Intraratio Case Studies Identify Problems in Manufacturing with AI

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	Identify Problems in Manufacturing with AI Intraratio

Identify Problems in Manufacturing with AI

Intraratio

Technology Category	Analytics & Modeling - Machine Learning
Applicable Functions	Discrete Manufacturing
Use Cases	Predictive Maintenance
Services	Software Design & Engineering Services
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. Read More
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 Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Machine Learning

Applicable Functions

Discrete Manufacturing

Use Cases

Predictive Maintenance

Services

Software Design & Engineering Services

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.

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

Impact #1	[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.

Impact #1

[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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Overview

Identify Problems in Manufacturing with AI

Operational Impact