Operation
❯
Predictive Maintenance
❯Intelligent technology to control manual operations via video Norma
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
Large Companies
Knowledge representation - Bayesian Network
For:
Process Engineers.
Scope:
Applying Bayesian Networks to root cause analysis of industrial processes.
Goal:
Improve Operation Efficiency
Predictive maintenance of public housing lifts
For:
FM company, residents in public housing
Scope:
Build an AI solution that can predict malfunction in a lift
Goal:
Other
Product failure prediction for critical IT infrastructure
For:
QA engineers, manufacturing line technicians, technical sales
Scope:
Building an AI solution to augment QA engineers
Goal:
Other
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
Active antenna array satellite
For:
Operators of satellite communication systems
Users of satellite communication systems
Regulation authorities
Space agencies
Scope:
Determine optimal spot beam patterns for communication satellites in order to
react to changing geographic distribution and bandwidth requirements of
terminals.
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
Carrier interference detection and removal for satellite communication
For:
Operators of satellite communication systems
Operators of other communication systems (satellite or non-satellite) that are
potential sources of interference
Users of satellite communication systems
Regulation authorities
Space agencies
Scope:
Machine-learning-based detection, classification and removal of interference
signals for satellite communication systems.
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
Intelligent technology to control manual operations via video Norma
For:
Industrial enterprises, repair enterprises, repair shops, operators of engineering
products.Goal:
OtherProblem addressed
"Norma technology will minimize, as far as possible, the number of errors made
by technical personnel during manual assembly of products. It visually displays
the correct sequence of actions to the user-assembler through augmented reality
glasses, overlaying the process on top of the parts. Norma controls the accuracy
of manual operations and the tools used. It fixes detected deviations in the
electronic passport of the product. Additionally, Norma promptly reports
identified violations of the process to the quality control department. Norma will
dramatically improve the quality of production and technological operations
without the widespread use of industrial robotics, which will avoid the negative
social consequences caused by automation of production.
Scope of use case
Tooltip visualization technology (augmented reality) based on technological
process and manual operations control in the assembly, maintenance, and repair
of engineering products.
Description
The quality of assembly, maintenance, and repair of
engineering products substantially depends on the number
of errors made during manual operations. According to data
from various sources (railway, nuclear, aviation, and other
industries), the percentage of failures caused by a violation
of maintenance and production technologies by technical
personnel is 54 %.
The mistakes made during assembly, maintenance, and
repair of engineering products are based on the following
problems:
lack of constant (objective) control of manual operations
at all stages of assembly, maintenance, and repair of
engineering products;
lack of reliable data on the operations performed and the
mistakes made throughout the life cycle of the product,
which makes it difficult to exclude errors from the
design of the product.
Norma technology is designed to control manual
operations during assembly, maintenance, and repair of
engineering products. Norma technology would monitor
compliance with the process through the analysis of video
data and record every step in the electronic passport of the
product.
Engineers performing maintenance and repair or operator-
assemblers would wear augmented reality (AR) glasses
which would show all information about the technological
process and step-by-step instructions. In these glasses, all
parts of the engineering product would be recognized and
marked up with bounding boxes showing which parts are
required at each step of the technological process.
The user wearing the AR glasses would be notified about
errors made during the technological operation so they can
fix the problem before proceeding to the next step. The AR
glasses would record and store video of the technological
process performed and create an electronic passport of the
engineering product.
The engineer would train machine learning models included
in the "Norma" technology in an automated manner using 3D
CAD models of engineering products and descriptions of the
technological process.
Live Video
AI: Perceive