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❯Improvement of productivity of semiconductor manufacturing
Large Companies
Computer Vision - Gesture Recognition
For:
Certification examiners.
Scope:
How Gesture Recognition authentication uncovered mortgage licensing fraud.
Goal:
Anticipate Risks
General Public
Education - Accessibility
For:
Deaf and hard of hearing (DHH), and non-native speaking academic students.
Scope:
Captioning lecturer's speech to improve the learning experience of Deaf and Hard of Hearing students.
Goal:
Improved Customer Experience, Improved Operation
Chromosome segmentation and deep classification
For:
Hospitals, doctors, cytogeneticists, patients
Scope:
Karyotyping of chromosomes is restricted to healthy patients.
Goal:
Improved Product Development / R&D
Government
Defense & Military - Intelligence & Surveillance
For:
Soldiers
Scope:
Reducing the requirement for manual monitoring in insurgency-hit areas with Smart Surveillance.
Goal:
Anticipate Risks
Dialogue-based social care services for people with mental illness, dementia and the elderly living alone
For:
Government or public institutions
Scope:
Daily life support AI services that provide an interaction with humans using natural language
Goal:
Improved Customer Experience
Instant triaging of wounds
For:
Wound nurses, diabetes patients, hospitals
Scope:
Build an AI solution to augment triaging decisions by wound nurses.
Goal:
Improved Employee Efficiency
Large Companies
Small Companies
Entertainment and Media - Metadata Tagging
For:
Digital asset managers.
Scope:
Realizing the value of historical sporting digital media assets by using Artificial Intelligence (AI) to assist in doing the work of 15 interns.
Goal:
Improved Product Development / R&D, Improve Operation Efficiency
Intelligent Video Traffic Monitoring
For:
Traffic Management Officials
Education - Automated Content Generators
For:
Online course creators.
Scope:
Intelligently generate, curate, and recommend content educational content.
Goal:
Improved Customer Experience
Large Companies
Small Companies
Entertainment and Media - Subtitle Creation
For:
Content creators
Scope:
Creating efficiencies for content creators via automatic subtitle creation for social video.
Goal:
Improved Employee Efficiency
Autonomous apron truck
For:
Transporter
Scope:
Automated transportation of luggage (carts) to requested destinations on an airport apron while following local traffic rules and resolving unplanned
conflicts.
Goal:
Improve Operation Efficiency
Robotic prehension of objects
For:
Customers, 3 rd parties, end users, community
Scope:
Outputting the end effector velocity and rotation vector in response to the view
from a red green blue depth (RGB-D) camera located on a robot's wrist.
Goal:
Improve Operation Efficiency
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
Government
Defense & Military - Autonomous Vehicle
For:
Military Operatives.
Scope:
Using computer vision to implement perimeter safety for Autonomous Vehicles.
Goal:
Improved Product Development / R&D
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
Automated defect classification on product surfaces
For:
Sanitary industries
Scope:
Image analytics for water taps in sanitary industries.
Goal:
Other
Pre-screening of cavity and oral diseases based on 2D digital images
For:
Dentist
Public
Scope:
Artificial intelligence-based oral examination platform.
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
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
Real-time patient support and medical information service applying spoken dialogue system
For:
Dentist
Hospital
Scope:
Medical business support system using artificial intelligence-based human-
computer interface technology.
Goal:
Other
AI situation explanation service for people with visual impairments
For:
Personal services
Scope:
A real-time situation explanation service through voice for people with visual impairments
Goal:
Improved Customer Experience
General Public
Education - Smart Learning Content
For:
Online course creators and online learners.
Scope:
Empowering course creators to focus on complex decision-making and creativity with Computer Vision and Natural Language Processing.
Goal:
Improved Employee Efficiency
Autonomous trains (Unattended train operation (UTO))
Scope:
Freight and passenger trains operate autonomously, excluding any crew
presence on board, but with remote operator attention involved.
Goal:
Improve Operation Efficiency
AI sign language interpretation system for people with hearing impairment
For:
Government or public institutions
Scope:
Increase the convenience of public services to people with hearing impairment
by providing a service to translate sign language image information into natural
language
Goal:
Improved Customer Experience
Precision Farming as a Service
For:
Farmers
Scope:
Use visual recognition to identify and help fight parasites attacking organic farms.
Goal:
Anticipate Risks, Improve Operation Efficiency
General Public
Computer Vision - Object & Activity recognition
For:
Commuters
Scope:
Using computer vision to enable Smart Parking solutions for realtime parking availability.
Goal:
Improved Customer Experience
Facilitating language learning of deaf people
Scope:
Use of advanced and multimodal sensing ability to facilitate a complex task.
Goal:
Improved Customer Experience
Computer-aided diagnosis in medical imaging based on machine learning
Scope:
Detecting image anomalies.
Goal:
Improve Operation Efficiency
Social humanoid technology capable of multi-modal context recognition and expression
For:
Dialogue service services using display devices
Service robot
Scope:
Human-AI sympathetic technology expressing dynamic immersive dialogue with
humans through a combination of various artificial intelligence technologies
Goal:
Other
Autonomous Robot Improves Surgical Precision Using AI
For:
Hospitals using Autonomous robotic surgery via the STAR system
Goal:
Improve Operation Efficiency
Improvement of productivity of semiconductor manufacturing
For:
Executives of semiconductor manufacturing companiesGoal:
OtherProblem addressed
Cost reduction of semiconductor manufacturing.
Scope of use case
Analysis of data taken from production equipment and improvement of productivity based on the analysis.
Description
This use case consists of the following three themes.
1. Support of analysis of cause of failure based on wafer
map patterns
At the final stage of semiconductor manufacturing, each chip
on a wafer is tested and a pattern of the failed chips are
distributed on the wafer is produced. Analysis of the cause of
failure is carried out based on the pattern and the history of
usage of manufacturing devices. The analysis is supported by
the following four technologies.
1.1 Clustering of wafer map patterns
Clustering of the wafer map patterns is carried out in order
to grasp an overview of the occurrence of the failure. Because
there are 200 thousand wafers per month, a fast clustering
algorithm is required to promptly provide information to
engineers. Making use of scalable k-means++, the clustering
process is 72,5 times faster than the previous method.
1.2 Cause estimation based on pattern mining
If failure of a particular manufacturing device frequently
occurs in the history of a wafer belonging to a wafer map
cluster and failure of the device seldom occurs in the history
of other wafers, then the device is likely to be the cause of the
failure. The candidates for the cause of the failure and their
likelihoods are calculated based on the number of
occurrences of the combinations of the devices promptly
counted by a pattern mining algorithm FPGrowth and
ranking through chi-square test.
1.3 Wafer map classification based on CNN
A wafer map is classified into registered typical wafer maps
in order to monitor the recurrence of the failure. The
classification accuracy (F1 score) with SVM was 0,898.
Making use of CNN, the accuracy is improved to 0,95.
1.4 Web portal for yield analysis
The information provided by the above technologies is
shown in a web portal. The portal has improved the average
analysis time from six hours to two hours.
2. Automatic classification of scanning electron
microscope (SEM) images of defects
Tests of wafers are carried out not only at the final stage of
the production but also between processes, where the result
of the previous processes is checked. One of the tests is
classification of images of microscopic aspects of the defects
observed by SEM. Thirty thousand images are taken daily. It
is an important test because the class of a defect may provide
valuable insight for cause estimation. Previously, the
classification was carried out semi-automatically by an
engineer with a tool with classification function. However,
the human workload was relatively high because the tools
ability was quite limited. Making use of CNN, the number of
defect categories that are automatically classifiable has
dramatically increased. Now the automation ratio is 83 %,
improved from 49 %.
3. Analysis of cause of variation of quality characteristic
value
In the Yokkaichi operation, the cause of the variation of a
quality characteristic value is identified and the yield is
maintained by countermeasures. For quick identification,
various data including process parameters and sensor
measurements from a manufacturing device are stored in a
DB. Therefore the number of attributes becomes huge by the
time of the completion of production. It is not uncommon for
the number of attributes to be much greater than the number
of products to be analysed, sometimes by several orders.
Making use of Lasso regression for data with 23 600
attributes and 303 products, a regression model predicting a
quality characteristic value has been built, with automatic
feature selection. Engineers cause identification tasks are
also supported by a network diagram that visualizes the
causal structure of the selected features. As a result, the
average analysis time is improved to one day from seven
days.
This proposal is based on the use case collection initiative
promoted by Japanese Society of Artificial Intelligence (JSAI).
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