Aluminum Manufacturer
Maintenance Optimization with AI-Augmented Software
Our client is a global firm that operates throughout the entire aluminum value chain—spanning from mining to manufacturing, extrusion, and recycling. Hiflylabs helped optimize their maintenance processes and built an AI solution that meets modern enterprise needs at their scale.
7.5%
shorter production downtime
12%
maintenance cost reduction
Challenge
Machine failure and slow troubleshooting cause costly production delays, especially when the failure of a single asset impacts the entire production pipeline. The information necessary for troubleshooting, such as user manuals and other documentation, is often spread across different formats and languages, which makes it time-consuming to access. Furthermore, key employees act as knowledge bottlenecks since they are the only ones who know where important documents are located, further delaying workflows and making the production process less efficient.
Solution
Hiflylabs developed a format-agnostic RAG (Retrieval-Augmented Generation) solution that streamlines the maintenance process by enabling efficient retrieval of information from various document formats, providing comprehensive and context-specific answers in a user-friendly interface tailored for factory environments. This solution also offers a unified language interface, making it easier to access multilingual data through a single language, reducing the complexity of handling diverse sources. As a result, troubleshooting is accelerated, and relevant documents are provided quickly, significantly reducing downtime and ensuring smoother operational efficiency.
Service
AI
Industries
Energy
Manufacturing
Mining
Technologies
Python
MLFlow
PostgreSQL
Unstructured
LangChain
LangGraph
Microsoft Azure
OpenAI
FastAPI
React
Angular
Docker
Technologies
Python
MLFlow
PostgreSQL
Unstructured
LangChain
LangGraph
Microsoft Azure
OpenAI
FastAPI
React
Angular
Docker
-
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