Real-time IoT Temperature Monitoring for Yarn Dyeing Machines

In Jaipur Rugs' yarn dyeing facility, temperature control is critical. Each dyeing recipe follows a precise temperature curve over time - specific temperatures must be maintained for exact durations to achieve consistent color results.

The machines had no built-in digital monitoring or alerting system. Operators were entirely responsible for tracking temperature manually, relying on memory and physical checks to know when to adjust settings or move to the next stage.

When an operator missed a step or forgot a timing requirement, the consequences were significant - the entire yarn batch would produce inconsistent color, requiring the recipe to be recreated and the yarn to be re-dyed. This wasted raw material, dye chemicals, machine time, and labor. The cost of a single missed step was substantial.

With multiple machines running simultaneously, the cognitive load on operators was unsustainable and errors were inevitable.

We designed and deployed an IoT monitoring system using ESP32 microcontrollers paired with PT100 temperature sensors installed directly on the dyeing machines. Each device continuously reads temperature data and transmits it via MQTT protocol to a NestJS backend.

A real-time dashboard built with WebSockets gives supervisors a live view of all machine temperatures simultaneously. More critically, the system sends instant alerts to operators via the mobile app whenever a temperature threshold is reached or a stage transition is required.

The backend also integrates with the existing ERP system, logging all temperature data automatically for quality records and compliance.

A pilot run was successfully completed validating the system before the planned full deployment across 34 machines.

The pilot deployment eliminated missed recipe steps entirely. Operators no longer need to remember timing - the system alerts them at every critical stage automatically.

Re-dyeing incidents caused by human error were eliminated during the pilot period, saving material costs, machine time, and labor on every batch where an error would previously have occurred.

The system also created a complete digital audit trail of every dyeing run - temperature logs stored automatically against each batch for quality traceability.

The planned Phase 2 extension would take the system further - using the same ESP32 hardware to not just monitor but actively control water flow and temperature, removing human intervention from the process entirely.

34

Machines in deployment plan

0

Missed recipe steps

Real-time

Live temp tracking