Automotive OEM process automation saves valuable time and eliminates human error


A large international automotive OEM (Original Equipment Manufacturer) was struggling with the inefficiency of their tool documentation process from supplier facilities where suppliers were required to take photos and upload them to an outside system and checking labels manually.

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Objectives

Automate a manual process for checking labels for supply parts.

Applied Intelligence

The AI solution includes deep learning, image processing, and natural language processing techniques such as text and language modelling. For the deep learning model, a recurrent neural network comprising of long short term memory networks (LSTM) units was used.

Results

We developed a machine learning based solution to automate and streamline the documentation of tools arriving at the manufacturing plant from a supplier facility. The new process has the supplier taking photos of the tools and labels associated with each piece of equipment. Our system documents these photos and the labels associated with each piece of equipment and performs optical recognition (OCR) to check that the label meets the manufacturer’s guidelines in real time. Now, there is no need to upload photos to a different system or checking labels manually - saving valuable time and eliminated human error.

 OCR Label reading system

OCR Label reading system

 
We developed a machine learning based solution to automate and streamline the documentation of tools arriving at the OEM manufacturing plant from their supplier facility... saving time and eliminating human error.

Other Use Cases

QUALITY ASSURANCE

LABEL RECOGNITION

SUPPLY CHAIN MANAGEMENT

PAINT INSPECTION