I N O V A T I F - M A N D I R I - T E R K E M U K A

Product Inspection through Machine Learning

Dr. Kahlil Muchtar

Electrical and Computer Engineering

Telematics Research Center

Universitas Syiah Kuala

I N O V A T I F - M A N D I R I - T E R K E M U K A

I N O V A T I F - M A N D I R I - T E R K E M U K A

Outline

❑ Pengenalan❑ Manufaktur Cerdas❑ Metode mendeteksi cacat pada produk❑ Evaluasi dan diskusi❑ Kesimpulan

Revolusi Industri 4.0 di Indonesia

Dalam sektor industri 4.0, akan banyak kegiatan industri

yang mulanya dilakukan masih mengandalkan tenaga

manusia akan beralih ke tenaga mesin digital dan

berteknologi canggih, sehingga berpotensi menggeser

peran tenaga manusia di sektor industri. Untuk

menjawab tantangan itu, Menteri Pendidikan dan

Kebudayaan (Mendikbud) Nadiem Makarim bersama

dengan tim meluncurkan program pendidikan "Merdeka

Belajar: Kampus Merdeka". Program Kampus Merdeka

sendiri dibuat untuk mempersiapkan sumber daya

manusia (SDM) sehingga mempunyai talenta yang

adaptif di zaman Revolusi Industri 4.0.

Perkembangan Revolusi Industri 4.0

The era of RI 4.0

Evolusi AI

• Expert Systems

• Artificial Neural Networks

• Fuzzy Logic Systems

Traditional AI

First Wave

Traditional Programming

Second Wave

Neural Nets – Deep Learning Cognitive Architectures

Third Wave

• Short- and Long-term Memory

• Pattern Matching

• Prediction

• Prioritization

• Reasoning, Planning, and many others

• All of the above

Artificial General Intelligence (General AI)

• Big Data Analytics

• Deep Learning

Narrow AI

Deep Learning Explosion

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Deep Learning vs Machine Learning

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Deep Learning: Face Recognition

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Lingkungan Cerdas (Smart Environment)

Self-learning Condition Monitoring

Wireless Networked Automation

CRITICAL ISSSUES:

• Identification

• Sensing or Data Acquisition

• Wireless Communication

• Low Energy

• Energy Harvesting

• Bandwidth

• Interact & Control (Ux)

• Intelligence

• Interoperability

• Analysis / Big Data

• Security / Privacy

Source: Fraunhofer IIS, EAS Division, Germany

Wireless Sensing, Connected

Manufaktur Cerdas (Smart Manufacturing)

Solution

Components

• CPS

• Self-configuration

• Virtual representation

• Context-aware

• Information

management

Benefits

• Increased flexibility

and agility

• Coping with

complexity

New customer order: We need

an extra shift on Saturday.

I need to go home

now. Who can take

over my orders?

I can work on

Saturday.

Sorry, I’m not

available on Saturday.

I have to be at the goods

issue in 2 hours!

I’m booked out till

Friday!

Magazine will be empty

soon, please refill!

Source: http://www.gereports.com/ Source: ThingWorx

Source: http://www.fastwayengineering.com/digital-twin/

PREDICTIVE MAINTENANCE

https://authentise.com/news/tag/digital-twin/

Source: GE Look ahead Posted September 30, 2015

https://cmfenews.com/

MECHANICAL OR ELECTRONIC?

COMPLEX COMPUTER ON FOUR-WHEELS

COLLABORATIVE CLOUD ROBOT (COBOT)

• No integration

• No programming

• Work intelligently

• No need to be in the cage

• Robot OS: extendable platform

• Cloud robot

Source: Rethink Robotics

Automatic Optical Inspection

Automatic Optical Inspection (AOI) plays an important role in the steel making industry. AOI

techniques are used to inspect the surfaces of objects to reduce defective products with high

precision and speed. In the inspection process, an AOI device acquires image of the object

under inspection using an optical imaging system, and then identifies the type of defects by

matching the input image with known template.

Wang, F. et al. 2019

Industrial Problem

Background and foreground defects (marked) of steel image as illustrated above, the main

challenge is to detect and locate defects as positive examples with varying sizes in a wide

background area as negative example.

Positive example

Negative example

Result Comparison

The experimental results showed the performance propose pipeline detected three type of defect

location with higher confidence score. The system also can detected smoothly different scale or

size of defects location.

Kesimpulan

I N O V A T I F - M A N D I R I - T E R K E M U K A

FUTURE TECHNOLOGICAL ENVIRONMENT

IoTLiquefaction of the

physical world

DataThe new mines

Big Data AnalyticsThe new math

BlockchainThe new Internet of

value and ownership

Computational

Thinking

BioThe new digital

Towards

Outcome Economy

and Pull Economy

Evolving …

AIReplacing jobs

Thank You

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