IIoT發展趨勢及設備業者因應之道_微軟葉怡君

1. Cathy Yeh 葉怡君
物聯網亞太創新中心 總經理
雲端暨人工智慧研發集團
工業物聯網發展趨勢
及設備業者因應之道

2. Agenda
• 工業物聯網發展趨勢及微軟策略
• 智慧製造應用實例
• 工業物聯網創新商務模式 - 以AOI 雲為例

4. IoT is in the critical path of innovation

5. And we know Industrial IoT is not Consumer IoT!

6. 在創新轉型趨勢之下，全球製造業的現況與挑戰 (一)
產品生命週期縮短 –
客戶需求走向個人化，大量生產
轉為少量多樣
科技加速進步，營運決策大不易 –
大數據時代，營運環境快速變動、
決策過程中不確定性、時效以及風
險遽升
產業生態改變及鏈重組–
科技、貿易全球化以及政經局勢
的影響之下促成製造業產業轉型
及產業鏈重組

7. 在創新轉型趨勢之下，全球製造業的現況與挑戰 (二)
O
E E
研發資本投入高，財務風險越
來越高-
各產業對於機台實務應用均有
特定規範與設定，面對產線調
整與設備設定更新曠日廢時難
以跟上產業變化的腳步。
勞力成本節節上升，經驗傳承
成為難題–
勞力成本節節升高，老師傅經
驗卻難以傳承，產業技術人員
出現斷層。
資訊流動緩慢 –
公司內部不同事業單位資訊系
統互不相通缺乏整合，新舊系
統無法融合；影響決策速度同
時也難以根據客戶需求變化即
時並且精準備料及調整產線。

8. GET INSIGHTS
Getting near real time
insights is difficult and time
consuming due to
disconnected data across
regions and product
REDUCING COST
Sub-optimal monitoring
capabilities prevent
manufacturers from reducing
the cost of service and
remaining competitive
NEW REVENUE
Uncontrolled costs and risks
make it challenging to secure
support for creating revenue
streams through new
innovative services or
business models

9. Connected chillers are
back online 9x faster
than unconnected
equipment, avoiding
more than $300,000 in
hourly downtime costs
Data from sensors and
systems to create
valuable business
intelligence and reduce
downtime by 50%
Reduced its accident rate
by 25% and fuel usage
by 20%, reporting
annual savings of $1.8
million
Cut down-time cut for
each packaging line by
up to 48 hours, saving
€30,000 for customers
Keeping farmers informed
about irrigation, disease
control diseases, and pest
has led to increased yields
of 30%, and a 20%
reduction in water use
Rolls Royce “power by the
hour” model provides
maximize availability by
cutting fuel consumption
by 1% and up to $250,000
per plane, per year.
Access to production and
supply chain data worldwide,
reduced downtime costs by
as much as $300,000 per day
Licorice extruders on
Twizzler’s production
line are performing at
peak optimization,
saving over
$500K/year on
materials alone
Enabled customers to
transport more than
1M additional tons of
cargo, and reduce fuel
consumption by 17%

10. 微軟工業物聯網策略 – 結合產業龍頭 帶動創新
Enable innovation that matters to the industry on Microsoft and Microsoft partners
Digital Twin
Smart
Manufacturing
Asset
Management
Predictive
Maintenance
Field Services
Quality
Assurance
Others…
Compute, Network, Storage, IoT, Data & AI platform, Security, Open platform
Stability/
Quality
New business
model
Capacity
planning
Minimize
unplanned
downtime
Improve
workplace
safety
Compliance Others…

12. 智慧製造數位轉型各大階段
“Pay-as-you-go”,
Outcome-based
products
Products that never break
“New business models”
Services
7
Digital feedback
loops,
Functions
How can an autonomous response be achieved?
“Self-optimizing”
Adaptability
6
AI Models,
Machine
Learning
What will happen?
“Being prepared”
Predictions
5
Time Series
Insights,
Hierarchical
Data Modeling
Why is it happening?
“Understanding”
Transparency
4
Telemetry
Dashboards
What is happening?
“Seeing”
Visibility
3
Edge Gateways
How to Connect?
“Plugging in”
Connectivity
2
PLCs/IPCs
What Data?
“Defining Tags”
Computerization
1
Value
Time設備聯網 數位化 數據分析可視化 可預測化 自動因應 服務化

13. PREDICTIVE ANALYTICS
I N FACT O RY OF THE FUTU RE
AT JABI L
▪ Improving Quality
– Predict downstream defects products in
upstream processes and evaluate the
impact to production BEFORE they happen
– Advanced statistics for early warning
detection of quality processes going out of
control long before they happen
▪ Equipment Optimization
– Machine learning algorithms used for
autonomous equipment adjustments and
M2M with no operator intervention
▪ Increasing Equipment Uptime
– Avoid unplanned downtime by predicting
future equipment failures
– Optimize maintenance schedules and
reduce costs

14. • Majans uses Zeiss Corona process measurement for failure
detection and quality control, which are mounted in-line and
checking moisture/salt, and there are only 3 such Zeiss Corona
spectrometers in the world. However, the interface to this only
speaks OPC DA.
• IIoT helped ZEISS to connect OPC DA to OPC UA, and also
enabled this at Majans for the real-time streaming of Zeiss
Corona process measurement into Azure IoT Hub. The data
flow ingests 15 PLC tags/measures to IoT Hub using the OPC UA
Publisher, which is running as a native .NET core app on an
Omron Industrial PC (IPC). This way we had nodes available via
OPC UA to synchronize with the OPC DA tags from the ZEISS
OPC Server.
• The measurements may be small (just 5 parameters for salt,
moisture and 3 more for color) but very important to our
customer for establishing quality in their products. Having the
capability to do this real-time is a big achievement for this
industry (versus a QA/QC sampling lab).
Majans – Quality Assurance

16. 緯謙應用案例

17. 緯謙應用案例

18. User experiences
Dashboards Mixed Reality Interactive speech Gestures
Preconfigured Azure IoT Suite and SaaS applications
Remote monitoring Predictive maintenance Connected factory Microsoft IoT Central
Analytics and artificial intelligence
HDInsight Machine
Learning
Data Lake
Analytics
Azure Time
Series Insights
Bot
Framework
Operations
Technology
Enterprise business processes
PLM ERP SCMCRM
Home
IT architecture
EdgeAnalyticsDeviceAgent
StreamAnalytics
onedge
Logic
Apps
API
integration
BizTalk
Services
Azure StackSQL Server
MES & Enterprise IT Business integration
Hot path analytics and application platform
Cold path analytics and storage
Stream Analytics Event Hubs Service Fabric (Actors) Functions
Data Factory DocumentDB SQL Database Data Lake Store
Field Gateway
Cloud Gateway
Azure IoT Gateway
Azure IoT
Hub
(device
provisioning)
Cognitive
Services
L3: Mfg Ops
Mgmt, MES,
CAD, PLM
L2: Supervisory
Control,
SCADA,
HMI
L1: Plant
Control PLC,
DCS, IPC
L0: Physical
Equipment,
I/O, Devices,
Sensors
L4: Business
Planning

20. 應用實例 – 惠特LED檢測雲服務

21. 從機械雲, 檢測雲到智慧製造
Microsoft’s Infrastructure & Data Platform 開放整合的數據平台
(Open, Common Data Model concept)
新舊機台聯網 Connect your “Things” (Greenfield or Brownfield)
快速部署各場域應用 Onboard/ Off board “Use Cases”
Predictive
Maintenance
預保維修
CAD/CAM
加工模擬管理
CNC
Calibration
機台校正
AI for QA
瑕疵檢測
OEE
產能優化

22. Recognition: Microsoft is recognized as the first to…
Microsoft is a leader in
the Forrester Wave for
IoT Software Platforms
Microsoft is a Leader in
the IDC MarketScape for
IoT platforms across
various use cases
Microsoft is a leader in the
Research Leaderboard
assessment of strategy and
execution for 15 IoT
platform providers
Azure IoT is the only
cloud platform that was
determined as best in
class in every category
• Deliver IoT solution accelerators | SaaS and PaaS for IoT | AA/AI at the edge
• Solve device provisioning at scale | Support OPC UA for manufacturing