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Adaptive Quality Assurance (AQuA) method and system Disclosure Number: IPCOM000190336D
Original Publication Date: 2009-Nov-24
Included in the Prior Art Database: 2009-Nov-24
Document File: 2 page(s) / 42K

Publishing Venue



Disclosed is a method which is generating checkpoints for visual inspection in real time with usage of artificial intelligence which combine different data analysis technique outputs.

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Adaptive Quality Assurance (AQuA) method and system

In manufacturing the visual inspection gate is one of the important process step which ensures that the product is meeting the required quality level and it is free from defects caused during the manufacturing process. To reach a high level of outgoing quality, the checklist can contain several hundreds of checkpoint if a product is a complex system like a high-end storage server. The maintenance of the checklist requires many engineering hours as it needs to be updated frequently based on costumer complaints and production failure trends. In addition, the visual inspection is a time consuming process step which doesn't represent value for the costumer.

The following system solution gives possibility to reduce both manufacturing process time and engineering hours reduction which needed to execute and define the visual inspection checkpoint.

The system contains the following main components, Picture 1.:

1. Visual inspection

Findings on products are collected by manufacturing operators and entered into a database

2. Database

Contains all historical data including production history, component lists, operator performance and defects/costumer complaints

3. Artificial intelligence is defining the checklist for operators (unique checklist for each product)


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