with production lines covering dozens of types of automated equipment, including die bonding, wire bonding, dispensing, sorting, taping, SMT, assembly, aging testing, and more. As market demands for product quality consistency and delivery efficiency continue to rise, the traditional management model—relying on manual report entry, paper-based records, and experience-based equipment maintenance—can no longer meet the requirements of refined production management.

The company now needs to enable data collection and networked monitoring for all types of production equipment, and to transmit production data, equipment status, process parameters, alarm signals, and more to the MES system in a unified manner. This will break down information silos and enable centralized management, real-time monitoring, scientific production scheduling, and data-driven decision-making. To address this, WideIOT provides a highly reliable and efficient industrial IoT gateway solution for data collection.

Solution Overview

Since Wi-Fi is already deployed in the workshop, the primary approach is to connect devices via Wi-Fi, with Ethernet as a backup. Collected data—including production data, equipment status, process parameters, and alarm signals—is reported to the on-premise server and then interfaced with the MES system via API. This enables data acquisition, transmission, and network connectivity, providing comprehensive and reliable data support for the production management system, and enabling transparent production management and visualized dashboards.

Key Features

Collects equipment operating status (running, standby, offline, fault), process parameters (temperature, pressure, current, vibration, welding parameters), production counts (units processed, good/bad counts), and critical material information in real time, and uploads all data to the MES system to support full product lifecycle traceability.

When abnormal parameters, equipment faults, or production target deviations are detected, the system automatically notifies designated personnel via WeChat, SMS, and email, and generates alarm reports on the MES dashboard. This supports rapid response and enables closed-loop exception handling.

The gateway supports edge computing capabilities, including data filtering, alarm calculation, formula-based computation, and grouping strategies. By pre-processing data at the device side, it effectively reduces the computational load on the MES server and minimizes cloud data traffic.

The gateway is equipped with self-healing mechanisms such as a built-in watchdog, auto-reconnection after network drop, store-and-forward with resumption, and application health monitoring. These ensure continuity and integrity of data collection even during network fluctuations or failures, guaranteeing that production data is never lost.

Automatically aggregates and visualizes key metrics including OEE (Overall Equipment Effectiveness), equipment utilization rate, downtime rate, alarm count and handling progress, and daily/weekly/monthly production reports. This helps with scientific production planning and optimized resource allocation.