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Manufacturing

Using ANAI, citizen data scientists and other developers with limited machine learning expertise can easily ingest data, generate insights and build/train ML models.

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potential use cases

AI in Manufacturing

Predictive Maintenance

Manage the maintenance cycles for mechanical equipment using AI-based predictive maintenance leading to better performance and saving costs on repairs.

Supply Chain management

Track goods and maintain proper material flow on the factory floor using industrial analytics and increase the efficiency of the entire manufacturing process.

Inventory management

Automate Inventory management using AI-powered systems to help keep track of the use and requirement of raw materials using the past data on demand and supply.

Quality Assurance

Using smart sensors and deploying Industrial Analytics can help companies keep better track of the quality of their manufactured product and help with saving costs on the rejected items.

limits

challenges found

01
Although AI in manufacturing comes with several benefits, setting up such systems requires a lot of upfront cost in the form of hiring a new team of AI experts and also setting up the IoT smart sensors everywhere on the factory floor. 
02
Lack of trust can be easily developed in the AI if it doesn’t work during some times or worse gives wrong decisions which can lead to a factory downtime and a halt in production. 
our platform

With ANAI, Build The Best AI Solutions

  • ANAI gives a simple easy-to-use AI-based platform that can handle everything from data engineering to building and maintaining complex AI models.
  • This can help companies save a lot of cost on hiring an expert for every part of the data science workflow and can enable companies to get the work done within weeks as compared to months or years.

ai manufacturing | artificial intelligence in manufacturing | manufacturing artificial intelligence | artificial intelligence for manufacturing

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