Machine Monitoring System in Manufacturing

Why we need Machine Monitoring System?

Production engineers, supervisors, or company owners are always interested in knowing what is happening on the shop floor. To get the information either they go to the production floor or call the machine operator. It’s a time-consuming task and can reduce productivity.

So what can be the Solution?

  1. Hire a person who will send me updates each hour.
  2. What if we can get shop-floor data on the mobile app.
This image shows how a machine monitoring solution idea comeup.

Starting a new position just for updates is very costly. And what if he goes to leave.

But getting all shop floor data on a mobile app looks like a great idea.

Yes, it will be great if we can get all production parameters on our mobile with minimal human interaction. We can make decisions backed by strong data instead of the gut, or intuition.

How can we get the machine data on my mobile app?

“Machine Monitoring Solutions” are here for the rescue.

The Machine monitoring is all about getting real-time machine parameters or data, processing this data, and generating real-time insights to get more visibility on the shop floor.

Machine Current Status Directly to Your Mobile Screen

This data from machine monitoring can have the following applications.

  • Monitor current machine status.
  • Condition monitoring
  • Predictive Maintenance
  • Real-time alerts
  • Machine utilization calculations.
  • Improve productivity
  • Maintenance Planning etc.

Here is the list of companies proving machine monitoring solutions:

Example of Machine Monitoring System

A machine monitoring system consist of hardware devices, Gateways, Cloud storage, Machine learning and analytics.

This image shows the Working of a Machine Monitoring System

Analog and digital sensors are connected to the machine to get machine data. These sensors send real-time machine data to a gateway & edge computing device. The edge computing device process the data to generate insights and sends data to the cloud.

In the cloud, we can train the machine learning algorithms. Users can access the data using the internet-connected web and mobile applications.

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