Manufactures & Factories
❯
Product improvement
❯AI decryption of magnetograms
AI solution to quickly identify defects during quality assurance process on wind turbine blades
For:
Manufacturer
Scope:
Detecting defects in products by inspecting non-destructive testing scanning
data.
Goal:
Other
AI decryption of magnetograms
For:
Manufacturer
Scope:
Oil and gas transportation. AI solution to quickly identify defects during the
quality assurance process on a field pipeline.
Goal:
Improve Operation Efficiency
Leveraging AI to enhance adhesive quality
For:
Manufacturing industries; suppliers and buyers; environment
Scope:
Batch/continuous/discrete manufacturing (Deployed in 75+ manufacturing lines
in 10+ countries; specifically identify the contributors to quality; predict
potential quality failures).
Goal:
Other
Improvement of productivity of semiconductor manufacturing
For:
Executives of semiconductor manufacturing companies
Scope:
Analysis of data taken from production equipment and improvement of productivity based on the analysis.
Goal:
Other
Generative design of mechanical parts
For:
Organizations, designers, customers, end users
Scope:
Help mechanical engineers design lighter, strong, and better parts.
Automatic classification tool for full size core
For:
Manufacturer, geologist
Scope:
Oil and Gas exploration, classification of rock types, oil saturation, carbonate and
fracture according to core images
Goal:
Other
Information extraction from hand-marked industrial inspection sheets
For:
Manufacturing companies, machine inspectors, engineers
Scope:
Localization and mapping of machine zones, arrows and text, to extract
information from manually tagged inspection sheets.
Optimization of ferroalloy consumption for a steel production company
For:
Steelmaking, steel industry
Scope:
Recommendation for the optimal consumption of ferroalloys by the ladle furnace
treatment during secondary steelmaking.
Goal:
Other
New machine-learning simulations reduce energy need for N95 mask fabrics
For:
Manufacturing companies of high density mask fabrics, in this project 3M specifically.
Goal:
Improved Product Development / R&D
AI solution to calculate amount of contained material from mass spectrometry measurement data
Scope:
Calculating the amount of contained material from mass spectrometry
measurement data using chromatography.
Goal:
Reduce costs
AI decryption of magnetograms
For:
ManufacturerGoal:
Improve Operation EfficiencyProblem addressed
Detection of internal defects (pits, ulcers, etc.)
Detection of structural elements (welds, bends, etc.)
Scope of use case
Oil and gas transportation. AI solution to quickly identify defects during the
quality assurance process on a field pipeline.
Description
In the territory of the Russian Federation, there are tens of
thousands of kilometres of small diameter production
pipelines under varying degrees of condition facing varying
numbers of internal defects (pits, ulcers, etc.) and structural
elements (welds, bends, etc.)
There are in-tube flaw detectors that allow the signal from
the magnetometer sensors to be read. These robots are not
widely used due to the speed of data interpretation.
Automation of the recognition of structural elements and
defects would reduce the pipeline diagnostics process by at
least 160 x
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AI: Perceive