12Service & Repair · IoT solutions

Remote equipment monitoring for predictive service

Service scheduled from equipment condition rather than a fixed calendar.

  • Runtime and condition collection
  • Threshold-based job creation
  • Fleet health dashboard
  • Fault alerting

The problem

Servicing was calendar-based, so some equipment was serviced unnecessarily while other units failed between visits.

What we built

We collect runtime and condition data from installed equipment, raising service jobs when thresholds are crossed rather than when the calendar says.

Modules delivered

  • Runtime and condition collection
  • Threshold-based job creation
  • Fleet health dashboard
  • Fault alerting
  • Service history per unit
  • Parts forecasting from condition

What changed

What the delivered system does differently from the process it replaced.

  • Service jobs are raised from equipment condition
  • Failures between visits are reduced by alerting
  • Unnecessary calendar visits are avoidable

Built with

The stack chosen for this build.

  • Go
  • PostgreSQL
  • REST API
  • MQTT

Why this customer is not named

Most of our customers allow the work to be described but not their name published. Where a customer has given permission, their name and testimonial appear here.

Independent accounts of our work are published by customers themselves on our Facebook reviews page.

Does this look like your problem?

If any of this is familiar, the first step is the same one this project started with: a free requirement study that ends in a written scope and a fixed price.

SYODONTECH
Remote equipment monitoring for predictive service | Case Study | Sydon Tech