accelerating smart manufacturing with connected …...accelerating smart manufacturing with...

Accelerating Smart Manufacturing with Connected Machine Services

從智慧機械到智慧製造

Deh Hui Chuan / Andy Li

Strategic Engagement & Industrial IoT

Azure IoT R&D

Myth# 1: Manufacturing plants are standardized and homogeneous…

Reality: There are many protocol and HW to deal with and there is no winner in this war…. In short, the Brownfield

No winner in the field bus/industrial

ethernet war!

Myth#2: We just need to focus on building our next future factory…. Why do we still need brownfield?

1960s - 1970s 1980s 1990s 2000s 2010s

1968

1978 1989 1993 2001

1982 19951973 2002 2009 2011

2006

2018

Reality: You invested in various protocols and HW/SW over time…

1940s-1960s: 1st- 3rd gen NC

1961: 1st robotic arm

by Unitec

1950s: 1st SCADA

appears to work

with telephone relay

system….

Myth#3: I just need an end to end vendor to help me out in my entire manufacturing value chain….

Raw materials

Manufacturing plant Engine transportation

Engine tracking

Machine processingMachine transportationProduction line Machine tracking

Machine assembly

Machine transportation

Microsoft Azure enables scale through IoT PaaS services

▪ Azure enables Top 10 automation companies to leverage secure-by-default Azure IoT PaaS and focus on value creation

▪ Azure partners with builder ecosystem to offer predictive maintenance solutions, bundled with machines

▪ Azure enables manufacturers to focus on process optimization through digital transformation

Automation Companies Machine Builders ManufacturersGateway and SI

• Azure leverages specialized solutions integration to focus on process optimization; connectivity specialist for OT/IT interoperability.

Reality: There will be an ecosystem of experts that comes together in support of your value chain…

The Top Automation Companies today run on Azure IoT…

Azure-Powers up most Industrial IoT Edge Gateways and Solutions in Market today…

Myth#4: Let’s build some dashboards, AI models and have my Connected Factory up & running today!

Connected

Factory as a

Service

Result

Digital

Feedback

Loops,

Method Calls

Adaptability

AI Models,

Machine

Learning

Predictions

Time-

Series/Historic

al Data,

Hierarchical

Data Modeling

Transparency

Telemetry

Dashboards

VisibilityConnectivityComputerization

Value

Time

Reality: 7 step journey in Digital Transformation, you can always leapfrog but have you solved Steps 1-2? (Connected Machine)

Connected

Factory as a

Service

Increased Business Value

Optimized processes

Result

7

Digital

Feedback

Loops,

Method Calls

Taking action

“Self-optimizing”

Adaptability

6

AI Models,

Machine

Learning

What will happen?

“Being prepared”

Predictions

5

Time-

Series/Historic

al Data,

Hierarchical

Data Modeling

Why is it happening?

“Understanding”

Transparency

4

Telemetry

Dashboards

What is happening?

“Seeing”

Visibility

3

How to Connect?

“Plugging in”

Connectivity

2

What Data?

“Defining Tags”

Computerization

1

Value

Time

Many are looking to go

through Steps 1 & 2

Connected

Machines first

First, it’s Connected Machines, then it’s Connected Factory

Azure IoT

ecosystem (to enable brownfield &

greenfield scenarios)

Azure IoT

platform and

services

Azure Data

Platform and

AI

Azure D365

and 3rd party

providers(SAP, etc.)

Connected

Factory as a

Service


Optimized processes

Result

7

Digital

Feedback

Loops,

Method Calls

Taking action


Adaptability

6

AI Models,

Machine

Learning

What will happen?


Predictions

5

Time-

Series/Historic

al Data,

Hierarchical

Data Modeling


“Understanding”

Transparency

4

Telemetry

Dashboards

What is happening?

“Seeing”

Visibility

3

How to Connect?

“Plugging in”

Connectivity

2

What Data?

“Defining Tags”

Computerization

1

Value

Time

Connectivity: Open,

Secure and Extensible

Standard – OPC UA

Edge Computing

OEE: Remote Monitoring,

Predictive Maintenance

Quality Control: AI for

Defect Inspection

MES/ERP Integration

Process Optimization

Adaptive AI for Mfg

ActionsThings Insights

… so let’s go back to that thing call Brownfield and let’s figure out how to standardize to OPC UA… but why?

VDMA released a Semantic Interoperability/ Companion Specs guidance to various industries

But you haven’t told me why standardize? Well…. What if everyone spoke different languages… how do you draw insights looking at different data models?

Connected

Factory as a

Service


Optimized processes

Result

7

Digital

Feedback

Loops,

Method Calls

Taking action


Adaptability

6

AI Models,

Machine

Learning

What will happen?


Predictions

5

Time-

Series/Historic

al Data,

Hierarchical

Data Modeling


“Understanding”

Transparency

4

Telemetry

Dashboards

What is happening?

“Seeing”

Visibility

3

How to Connect?

“Plugging in”

Connectivity

2

What Data?

“Defining Tags”

Computerization

1

Time

Insights

… and that is why Azure Industrial IoT is built for open-ness and interoperability.

Presentation & Business Connections

Websites, Mobile Services

Dynamics, Notification Hubs

Azure Edge Analytics,

Azure ML on Edge,

Azure Functions,

Azure Edge Runtime


Azure ML on Edge,

Azure Functions,

Azure Edge Runtime

Azure IoT Edge

On-Premises: Machine Interoperability Azure Cloud: Data Ingestion & Processing, Command & Control Azure Cloud: Presentation

Indu

stri

al D

evic

es(O

PC U

A S

erve

rs)

Hot Path Analytics:

Azure Stream Analytics, Azure Time Series Insights…

Azure IoT Hub

Connected Factory Solution Accelerator:

OEE, KPIs calculation

Alarms, Events & Telemetry based on OPC UA Information Model

Cloud-based Device Management

OPC Client using OPC UA .NET Standard stack

OPC Publisher Module

Firewall

Cold Path Analytics, ML, Functions & Storage:

Azure Machine Learning, Azure Data Lake, Azure CosmosDB Graph…

UA Client/Server

(UA Binary)

UA PubSub

(JSON over AMQP/MQTT)


Azure ML on Edge,

Azure Functions,

Azure Edge Runtime

Micro-Services: OPC Twin, OPC Vault

OPC Twin & Proxy Modules

UA Client/Server

(UA Binary)IoT Edge Methods/Properties

& UA Client/Server (UA Binary over MQTT)

Hard truths summarized: Industrial IoT is after all NOT Consumer IoT

Manufacturing

environment is

complex by nature

• Long life cycles to

modernize

machinery

• Isolated business

processes

• Security and liability

challenges

Integrations and

platform

• Machines cannot

easily be replaced

($$$)

• Must run for over

20 years or more…

Interoperable

• Must be

interoperable to

avoid vendor lock-in

Complex Ecosystem

• Require ecosystem

to optimize

automation

processes and

enable new

business models

Use case sharing

▪ Producer and distributor of specialized plastics

▪ Five production sites

▪ Each site has two to six extruders

Use Case

▪ Samples are analyzed for quality control,

every two hours

▪ Cost for one sample: €50

▪ Total cost per month (eight samples

per day per extruder, 20 extruders,

20 days per month):

€160,000

The Business Case

▪ “Classic approach“

• Buy expensive hardware

• Do everything on-premise

▪ Cloud centric approach

• Use cloud technologies

• Start small

• Grow if successful

Two Options

End-to-End Solution Overview

OPC UAOPC Classicbrownfield• Siemens• Rockwell• Mitsubishi• …

Process andmachine data Other applications and services

Azure IoT Suite Connected Factory• OEE• Analytics• …

• dataFEED OPC Suite• OPC Proxy (Azure IoT Edge) • OPC Publisher (Azure IoT Edge) • Windows 10 IoT Enterprise• HPE GL20

The Result

Customer CTO: ”We wouldn‘t have achieved this that easy and without big investments if we had done this on premise.“

Initial cost Millions vs 6 digit cost12 months vs 10 man days

What did we learn from the case above on why cloud?

Fast

Scalability

Financial

Flexibility

… but not just that, security is also the biggest reason why cloud

Security Availability

Data

SovereigntyLiability

Microsoft Azure enables scale through IoT PaaS services

▪ Azure enables Top 10 automation companies to leverage secure-by-default Azure IoT PaaS and focus on value creation

▪ Azure partners with builder ecosystem to offer predictive maintenance solutions, bundled with machines

▪ Azure enables manufacturers to focus on process optimization through digital transformation

Automation Companies Machine Builders ManufacturersGateway and SI

• Azure leverages specialized solutions integration to focus on process optimization; connectivity specialist for OT/IT interoperability.

Remember we said we will come back to this picture to look at the Machine Builder side of the story?

Why? Because over 40% of Asia’s manufacturing exports are derived from making parts & components (upstream)… all relying on machineries to make it happen!

… there is a whole lot that needs to work in these machines. And this is a use case we are working on…

Which will see a whole new Managed Service Model being applied, truly bringing the value from connected machines to connected factory.

Connected

Factory as a

Service


Optimized processes

Result

7

Digital

Feedback

Loops,

Method Calls

Taking action


Adaptability

6

AI Models,

Machine

Learning

What will happen?


Predictions

5

Time-

Series/Historic

al Data,

Hierarchical

Data Modeling


“Understanding”

Transparency

4

Telemetry

Dashboards

What is happening?

“Seeing”

Visibility

3

How to Connect?

“Plugging in”

Connectivity

2

What Data?

“Defining Tags”

Computerization

1

Time

Managed

Service

Model

工具機(CNC)智慧工廠服務化

CNC Controller

DAQ

VimoNet

CNC

Sensor : • Accelerometer• Ammeter • Thermometer• …

BNC

USB

RJ45

Ethernet

Pre-install Azure IoT Edge & VMX software • Support various commercial CNC controllers, PLC and

DAQ.• Move cloud analytics and custom workloads to device

securely. Such as data normalization, ML Model, OEE engine…

• Perform anomaly detection on the device itself and respond to emergencies as quickly as possible.Intelligent Machine Box

Azure Market Place

• For Customer• One simple place to discover all the

capabilities that can be deployed to an the edge device.

Azure IoT Hub & Edge• Seamless deployment of AI and advanced analytics from

cloud to the edge• Centralized configure, update and monitor from the cloud

• All the modules are certified for quality and scanned for security vulnerabilities.

• For Service Provider• Publicize and monetize your IP• Bill anyone using the module securely, automatically, and

without writing a bunch of sensitive billing logic.

工具機(CNC)智慧工廠服務化導入成本預估

CNC 雲端智慧製造Jerry Hsieh 謝尚亨

GM 總經理

CIMForce International 上博科技

Professional quality, definitely worth your trust.


CNC精銑(Bo面)CNC精銑(T面)EDM加工(T面)WE加工(T面)

傳統鐉(鉆) CNC粗銑(Bo面) CNC粗銑(T面) 熱處理備料

傳統研磨

鐵塊零件


CNC機台

加工坐標

程式

刀具

裝夾

機台通訊與監控

工件資訊

機台資訊

刀具資訊

治具資訊

•機台型號•加工程式格式•上傳的網路IP•機台監控

•工件裝夾要求•治具型號

•機內/機外校正•工件加工坐標原點補正值

•刀具/刀把型號•刀具安裝伸出長•刀具之ATC刀號

•加工程式版本•切削程式順序•程式對應刀號•冷卻指令

• IoT技術應用•加工資料與機台訊息上/下傳•主軸負載與電流監控


效率低LAN SERVER

CAM手動編程

手動上傳加工程式

加工任務通知

現場加工

人工發行圖面

生產管理準備材料

手動下載加工程式至機台

易出錯


機台零件

治具刀具材料

收費

CAPP/MES

FMSMULTITASKINGLATHEWEDMEDMCNC 量測

MONITORING (機台監控) 數據傳輸

量測程式

Auto-CAM

自動佈點

切削模擬

線割程式

雲端運算CAD/CAM

PLM/ERPAPS

INTERFACE

…

1. 加工資源共享媒介服務2. 機台監控

(INTRANET/INTERNET)3. 雲端運算4. 雲端數據儲存5. 資源數據共享平台

…


雲端資料庫

刀把資訊刀具資訊捨棄式銑刀捨棄式刀片金屬材質加工條件

常用刀

雲端資料庫

Cloud

LOCAL

同步儲存

Hybrid

Adapter…

Adapter 切削模擬

Cloud

AutoCAM


雲端資料庫

同步儲存

Cloud

Hy

brid

機台規格參數機上量測測頭刀具測量

雲端資料庫

…

機台類型控制器 MQL 回霧回收

LOCAL

機台編號管理

機台與治具底座配置

刀具管理主程式產生機台3D模型

Cloud

切削模擬Adapter

Adapter


雲端運算機台型號

CAM編程

機台資訊管理刀具資訊管理

數據更新啟動CAM 打開模型 CAM編程程式上傳加工模擬模擬確認

雲端存儲

治具資訊管理

LocalDB

根據規則篩選機台/治具/刀具

刀具/刀把/刀組數據治具數據/3D模型

•機台數據•後處理器

系統自動輸出之資料與數據• e工單資訊: 使用刀組/切削順序/…•檔案: CAM檔/裝夾圖&JT/模擬模型/…• POST之路徑加工程式/…

•模擬報告• 3D模擬動畫•優化之加工程式

Hybrid

Local

Cloud

機台+治具底座3D模型

•模擬模型•加工程式

模擬運算


來料接收指派機台

加工任務管理刀具資訊管理

手動CNC加工

各機台虛擬刀具庫資訊•刀具編號/規格•刀具現存壽命

機台工件加工任務資訊

更新機台負載資訊

生管人員

加工任務導入

•工件加工任務資訊(件號/版次/數量/…)

雲端運算

雲端存儲

治具管理

加工任務管理

工件機外裝夾/校正

•治具型號與檢校有效期確認•治具狀態資訊更新

•工件RFID編碼•工件加工原點坐標補正值

工件上機掛換刀

•工件件號•機台編號/IP

•選擇之機台加工坐標

更新實體機台刀具庫資訊:ATC刀號/刀組ID

產生主程式

主程式產生器運算

•機台編號/控制器型號•工件件號/程式版本•子程式名稱/切削順序•程式粗精銑性質•掛刀數量/程式對應刀號•刀具冷卻方式•刀具伸出長•選擇之機台加工坐標•工件加工原點坐標補正值• ...

加工主程式

程式上傳機台開始加工

•加工主程式•加工子程式

更新工件加工任務狀態資訊

Hybrid

Local

Cloud


Web API

Web API (Ajex)html (jsp)

Web API

Web API

MSMQ

Windows

Edge Computing

C#

ECS Sever

Web API

Identity ProvidersAuthorizations

Token,Jwt

Windows

Browser

Angular 5

Client

C#

CAD/CAM software

Client

Windows

Web API

API Gateway Server

Java

Windows

Spring Boot

SQL Database

Java

MES AP

MicroService

Windows

Spring Boot

Eureka

Machine B

Controller B

Machine A

Controller A

Background Application

Windows

C#

NX

NCS

ESPRIT

...

Task Manager

C#

Task Dispatching

Windows

file

Linux

Machining Program

Apache

FTP Server

3D Model

file


• 刀具管理• 治具管理• CAM編程管理• 加工模擬• 加工任務管理• MES

Microservices

VM

製造模組微服務

Browser CAM

機台控制模組(ECS)

IoT Edge


機台控制模組(ECS)

EdgeComputing IoT Edge

Optical Sensor

RFID

•儲位資訊•工件資訊

•工件搬運指令•夾爪更換指令

•加工程式傳送•即時狀態監控

ECS

ECS

•即時狀態回報•歷史狀態回報

•加工任務

狀態資訊

•加工任務資訊•工件資訊•設備狀態資訊• …

加工程式加工程式

加工任務

CloudComputing

•自動編程•加工模擬• …

•加工任務導入•機台/刀具/治具資訊

•資訊看板-加工進度/機台狀態/稼動率/報警記錄/…

CloudLocal


FMS

CMM自動編程Auto

-CAM

CloudComputing

NCS加工模擬

CMM報告生成

資訊看板


系統產品方案定位考量

考慮資安問題，客戶希望系統建在內部

由單一模組開始導入再逐步增加功能!

單一功能模組居多(SERVER建置在雲端)

客戶數量佔比 <10％ <=30% ~60%

商業模式方向全模組銷售+維護費模組銷售或雲端(配合合作夥伴)

雲端服務、按機台每月收費

銷售策略提供全模組及單一功能先單模組、再整個系統網路服務、租賃為主

伺服器私有雲可以使用混合雲或私有雲使用公有雲

依不同客戶需求、提供不同商業模式與服務

私有雲公有雲混和雲

外包服務


平台服務

雲端計算

技術情資

SOHO

廣告

中/小企業

中/小企業

中/小企業

中/小企業

中/小企業

中/小企業

集體採購

外包服務的機會

•外包作業困難

•品質不穩定

•交期無法控制

•價格差異大

電子商務(買/賣雙向服務)

中小企業

客戶

出售製造資源(產能)

購買設備/原物料/耗材/培訓/認證/人才資源/…

購買製造資源/原物料…

賣買SOHO客戶

設備廠商

精密機械零件廠商

出售刀具/治具/工具/耗材/…

•技術支持•外包管理• SOHO•教育訓練•認證•稽核服務• UBER服務•…

…

…

…

Partners & Microsoft come together for your Industrial IoT requirements as with the examples you saw earlier

VMs, VNet, KeyVault, Active Directory, Resource Manager, Azure Portal, …Globally Available Edge/Private/Public Cloud Infrastructure (IaaS)

IoT Edge, IoT Hub, Time Series Insights, CosmosDB, AzureML, …Scalable, Managed Services for Common Patterns (PaaS)

Connected Factory SA, OPC Publisher, OPC Proxy, OPC GDS, OPC Twin, …Scalable Services for Manufacturing Interoperability and Data Modeling

Services for Specific Use Cases

Applications that Solve Business ProblemsA

zure

Part

ner

From Connected Machines to Connected Factory –value add to all parties in the ecosystem

For Manufactures

• Productivity: counter labor

shortage

• Global Operation: efficient supply

chain management with better

data transparency and

integration.

• Mass Production vs Mass

Customization: Need to nimbler

to adjust production capacity.

• Risk Management: Data

governance and trade-war.

For Machine Builder

• Value-Added: Offer turn-key

solution to support whole

production line, not just a single

station

• Global services: Offer remote

consultant services to

international customers through

packaged solutions, carried by

cloud

For System Integrator

• Extend business to SMB, who are

usually lacking IT capacity to

manage on-prem servers and

customization.

• Extend footprint to global market,

to support cross-country business

and operation

• Scale their solution by leveraging

Azure data and advanced analytics

services without worrying about

operations.

• Accelerate their DevOps cycle by

leveraging IoT/AI assets on Azure,

no need to re-create the wheel.

accelerating smart manufacturing with connected …...accelerating smart manufacturing with...

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