presented by asst.prof.dr. diew koolpiruck

King Mongkut’s University of Technology Thonburi

Cyber-Physical System in Manufacturing

12/03/2018

Presented by Asst.Prof.Dr. Diew Koolpiruck

12-13/03/2018 NAC 2018

AGENDA

01: Introduction 02: iStarch: industry 4.0 exercise for starch manufacturing 03: Future direction

02: iStarch project: industry 4.0 automation system

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Source: Andrew MaAfee, Erick Bryjolfsson

http://www.moddb.com/mods/cyberpunk/images/cyberspace

Cyber Space: Cyber physical + Digital human + …

http://design-engine.com/thingworx-augmented-reality-and-iot-in-the-workplace/

Cyber physical via Cyber physical system

Source: Werner Steinhogl, European Commission

Cyber physical system evolution

Digital human

Digital humanity evolution

Socio-Technological System

01: Introduction

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Source: Andrew MaAfee, Erick Bryjolfsson

02: iStarch project

02: iStarch project: Motivation

27%

15%

12% 11%

8%

27%

World Tapioca Root Production

Nigeria

Thailand

Indonesia

Brazil

Congo

Other

80%

10%

2%

1% 1% 6%

World Tapioca Product Export

Thailand

Vietnam

Indonesia

China

Brazil

Other

Harvested area:

1.4 Million hectare

Root productivity:

22.6 tons/hectare

(World average 12 tons/hectare)

0.00

5.00

10.00

15.00

20.00

25.00

30.00

35.00

40.00

45.00

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Valu

e (

tho

usan

d m

illio

n b

ah

t)

Thailand Tapioca Starch Export Value

Main tapioca root Chips Pellets Starch

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02: iStarch project: Motivation

Most Operated manually by workers

Decision based on worker’s experiences

Product quality unstable

Take a long time to diagnose abnormal operation

More than 50% of starch factories in Thailand are manually operate

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02: iStarch project

Process engineer

Systems engineer

Factory

Challenge: cost-effective automation with intelligent manufacturing. Manual ----> Intelligent automation

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Data type Level, temperature, pressure, flow rate

Time Frame Minutes, second

Operator station

Controller

Manufacturing Execution System

Enterprise Resource Planning

Process Control System

Production Line

Information Yield, loss, Performance Time Frame Shift, hours, minutes, second

Information Material, delivery, inventory Time Frame Months, weeks, days, shifts

(ISA 95)

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PIMS

EMS

LIMS

Unit I CPS

PIMS

EMS

LIMS

Unit 3 CPS

PIMS

EMS

LIMS

Unit 2 CPS

PIMS

EMS

LIMS

Unit 1 CPS

Energy Management System

Production Information Management System

Laboratory Information Management System

Modeling and Control Control Control

Math model

Control

Math model

Control

Math model

Math model

Vert

ical

Inte

gra

tio

n

Horizontal Integration

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02: iStarch project: Our system architecture design

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02: iStarch project: Our system architecture design

Tapioca tuber

Dry Sieve

Washer

Chopper

Rasper

Extractor

Separator

Dewatering

Flash dryer

Hot cyclone

Cool cyclone

Packaging

Air Heater

Product

Moist. Starch

Starch + Hot air

Starch + Air

Starch

Hot air

Hot blower

Cool blower

Fuel

Water

Air

Hot air

Air

Water

Water recycled

Waste water

Sands

Clean tapioca tuber

Tapioca chopped

Pieces of Tapioca

Pulp of starch

Residue of starch

Starch water

Sulfur water

Tapioca tuber

Water recycled

PIMS

EMS

LIMS

Extractor Unit

CPS

PIMS

EMS

LIMS

Separator Unit

CPS

Control Control

Mathmodel

Mathmodel

Machine cyber-physical system

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02: iStarch project: CPS design Cyber-Physical Stack Property in Flash Dryer Unit

Include :

Energy Management Service (EMS)

Energy per kilogram Energy quality control of flash dryer unit

Include : YieldUtilizationCapacityQuality control of starch moisture

Production Information Management Service (PIMS)

Include : Percent of starch moisture inletPercent of starch moisture outlet

Laboratory Information Management Service (LIMS)

Include : PID control of starch outlet

Temperature measurement: input, outputOutput starch feed in: adjust a speed conveyer

Control Function

• Auto/Manual State• Process variable, Set-point, Controller output• Gain parameter: KP, KI, KD

Include : Input parameters

Output parameters

Intelligent function

• Starch feed rate• Starch moisture inlet• Air temperature inlet

Mathematic Models

• Starch moisture outlet• Air humidity outlet• Air temperature outlet

• Moisture estimation

PIMS

EMS

LIMS

Control

Math model

• The structure of information model of flash dryer unit is

shown in this picture.

• Flash dryer unit information model developed based on

Microsoft .NET framework using OPC UA base object

types, variable types and reference types.

• Services of machine CPS is consisting of EMS, PIMS,

LIMS, Control function, Mathematical Model.

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02: iStarch project: CPS design

Fuel burner

Screw feeder 1-2

Screw feeder 2-2

Screw feeder 2-1

Screw feeder 1-1

Hot Cyclone

Hot air

Cool Cyclone

Cool a ir

PACKING TANK

Mixer Tank (old)

Mixer tank (new)

Conveyer 2-2

Fuel oil

Wood burnerFirewood

VSD

M

Conveyer 1-2

M

703TI

TI703

704TI

TI704

TI705

M

M

705SIC

VSDM

M VSD712SIC

711SIC

Tube 1

Tube 2

1 2

702TI

TI702

701TI

TI701

2

1

1

2

M

M

Starch

721TI

TI721

722TI

TI722

Conveyer 1-1

De-watering

De-watering

De-wate ring

Flash Dryer

Model

Air Humidity.

Air Temp.

Starch Moisture.

Starch Feed Rate.

Air Temp.

Starch Moisture.

PIMS

EMS

LIMS

Flash Dryer Unit

CPS

Control

Mathmodel

starch moisture estimation

MT

MC

starch moisture control

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• Plant CPS and machine CPS were designed by OPC-UA and develop by .NET framework.

Plant CPS Machine CPS

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02: iStarch project: infomation services

Public-Cloud

Private-Cloud

Cloud Gateway

OPC-UA

IoT Gateway

REST Server

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02: iStarch project: infomation services

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02: iStarch project: Production monitoring Starch Production Monitoring Project Home Dashboard Report Filling Forms

Separation Unit

Per

form

ance

(%)

Hydrocyclone section

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02: iStarch project: Production reports

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02: iStarch project : Web HMI

02: iStarch project: Laboratory information management

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02: iStarch project: Hardware implementations

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03: Future works

03: iStarch project: Future works

• Expert system

• Predicted alarm

• Optimization

Intelligent functions

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presented by asst.prof.dr. diew koolpiruck

Documents