AI scenarios for Manufacturing & Supply chain in 2020

Dmytro Turchyn

Artificial Intelligence Product Marketing Lead,

Microsoft CEE

AI is Transforming the Manufacturing Industry

Increase customer specificity

& product variability

Predictive inventory management,

customized quoting and contracting.

Eroding Margins & Rising CostsIncreased operational efficiency, automatic asset

maintenance, and less asset replacements.

Growing skills gap & deteriorating assetsImproved reporting, more natural

interfaces, and efficient training.

Manufacturing: Key Transformational Scenarios

ConnectedField Service

Enable proactive

engagement throughout

the product lifecycle

Connected Salesand Service

Customize sales and services

to strengthen relationships

and loyalty

Factory ofthe Future

Leverage industrial IoT and

other smart technologies

for agile production

IntelligentSupply Chain

Optimize supply chain to

produce the right products

at the right time and price

What is Connected Field Service?Connected Field Service empowers manufacturers to transform their services and deepen customer loyalty.

Remote monitoringData collection and automatic action

Predictive maintenancePattern recognition and diagnosis

Smart interface Issue reporting and efficient employee guidance

Triage-by-complexityFlexible reactions from tutorials to expert referral

Tutorial document

Expert referral

AI in factory of the future

Next pickup: bin 5141

Bin 5139

Bin 5140

Bin 5141

9

Process optimization controls high speed processes

Autonomous vehicles/robots optimize

warehouse utilization

Machine calibration automates system

tuning

Smart systems enables process automation and optimization

Smart spaces transmits information on energy

consumption

Factory assistance provides operators with information

upon request

Predictive maintenance enables condition-based maintenance

Cognitive quality detects defects with image

recognition

Product traceability allows end-to-end

tracking

Health and safety mitigates and prevents

incident factories

Industrial robots/cobots adapt to

changing location

Siemens

Auto-tune CNC 30x faster with deep reinforcement learning

Jabil decreases false flags with intelligent optical inspections

Impact

8x increase in auto-approval rate

75% accuracy for false-positives

92% accuracy on defectives

Reduced costs of scrap and re-work

by 17%

Delivered energy savings of 10%

Safety CapabilitiesImage matching and object detection

Machine unsafe Zone violation Emotional response

Video evidence Safety gear absent Unauthorized access

Proactively prevent accidents

AI in intelligent supply chain

Inventory levels

452232111

Customer part no.

Customer location

10 week forecast Stock on hand

45245465

36525224

58744563

36225412

12545583

London

Zurich

Brazil

Singapore

Sydney

London

Understock

Understock

Over stock

Over stock

On track

On track

Increase supply level

Decrease supply level

102

352

521

124

346

356

Recommended adjustments

Steel price

Salvador product flow San diego product flow

Outsourced supplier options

• Nabtech corporation

• Commonwealth aero

• GRS aerospace

• DandC engineering

• Advanced

electronics, ltd.

• Apex industries

• Eastern aircraft tires

• Fabritech ab

Outsourced supplier options

Mombasa product flow Hamburg product flow

New distribution center options

Marketing event timeline

Projected production levels

Planning Demand forecast

Region CategoriesAsia Automobile

Q4Q3Q2Q1

Demand forecasting predicts future demand with AI

Predictive and cognitive quality, yield uncovers defects through

image recognition

Inventory planning and optimization spans across

multiple echelon and location

Warehouse automation optimizes warehouse

utilization

Sourcing and procurement enhances spend analytics,

contracting, and BOM management

Supply chain visibility and orchestration drives agility,

responsiveness, and flexibility

Integrated track and trace enables product

tracking

Integrated business planning empowers businesses with

prescriptive analytics

Application: Dynamic Network Management

An integrated Global Platform to

visualize our Global Network.

Millions of supply chain data points,

both internally and externally, are

being processed in real time through

a data science model and displayed.

The foundation for machine learning

and predictive analytics delivery

performance.

35+ ELD AGGREGATORS/

GLOBAL GPS PROVIDER

ALL VESSEL

VOYAGES GLOBALLY

CELL PHONE

TRIANGULATION

4.5 million/month

ELECTRONIC DATA

INTERCHANGE

11K customers

3.5K Carriers

ALL FLIGHTS

GLOBALLY

Machine Learning and Predictive Analytics

As the supply chain industry

moves forward and the

Internet of Things continues its

expansion, the ability to

consume, combine, and

analyze data from growing

number of integrations is

essential

Machine Learning and Artificial

Intelligence methodologies

need to be incorporated to

create predictive capabilities

that evolve and improve over

time

Live Route Calculation

Predictive ETA using Data Science Model

Push Notifications to Customers/Stakeholder

Kazakhstan RailwaysOptimization of rail logistic of oil & gas products, using Azure ML model to forecast demand and time.

▪ Improved forecasts for tanks availability

▪ Reduced empty runs

▪ Operational costs have been reduced on 17%

Partner Enabled Scenarios

16

AI in industrial IoT summaryUse cases

Product-as-a-service

Factory of the future

Intelligent supply chain

Industrial IoT

Factory

assistance

Predictive

maintenance

Cognitive

quality

Product

traceability

Industrial

robots/cobots

Process

optimization

Autonomous

vehicles/

robots

Machine

calibrationSmart systems Smart spaces

Health and

safety

Cognitive

service alerts

Predictive

anomaly

detection

Tuned and

optimized AI

models

Service bots

Automatic part

detectionSmart devices

Guided service

workflow

Upsell and cross

sell

opportunities

Smart routing

Service history

insights

Sourcing and

procurement

Supply chain

visibility and

orchestration

Inventory

planning and

optimization

Demand

forecasting

Integrated track

and trace

Predictive and

cognitive

quality, yield

Integrated

business

planning

Warehouse

automation

Happiness

Meaningful

Innovation

Empowering

PeopleResponsible AI

Principles >Practices >Tools

UnderstandML models

Protectpeople and their data

Controlend-to-end ML process

AI Business School

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Practical guides

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