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FIND YOUR WOW Applying Machine Learning to Optimize the Supply Chain: How IoT Will Revolutionize Supply Chain in 2019 Presented by: Fellow Inc.

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Page 1: Applying Machine Learning to Optimize the Supply ChainThe Case for Machine Learning 33 •Too much data for humans to understand quickly •Patterns are hard to discern- Merchants

FIND YOUR WOW

Applying Machine Learning to Optimize the Supply Chain:How IoT Will Revolutionize Supply Chain in 2019

Presented by:

Fellow Inc.

Page 2: Applying Machine Learning to Optimize the Supply ChainThe Case for Machine Learning 33 •Too much data for humans to understand quickly •Patterns are hard to discern- Merchants

FIND YOUR WOW

Presenters

2

Marco MascorroPresident/CEO

Fellow Inc.

Frederick GeigerMarketing & Customer

Success LeadFellow Inc.

Page 3: Applying Machine Learning to Optimize the Supply ChainThe Case for Machine Learning 33 •Too much data for humans to understand quickly •Patterns are hard to discern- Merchants

FIND YOUR WOW

Agenda

Fellow Background

The Internet of Things - IoT – Supply Chain overview

An example of a Supply Chain tracking solution

Why Applied Machine Learning is necessary

Questions

3

Page 4: Applying Machine Learning to Optimize the Supply ChainThe Case for Machine Learning 33 •Too much data for humans to understand quickly •Patterns are hard to discern- Merchants

FIND YOUR WOW4

Fellow Inc. designs and develops cutting-edge,

innovative core technologies and builds products

by working with key manufacturing partners

through strategic relationships. Fellow has

multiple national and international patents granted

and pending for its technologies.

Innovative & Creative Technology Solutions

Page 5: Applying Machine Learning to Optimize the Supply ChainThe Case for Machine Learning 33 •Too much data for humans to understand quickly •Patterns are hard to discern- Merchants

FIND YOUR WOW5

• Tracking and protecting your most valuable

assets has never been easier

• IoT devices overcome the shortfalls of

traditional tracking technology

The Supply Chain Revolution in Real Time

Page 6: Applying Machine Learning to Optimize the Supply ChainThe Case for Machine Learning 33 •Too much data for humans to understand quickly •Patterns are hard to discern- Merchants

FIND YOUR WOW

The Supply Chain Revolution in Real Time

6

• IoT solutions offer:

• Flexibility • Affordability

• End-to-end view • Real time updates

Page 7: Applying Machine Learning to Optimize the Supply ChainThe Case for Machine Learning 33 •Too much data for humans to understand quickly •Patterns are hard to discern- Merchants

FIND YOUR WOW

The Supply Chain Revolution in Real Time

7

• Monitor the location and condition of goods as they travel

• Offer improved security for warehouses and fleet vehicles

Page 8: Applying Machine Learning to Optimize the Supply ChainThe Case for Machine Learning 33 •Too much data for humans to understand quickly •Patterns are hard to discern- Merchants

FIND YOUR WOW

Asset Tracking

8

• Barriers that traditional tracking technology comes up against are

being broken

• Affordable, easy to install, easy to maintain, and available worldwide

• Devices can run for months without a battery or device charge

• Work both indoors and outdoors

Page 9: Applying Machine Learning to Optimize the Supply ChainThe Case for Machine Learning 33 •Too much data for humans to understand quickly •Patterns are hard to discern- Merchants

FIND YOUR WOW

Asset Tracking

9

• Trackers transmit location data from fleets of returnable containers

• Transmit valuable information on the whereabouts of other deliveries

• Offers value chain security, efficiency, and peace of mind

Page 10: Applying Machine Learning to Optimize the Supply ChainThe Case for Machine Learning 33 •Too much data for humans to understand quickly •Patterns are hard to discern- Merchants

FIND YOUR WOW

Monitoring Conditions

10

• IoT, machine learning, and AI provide better insights into:

• Quality control

• Traceability

• Responsibility boundaries

• Tracking ensures safety for assets, timeliness, and condition status

Page 11: Applying Machine Learning to Optimize the Supply ChainThe Case for Machine Learning 33 •Too much data for humans to understand quickly •Patterns are hard to discern- Merchants

FIND YOUR WOW

Security Where You Need It

11

• Most security alarms are connected via GSM

• GSM jammers are widely available on the market

• Anyone can break in, steal, or vandalize your most valuable assets

Page 12: Applying Machine Learning to Optimize the Supply ChainThe Case for Machine Learning 33 •Too much data for humans to understand quickly •Patterns are hard to discern- Merchants

FIND YOUR WOW

Security Where You Need It

12

• Radically creative IoT solutions

protect facilities from threats

• Tackle the problems with alarm system

downtime and jamming

Page 13: Applying Machine Learning to Optimize the Supply ChainThe Case for Machine Learning 33 •Too much data for humans to understand quickly •Patterns are hard to discern- Merchants

FIND YOUR WOW

Manufacturing: Industry 4.0

13

• Manufacturing is moving into Industry 4.0

• Harness the power of data with the newest IoT solutions

• IoT solutions help cut cost and streamline daily operations

• Gain new analytical insight

Page 14: Applying Machine Learning to Optimize the Supply ChainThe Case for Machine Learning 33 •Too much data for humans to understand quickly •Patterns are hard to discern- Merchants

FIND YOUR WOW

Digitization Optimization

14

• Using data, IoT solutions can optimize the manufacturing process

• Enable a variety of connected sensors to monitor metrics:

• Pressure • Vibration •Temperature

• Humidity • Switches • Voltage

Page 15: Applying Machine Learning to Optimize the Supply ChainThe Case for Machine Learning 33 •Too much data for humans to understand quickly •Patterns are hard to discern- Merchants

FIND YOUR WOW

Digitization Optimization

15

• Detect problems in equipment:

• Openings • Leaks • Tilt

• Battery levels • Current • Flooding

• Data flow combined with real-time dashboards,

makes predictive maintenance a reality

Page 16: Applying Machine Learning to Optimize the Supply ChainThe Case for Machine Learning 33 •Too much data for humans to understand quickly •Patterns are hard to discern- Merchants

FIND YOUR WOW

Collaboratively Utilizing IoT

16

• Rechargeable beacon devices send out real-time

location information

• Receivers, monitors, and routers consolidate and

route data to cloud-based software services

• Apply business rules to real-time monitoring

and reporting

Page 17: Applying Machine Learning to Optimize the Supply ChainThe Case for Machine Learning 33 •Too much data for humans to understand quickly •Patterns are hard to discern- Merchants

FIND YOUR WOW17

Let’s explore a real-life scenario in which

an innovative, supply chain management

system, Fellow WatchDog, solves

common supply chain problems

Page 18: Applying Machine Learning to Optimize the Supply ChainThe Case for Machine Learning 33 •Too much data for humans to understand quickly •Patterns are hard to discern- Merchants

FIND YOUR WOW

Real World Example

18

Our solution places IoT beacons and tracking

units in the warehouses, trailers, and receiving

areas of its stores, facilities, and factories

Page 19: Applying Machine Learning to Optimize the Supply ChainThe Case for Machine Learning 33 •Too much data for humans to understand quickly •Patterns are hard to discern- Merchants

FIND YOUR WOW

Real World Example - Mapping

19

Page 20: Applying Machine Learning to Optimize the Supply ChainThe Case for Machine Learning 33 •Too much data for humans to understand quickly •Patterns are hard to discern- Merchants

FIND YOUR WOW

Real World Example – Mapping RFID Micro location

19

Page 21: Applying Machine Learning to Optimize the Supply ChainThe Case for Machine Learning 33 •Too much data for humans to understand quickly •Patterns are hard to discern- Merchants

FIND YOUR WOW

Real World Example

20

Fellow DogTags are added to each transport

pallet or item and linked to each unique pallet

Page 22: Applying Machine Learning to Optimize the Supply ChainThe Case for Machine Learning 33 •Too much data for humans to understand quickly •Patterns are hard to discern- Merchants

FIND YOUR WOW

Real World Example

21

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Outbound

#0925

Outbound

1460 Koll Circle

San Jose, CA 95112

NASA Research Park

20 S. Akron Rd. MS 20-1

Moffett Field, CA 94035

Page 23: Applying Machine Learning to Optimize the Supply ChainThe Case for Machine Learning 33 •Too much data for humans to understand quickly •Patterns are hard to discern- Merchants

FIND YOUR WOW

Real World Example

22

Fellow DogTags movements sensed by Fellow InFormant

and are synced with the logistics system data using

Fellow Fusion and its Machine Learning and alerting

Page 24: Applying Machine Learning to Optimize the Supply ChainThe Case for Machine Learning 33 •Too much data for humans to understand quickly •Patterns are hard to discern- Merchants

FIND YOUR WOW

Real World Example

23

Assets are loaded into the trailer, alerting geofence

Fellow InFormant devices in the warehouse

Page 25: Applying Machine Learning to Optimize the Supply ChainThe Case for Machine Learning 33 •Too much data for humans to understand quickly •Patterns are hard to discern- Merchants

FIND YOUR WOW

Real World Example

24

Other IoT Trailer-based and GPS enabled tractor

send telemetries to cloud-based Fellow Fusion

Page 26: Applying Machine Learning to Optimize the Supply ChainThe Case for Machine Learning 33 •Too much data for humans to understand quickly •Patterns are hard to discern- Merchants

FIND YOUR WOW

Real World Example

25

Delivery of trailer is recognized by the geofence at the

receiving store and pallets are checked accordingly

Page 27: Applying Machine Learning to Optimize the Supply ChainThe Case for Machine Learning 33 •Too much data for humans to understand quickly •Patterns are hard to discern- Merchants

FIND YOUR WOW

Real World Example

26

Empty pallets are then tracked as they are returned

to the warehouse for reuse and reassignment

Page 28: Applying Machine Learning to Optimize the Supply ChainThe Case for Machine Learning 33 •Too much data for humans to understand quickly •Patterns are hard to discern- Merchants

FIND YOUR WOW

Real World Example

27

Value of this solution becomes

apparent when things go wrong

Page 29: Applying Machine Learning to Optimize the Supply ChainThe Case for Machine Learning 33 •Too much data for humans to understand quickly •Patterns are hard to discern- Merchants

FIND YOUR WOW

Real World Example

28

Fellow Fusion sends auditable action alerts to:

• SMS device or email

• Or task management systems

Page 30: Applying Machine Learning to Optimize the Supply ChainThe Case for Machine Learning 33 •Too much data for humans to understand quickly •Patterns are hard to discern- Merchants

FIND YOUR WOW

Real World Example

29

Dashboards built in Microsoft Power BI show trends,

alerts, paths, and assets presently shown by location

Page 31: Applying Machine Learning to Optimize the Supply ChainThe Case for Machine Learning 33 •Too much data for humans to understand quickly •Patterns are hard to discern- Merchants

FIND YOUR WOW

Real World Examples - Dashboards

30

Immediately track product action and

other telematics in software applications

Page 32: Applying Machine Learning to Optimize the Supply ChainThe Case for Machine Learning 33 •Too much data for humans to understand quickly •Patterns are hard to discern- Merchants

FIND YOUR WOW

Real World Examples - Dashboards

31

Page 33: Applying Machine Learning to Optimize the Supply ChainThe Case for Machine Learning 33 •Too much data for humans to understand quickly •Patterns are hard to discern- Merchants

FIND YOUR WOW

Real World Examples - Dashboards

32

Page 34: Applying Machine Learning to Optimize the Supply ChainThe Case for Machine Learning 33 •Too much data for humans to understand quickly •Patterns are hard to discern- Merchants

FIND YOUR WOW

The Case for Machine Learning

33

• Too much data for humans to understand quickly

• Patterns are hard to discern- Merchants and operators want to work on their business, not analyze data

• Outside data sources – weather supply feeds and enterprise systems need to be integrated

• Speed is necessary for prevention of problems

Page 35: Applying Machine Learning to Optimize the Supply ChainThe Case for Machine Learning 33 •Too much data for humans to understand quickly •Patterns are hard to discern- Merchants

FIND YOUR WOW34

Questions?

Page 36: Applying Machine Learning to Optimize the Supply ChainThe Case for Machine Learning 33 •Too much data for humans to understand quickly •Patterns are hard to discern- Merchants

FIND YOUR WOW

For more information:

Marco Mascorro

[email protected]

Website: www.fellowrobots.com

Frederick Geiger

[email protected]

Website: www.fellowrobots.com

Visit ProMat Booth #N6559

35


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