Manufactures & Factories
❯
Predictive Maintenance
❯Automated defect classification on product surfaces
Deep learning technology combined with topological data analysis successfully estimates degree of internal damage to bridge infrastructure
Scope:
Estimate and detect the risk of catastrophic collapse of old bridges.
Goal:
Improve Operation Efficiency
Automated defect classification on product surfaces
For:
Sanitary industries
Scope:
Image analytics for water taps in sanitary industries.
Goal:
Other
Analysing and predicting acid treatment effectiveness on bottom hole zone
For:
Manufacturer
Scope:
Mining of oil and gas; digital assistant for analysing and predicting the
effectiveness of acid treatments of the bottom hole zone.
Goal:
Other
Machine learning-driven approach to identify weak spots in the manufacturing of circuit breakers.
For:
Manufacturer of high-voltage (HV) circuit breakers
Scope:
Detecting issues in the manufacturing process that lead to early failure of the
circuit breakers through data mining related to the manufacturing process.
Goal:
Other
Intelligent technology to control manual operations via video Norma
For:
Industrial enterprises, repair enterprises, repair shops, operators of engineering
products.
Scope:
Tooltip visualization technology (augmented reality) based on technological
process and manual operations control in the assembly, maintenance, and repair
of engineering products.
Goal:
Other
Jet engine predictive maintenance service
For:
Airline industry, Jet engine industry, Airline maintenance industry, cloud-based
AI providers, airline insurance industry
Scope:
Use of jet engine telemetry data to train predictive maintenance algorithms
Goal:
Other
Large Companies
Manufacturing and Factories – Predictive Maintenance
For:
Operation, R&D
Scope:
Avoiding unplanned shutdowns in Manufacturing using Machine Learning to predict failure states in equipment.
Goal:
Anticipate Risks, Improve Operation Efficiency
Solution to detect signs of failures in wind power generation system
Scope:
Detect signs of malfunction (failure) in wind power generators
Goal:
Improve Operation Efficiency
Machine learning-driven analysis of batch process operation data to identify causes of poor batch performance
For:
Batch manufacturers such as milk pasteurizers, pharmaceutical makers, paint
manufacturers, etc.
Scope:
Detecting issues in a batch manufacturing process that lead to bad quality
products or longer cycle times for batch processing.
Goal:
Other
Automated defect classification on product surfaces
For:
Sanitary industriesGoal:
OtherProblem addressed
Image analytics using a combination of feature extraction and classification of
defects on shining surfaces in sanitary industries.
Scope of use case
Image analytics for water taps in sanitary industries.
Description
The proposed vision system has two parts: hardware and
software. The hardware captures images of product surfaces
under constant illumination. The software is developed to
perform image processing tasks and identify defects on
product surfaces.
The steps of the proposed system include image acquisition,
pre-processing, segmentation, feature extraction,
classification and post-processing. The system has two
software components: Feature Extraction and Classifier
Design. These two modules are implemented independently.
They can be developed in an offline platform and then
integrated into the vision system to work online.
As the first step, feature extraction is critical and guides the
extent to which a classifier can distinguish defects of one
class from those of another. A combination of features is used
like geometry (shape, texture), and statistical features of the
segmented images are also used. In the second step, a
support vector machine classification model is trained to
identify the defect types. The classification results obtained
by combining Gabor features, statistical features, and
grayscale features showed comparable performances with
human evaluations.
Overall, the vision system is modularized with capabilities to
self-learn and for future extension.
Live Video
Audio
AI: Perceive
Computer Vision
AI: Understand