Industry

4.0
What is it and what does it mean for businesses?
 We’re entering the fourth revolution of industry
Complexity

Cognitive
Manufacturing
Miniaturization & Cyber-physical
Global Scale systems: sensors, big
data, predictive
Electrification & Embedded systems: analytics, cognitive
Automation Semiconductors,
Line computing, cyber-
computers, physical systems,
Production Assembly systems:
information robotics, 3D printing
Lighting, electricity
Water, steam, and technologies and
and assembly lines
conveyors; modern increase in trade
materials handling
1783
1870 1960 2020
Era
Improve Operation and lower cost Enhance Customer experience
Transform and generate new revenue streams
IBM Industry 4.0 Cognitive & Digitization Platform

Focused on: Focused on:

=> Operational Excellence => Data-driven Business Models
Focused => Costs Reduction => New Revenue Streams
Pain points => Manufacturing performance and quality => Remote Control IoT Services
=> Process Automation & Smarter Resources => Intelligent products

Make & Use Design & Use

Twin
Approach Connected Process Innovation & Discovery Connected Product

Analytics Cognitive Learning Automation

Edge Weather Blockchain Security

IBM Industry 4.0

IBM$Watson$IoT$Platform
Cognitive &
Digitization Platform
Cases…

Connected Products Connected Operations

Leverages cognitive capabilities to enable Analyzes data from connected products,
clients to accelerate technical and business facilities, and equipment to improve reliability,
innovation by adopting agile processes at scale reduce downtime and improve process quality
and connecting real-time data and efficiency

Accelerate Business Innovation Enhance Asset Performance

To enable new sources of revenues with actionable Reduce cost by improving maintenance, reliability,
tracking of operations, maintenance, monitoring, availability and planning of physical assets; Manage
updates and new services installation, service and repairs of systems and
equipment

Accelerate Technical Innovation Improve Operations Efficiency

To reduce development cost and increase
Drive process efficiency, reduce cost and
differentiation and competitiveness by leveraging
increase revenue by improving quality, yield and
Agile processes at enterprise scale
operations; Help identify where warranty-
eligible defects are arising and determine why
they are occurring
 The Ingredients of

Decision Making
Predictive Analytics
Real-time Analytics
Real-time Action
Edge Analytics with Machine
Context Learning
Business Automation
Weather data
Social data
Industrial knowledge
Connectivity Data Mining
Platform of platforms Textual Analytics
API Economy Video/Image Analytics
Embedded Security Natural Language Processing
Data
IoT Data
Data Platform (BigData,
Dake,IoT Data Platform)
Embedded Security
How it mapped into Economic Financial Activities?
• The digitalization of banking and financial services
• Automation (internal and external)
• Focus to customer experience, speed up the analyzing existing data and Omni-
channel
• Simplify regulatory compliance with information transparency

• Cyber-Currency?
• Peer-to-Peer transactions
• Distributed ledger

• Security and Fraud

• Managing the Identity and Access Management,
• Data Security
• Network
• Financial Malware
Technology behind the scene
11
Technology Set 1 : Blockchain & IoT • IBM Watson IoT platform
enables IoT devices to send data
to private Blockchain ledgers for
inclusion in shared transactions
with tamper resistant records.
• Blockchain’s distributed
replication allows your business
partners to access and supply
IoT data without the need for
central control and
management. All business
partners can verify each
transaction, preventing disputes
and ensuring each partner is
held accountable for their
individual roles in the overall
transaction.

12
• Blockchain for Business…

Shared,
replicated, Blockchain
for
permissioned
Business
ledger
• Requirements of blockchain for business

Participants Choosing Transaction

decide which what to Endorsement Participants
assets to share give provable
share endorsement

Participants
know who they Information
are dealing shared via
Privacy and need-to-know
with
Identity Confidentiality
Technology SET 2 : bigdata & analytics

We need to Find it, Extract It, Refine It,

Distribute it and …
Monetize It
DATA sources?

IBM Cloud / DOC ID / Month XX, 2017 / © 2017 IBM

16
Corporation
The Challenges The Collection of Data
Which One do you prefer?

17
Analytics Maturity Curve
• The Building Blocks of Data & Analytics

CAPTURE SECURE ANALYZE OPERATIONALIZE

Build Descriptive,
Understand and Model
Collect, Connect, and Govern, Search, Predictive, and Create Analytics
Prepare Data Management and
Access Data and Find Data Prescriptive Applications
for Analysis Deployment
Models

Connect and Grant user access Understand, cleanse Create Machine Manage your models Incorporate trusted
discover content levels and enforce and prepare your Learning, Deep across dev, test, and governed models
from multiple data business policies. data to create data Learning, Optimization, staging, and prod. into applications,
sources across your preparation pipelines and other advanced dashboards, and
organization. Index for search, visually. mathematical models. Deploy your models operational systems.
visualize consumers and scale automatically
Provision and producers of Use popular open Tools to design your for online, batch or
databases and assets with lineage, source libraries to models program- streaming use cases
virtualized data metrics, and quality prepare structured and matically or visually. with SLAs.
access. profiles. unstructured data.
Train at scale with Monitor model
Find data and support for performance and
analytics assets in the distributed compute automatically trigger
Enterprise Catalog. and GPUs. retraining and
redeployment as rolling
upgrades.
Technology SET 3 : machine learning &
automation
Consume Model

Publish Model Monitor

20
Machines/Computers excel at:
Humans excel at:
Locating Knowledge
Pattern Identification Common Sense

Natural Language Morals

Machine Learning Imagination

Eliminate Bias Compassion

Endless Capacity Abstraction

Dilemmas
Dreaming
Generalization
Supplementing people
with bots drives new
automation outcomes Right brain
Cognition based

Left brain
Rules based

Digital labor is achieved by

combining robotics with other Central nervous system
Coordination &
forms of automation orchestration

Eyes
Data capture

Hands
Software robots

© 2018 IBM Corporation 22

IBM Cloud / DOC ID / Month XX, 2018 / © 2018 IBM Corporation 22

Digital labor enables businesses to remix the
distribution of work
Central nervous Left brain + hands Eyes + hands
system + hands
• Orchestrating the right • Separating complex • Extraction and action
balance of repetitive rules from repetitive on information from
work & knowledge work tasks unstructured content

• Example: Handling • Example: Calculating • Example: Interpreting

claims exceptions at discounts during and matching invoice
scale order entry data with the contract

© 2018 IBM Corporation

23
IBM Digital Business Automation

Points for Automation

Unique
EXPERT WORK

CROSS-
Content Workflow ENTERPRISE
WORK
ADMINISTRATIVE WORK DEPARTMENTAL
Digital WORK

Uniqueness of work
Business
Automation
Decisions capabilities Capture

REPETITIVE WORK
Tasks
Repetitive

Low volume High volume

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AI

4. Artificial Intelligence

3. Machine Learning

2. Analytics

1. Data
 Go Beyond: Unleash The Power Of Data

Operational BI and Data Self-Service New Business

Warehousing Analytics Models

83%
of view AI as
a strategic
Value

opportunity
Most
are
here

COST REDUCTION MODERNIZATION INSIGHT-DRIVEN TRANSFORMATION

Thank you