Automated Weight Validation & QR-Based Traceability for Copper Wire Manufacturing -

The Rise of Edge Computing in Industrial IoT

The Industrial Internet of Things (IIoT) continues to evolve, and one of the most transformative trends in this space is the rise of edge computing.

As factories and industrial environments generate increasing amounts of data, processing that information close to where it is created — rather than sending everything to the cloud — is becoming essential.

Why Edge Matters in IIoT

Traditional cloud-based models have limitations when it comes to real-time decision-making.

For mission-critical systems such as quality control, utility automation, or production line monitoring, latency and intermittent connectivity can seriously impact performance.

Edge computing addresses these challenges by enabling:

Real-time decision-making through rule-based logic and automation running directly on edge hardware
Reduced data bandwidth costs by transmitting only critical information to the cloud or central platforms
Improved system resilience, allowing operations to continue even during network outages

Real Industrial Impact

In a manufacturing environment, an edge-enabled system can immediately respond to anomalies such as deviations in product weight or unexpected machine temperature changes without waiting for cloud-based validation.

This immediate response capability increases operational uptime, reduces risk, and improves overall quality assurance across production processes.

As IIoT deployments continue to expand across manufacturing, energy, utilities, and infrastructure sectors, edge computing is increasingly becoming the foundation of modern industrial automation.

Automated Weight Validation & QR-Based Traceability for Copper Wire Manufacturing

Industry

Wire & Cable Manufacturing

Solution Type

Industrial IoT | Edge-Based Automation | Hardware + Software Integration

Client Challenge

A copper wire manufacturing company produces wires in multiple specifications, such as:

Wire size (e.g., 0.75 sq.mm)
Length (e.g., 40 meters)
Insulation class (e.g., Class 2, FR)

During production:

Individual wire coils are packed into small boxes
Multiple small boxes are then placed into a single large master box
Each master box carries a QR code containing wire specifications

The Critical Problem

Each master box must meet a strict weight range based on its wire specifications.

Example:

Expected weight: 30.6 kg
Allowed tolerance: 28.6 kg – 32.6 kg

Issues faced:

Manual verification caused errors
Incorrect boxes entered packing and dispatch
No reliable digital traceability
Lack of real-time pass/fail visibility

The client needed a fully automated, high-accuracy validation system that works directly on the shop floor.

Aceomation’s Solution

Aceomation designed and implemented a custom Industrial IoT solution combining:

Custom hardware
Edge computing
Automated validation logic
On-device web application

All processing happens locally, ensuring speed, reliability, and zero dependency on internet connectivity.

System Architecture Overview

QR Scanner + Weight Calibration Hardware → Raspberry Pi (Edge System) → Printer + Dashboard

How the System Works

Step 1: QR Code Identification

Each master box carries a QR code with wire details:

Wire size
Length
Insulation class

When the box reaches the scanning point:

The QR scanner reads the code
Data is sent to the system via Ethernet

Step 2: Weight Acquisition

Aceomation built custom hardware to interface with the weight calibration machine

The actual box weight is transmitted to the system via USB communication

Weight data is captured in real time

Step 3: Intelligent Validation

A Node.js backend running on a Raspberry Pi (Linux OS) performs:

QR data lookup from the local database
Fetches the allowed weight range
Compares actual weight vs permissible range

Machine Control & Rejection Logic

To ensure incorrect boxes never reach the packing stage, Aceomation implemented direct machine-level control integrated with the production line.

How Rejection Works

Once the backend completes the weight validation:

The system determines Pass or Fail in real time

For failed boxes:

The Aceomation-built hardware sends a control voltage signal to the PLC
The PLC immediately triggers the rejector mechanism
The box is physically ejected from the conveyor line

For passed boxes:

No rejection signal is sent
The box proceeds to printing and final packing

Step 4: Automated Print ID Generation

For passed boxes:

System generates a unique print ID
Example: A0000001

Print data is sent directly to the printer via USB

Box moves forward for final packing

For failed boxes:

Box is automatica

Let’s Solve a Real Industrial challenge

Our systems are actively running in critical industrial environments, delivering measurable results and operational improvements.

24/7 Edge Operation

Designed for continuous, uninterrupted performance.

Sub-second Control

Low-latency processing for time-critical applications.

Secure Data Segregation

Robust security protocols to protect sensitive operational data.

Scalable Architecture

Systems that grow with your multi-site operations.

Industrial IoT & Applied AI Systems, Engineered for Real-World Operations.