Intraratio > Case Studies > Identify Problems in Manufacturing with AI

Identify Problems in Manufacturing with AI

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 Identify Problems in Manufacturing with AI - IoT ONE Case Study
Technology Category
  • Analytics & Modeling - Machine Learning
Applicable Functions
  • Discrete Manufacturing
Use Cases
  • Predictive Maintenance
  • Software Design & Engineering Services
The Challenge

Outliers have often been seen as the low-hanging fruit for various manufacturing issues, whether it's root cause, machine issue, or raw material.

The Solution

With the power of AI and machine learning, the company applies these various algorithms to automatically detect these different outliers across the whole manufacturing production line.

Intraratio chose Isolation Forest because of its ease of use. It can be used in different programming languages and takes categorical data and numerical data without many transformations involved

Operational Impact
  • [Data Management - Data Analysis]

    Instead of going one by one, versus a graph, customers can actually group a bunch of different features together and it can look for outliers of the whole. Isolation Forest takes the features and dissects them into a decision tree and isolates that very uncommon data point as being the outlier.

    Once it does that, it flags that outlier and outputs it into a table where the engineer could further investigate where it comes from.

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