Machine Vision for Warehouse Optimization

Machine Vision for Warehouse Optimization
Summary
The experiment was carried on by Gualini Lamiere SpA.Gualini experiment was about “Machine Vision for Warehouse Optimization”, and the warehouse of Gualini was the problem and the core of the Pilot itself.
 
Gualini’s warehouse is made of piles of heavy steel sheets, which, for this reason, need to be placed on the ground. The sheets have different dimension, thickness, structure and weight. The responsible of the warehouse, who receive punctual inputs from the production line, need to know exactly where to find the sheet they need, where it is located within the piles and in which position exactly.
 
The problems in Gualini’s warehouse was related to labelling, recognition and handling of the steel sheet, and was extendable to many manufacturing companies. Labelling is often inefficient due to the cover of the label made by the pile structure; besides, the frequent handling of the sheets exposes the label to a physics degradation; the bar codes attached on each sheet in the pile can wear out, tear and get lost during the handling which is frequent, each day.
The focus of the experiment was the implementation of a system able to support operators in the warehouse to identify exactly the unique sheet they need at that time for further delivery to production line.
The gain of the Pilot in Gualini has been to “recognize” exactly the characteristic of each steel sheet and to know exactly the position of the needed steel sheets within the piles and inside the pile, so as to reduce the handling, that has a high impact on men efforts, time and cost.
 
The idea of the experiment was to use AI, machine vision and a vision system to identify in real-time the sheets inside piles in the warehouse (storage area) and efficiently and fast moving them to forward to the production line.
Machine Vision is needed to automatically analyse the dimension of the “incoming” steel sheet and recognize the correctness between the physical element and the digital data. After which, track the position of every single sheet in every pile.
Artificial Intelligence is needed to track the material available and every handling in the warehouse, identify possible human mistakes and advice, and automatically analyse the data and be aware of the position of every steel sheet in the Wearhouse.
Expert system is needed because the system must improve its ability during time and allow a perfect and impeccable handling and warehouse management.
 
The project tested this recognition and traceability technique; in this experiment the technology has been applied in the warehouse in order to  easily trace exactly the sheet needed by the production line.
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Country: IT
Address: via Europa, 50, Bolgare 24060
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Comment:

The experiment has achieved the following objectives:

Provide a tool able to help operators to find the exact sheet they need for production line.

The tool can significatively decrease time usually needed to find out, handle and pick up the sheet that is needed from the production line.

The tool is expected to self-learn over time.

Comment:

Optimize the Handling

Reduce Technical Checks by Humans

Improve data quality