株式会社スカイディスク

The Innovator of Smart Factory

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Mission

Improve Factoryʼs productivityby AI

Company Name Skydisc, Inc.

Office Locations Fukuoka (HQ), Tokyo, Osaka, Nagoya, Vietnam

Employees 64 people（2019 May）31 AI engineers from 8 countries

Capital 1.7 billion JPY

CEO Osamu Hashimoto

Founded on Octobor 1st / 2013

Business Domain AI×IoT - Smart Factory Solution

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Company Overview

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Strong R&D oriented engineering team

9 PhD holder

From 8 countries

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SKYDISC would like to grow with Thailand by supporting manufacturing industries. The CEO of SKYDISC shook hands with H.E. Dr. Somkid Jatusripitakto make Thailand 4.0 in action.

▲Dr. Somkid Jatusripitak and Skydisc CEO Hashimoto

Business in Thailand

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Investment from VCs

2017 20182016 2019

3⽉ 20191⽉ 2016 10⽉ 2017

1milUSD

7mil

USD7mil

USD

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Business in Japan

Car manufacturerCar parts manufacturer (Tier1) Chemical Plants Power Plants

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SKYDISC no. of AI projects

0

5

10

15

20

25

30

35

40

45

50

2017 2H 2018 1H 2018 2H

Accumulated no. of AI projects

45

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Plan to have an Thai office

FukuokaHQ

ThaiOffice

Expect to starting in 2019

VietnamDev

Office

TokyoHQ

OsakaNagoya

We will be recruiting in the near future• AI engineers• Consulting sales

SKYDISC is waiting for approval from BOI…

things you should know before you use AI in your factory

株式会社スカイディスク – 10

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3 things you should know before you use AI

1. Where you should use AI?

2. Donʼt expect too much

3. Worker-AI collaboration

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3 things you should know before you use AI

1. Where you should use AI?

2. Donʼt expect too much

3. Worker-AI collaboration

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Keyword to find AI application

UnwrittenRules

Replacehuman’s 5 senses

1. Where you should use AI?

ReplaceTasks by intuitioins

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1. Where you should use AI?

Replace human’s 5 senses→ Vision, hearing, touch

Vision︓Product Inspection by Images

Hearing︓Product Inspection by Sound

Touch︓Machine Inspection by Vibration

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1. Where you should use AI?

Vision Sound Vibration

Car partsProduct inspection

Silicon waferProduct inspection

MotorsFacility maintenance

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Replace tasks by intuition

→ There are rules, but they are only in the head of skilled engineers

Manual parameter setting of manufacturing

machines on factories floors or plants

done by skilled engineers

1. Where you should use AI?

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1. Where you should use AI?

Chemical plantsmachine parameter optimization

Power plantsMinimize fuel consumption

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3 things you should know before you use AI

1. Where you should use AI?

2. Donʼt expect too much

3. Worker-AI collaboration

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2. Donʼt expect too much

Issues coming from too much expectations

1. Expecting too much results from PoC （Proof of Concept)

AI development requires “search” phase to find out the best result. It is impossible to find out the ideal methods from start.

We perform PoC not as a “development” We must set an “appropriate” goals.

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2. Donʼt expect too much

Issues coming from too much expectations

2 . Perform as human?

Newly develop AI doesnʼt perform as same as human.

You need to learn what AI can do.

AI just supports humansʼ tasks.

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AI is like a new graduate in your office

You need to train it

2. Donʼt expect too much

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AI is like a new graduate in your office

You need to train it

2. Donʼt expect too much

Don’t worry, it will never quit or retire

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Data and the skilled engineers train Mr. AI

Data on the factory floor and the skilled engineersʼ experience will help develop the optimized AI on your factory.

It is very important to invite skilled engineers to the AI team. Skilled engineerʼs domain knowledge will help AI smarter.

2. Donʼt expect too much

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3 things you should know before you use AI

1. Where you should use AI?

2. Donʼt expect too much

3. Worker-AI collaboration

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3. Worker-AI collaboration

95% 93%

AI Human

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3. Worker-AI collaboration

AI Human

99%

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3. Worker-AI collaboration

AI human

The abnormality human can find andThe abnormality AI can find are different

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3. Worker-AI collaboration

AI will help your decision not decide by itself from start.

If you properly train it, it will be independent soon.

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3. Worker-AI collaboration

Examples of worker-AI collaboration

Abnormality detection / predictive maintenance

à Realize less down time

à Speed up on checking

Failure reason analysis

à Improve yield

à Machine setting optimization

Product Inspection

à AI perform pre-check and human checks later

à Reduce the number of products human checks

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3 things you should know before you use AI

1. Where you should use AI?

2. Donʼt expect too much

3. Worker-AI collaboration

Inquires from here

Or e-mail me

Suenaga Yoshihikosuenaga@skydisc.jp