Predictive Maintenance - Improve Your Equipment Reliability

USE CASE

Predictive Maintenance in Manufacturing.

TARGET USER

Manufacturing industry.

OVERVIEW

A manufacturing factory relies on their equipment to produce their products, but unexpected equipment failures can result in significant downtime and maintenance costs. To address these challenges, the factory implements an IIoT system that monitors their equipment in real-time and predicts equipment failures before they occur.

Challenge 1

Reactive maintenance approach.

The factory’s current maintenance approach is reactive, leading to increased downtime and maintenance cost.

Challenge 2

Inefficient maintenance scheduling.

The man factory’s current maintenance scheduling process is inefficient, resulting in unnecessary maintenance and downtime.

Solution 1

Predictive maintenance using machine learning algorithms.

The analytics feature uses machine learning algorithms to predict equipment failures, allowing the company to schedule maintenance proactively and reduce downtime and maintenance costs.

Solution 2

Streamlined maintenance scheduling using IIoT technology.

The manufacturing factory uses IIoT technology to automate their maintenance scheduling process, reducing errors, and improving scheduling efficiency.

Predictive Maintenance in Manufacturing