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AUTOMATION, ROBOTICS
& ARTIFICIAL INTELLIGENCETH E F U TU R E O F E -CO MME R CE , F U L F I L L ME NT & D I S TR I B U T I ON
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
PRESENTED BY
Austin Smith
CEO
Connecting fulfillment technologies,
data, and people, all in one platform.
Jatin Lewis
Senior Sales Consultant
SDI is a leading international manufacturing
company of automation and robotics solut ions
for enterprise-level logist ics centers.
Mike Higley
Senior Software Architect
Barron DeSanctis
Partner | EVP
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
1. Who are we? - SDI
2. History of Distr ibution
3. The Future of Automation & Robotics
4. The Future of Art if icial Intell igence (AI )
5. Questions
AGENDA
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
SDI OVERVIEW
1977FOUNDED IN
40YRS.OF EXPERIENCE
300+EMPLOYEES IN NORTH
& SOUTH AMERICA
A LEADER IN SYSTEMS INTEGRATION & AUTOMATED SOLUTIONS
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
TURNKEY MATERIAL HANDLING & STORAGE SYSTEMS
• Consulting & Data Analysis
• Distribution Center Design
• Vendor Selection & Evaluation
• Engineering & Manufacturing
• Warehouse Management (WMS)
& Warehouse Control (WCS)
• Mechanical Installation
• Controls & Field Wiring
• Project Management
• After Sales Spare Parts, built in USA
• After Sales Support Hotline – based in
Florida – multi-lingual
• Geographically Diverse
WE ARE VERTICALLY INTEGRATED – ONE STOP SHOP
Full Systems
IntegratorProvider
Design Engineer
Implement Support
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
ONE-STOP SHOP APPROACH "NINJA STYLE"
SDI COMBINES CAPABILITIES WITH HIGH TOUCH SERVICE TO BE THE INTEGRATOR OF CHOICE
Senior executives
and owners are
in touch with
the clients and projects
AT ALL TIMES.
Design / Consulting
Capabilities
that rival the competition
Nimble / can handle schedules
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
HQ
LOCATIONS IN THE AMERICAS w/ GLOBAL PARTNERS
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
SDI CLIENT LIST CONSISTS OF
Omni-ChannelMulti-Channel
Retail / Wholesale
E-Commerce
3rd PartyLogistics
Fashion, Shoes& Accessories
ParcelHandling
ParcelHandling
MedicalIndustry
Vitamins & Supplements
Food & Super Market
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
History of Distribution
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
The Future of Automation & Robotics
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
MORE GOODS TO PERSON
D E S I G N E D F O R :
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
ROBOTICS
E N Z O ( A G V )K I N D R E D R o b o t i c A r m
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
DARK WAREHOUSEa ful ly-automated warehouse that
operates w ithout the use of human labor.
You can s imply turn the l ights out and the operation w i l l continue to run.
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
Anyone invested into any automation /
robotics project / success s tor ies they want
to talk about?
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
CONNECT, COLLECT & ADAPTArti f icial Intel l igence
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
NOT JUST A WATERCOOLER
CONVERSATIONCOVID-19 made us go f rom a
“nice to hav e” to a “need to hav e”
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
62%
Supply chain leaders believe similar
large-scale disruptions are likely to
occur in the future.
AC C ORD I N G TO THE 2 0 2 1 D E L O I T TE G L O B A L R E S I L I E N C E R E P O R T
30%
Supply chain leaders believe their
organizations can quickly adapt and
pivot in response to disruptive events.
34%
Supply chain leaders feel prepared to
lead through uncertainty or disruptions
that might arise in the future.
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
PANDEMIC-DRIVEN SHIFTSThe pandemic exposed the v ulnerabi l i ty
and fragi l i ty of supply chains
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
Lack of v isibility and forecasting with
changing pressure on online demand.
O R D E R V O L U M E
Lack of v isibility and forecasting with
the challenges in Labor.
L A B O R
Lack in v isibility and forecasting: damaged
items, returns & refunds caused by DC.
C O N S U M E R S
W H A T H A S C H A N G E D ?
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
Lack of v isibility and forecasting with
changing pressure on online demand.
O R D E R V O L U M E
Lack of v isibility and forecasting with
the challenges in Labor.
L A B O R
Lack in v isibility and forecasting: damaged
items, returns & refunds caused by DC.
C O N S U M E R S
W H A T H A S C H A N G E D ?
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
J U M P I N I N V E S T M E N T S F R O M T H E P R E V I O U S Y E A R
Inventory & Networking Optimization Tools55%
Cloud Computing & Data Storage
Robotics & Automation
Sensors & Automatic Identification
Predictive & Prescriptive Analytics
Artificial Intelligence Technologies
54%
53%
52%
45%
35%
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
EARLY ADOPTERSWhat are technology leaders doing r ight now ?
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
Partnering with vendors to better understand applications and business benefits
Piloting new technologies
Increased investments for innovative technologies
Recruiting for different skillsets to align to future needs
Change Org. Structure to create culture of Innovation
Training for emerging technologies
48%
42%
39%
33%
30%
W H A T P R E P A R A T I O N S F O R C H A N G E A R E B E I N G M A D E ?
37%
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
C O M P A N I E S T H A T E M B R A C ED I G I T A L T E C H N O L O G I E S & I N N O V A T I O N S C A N …
B E N E F I T
Create sustainable competitive
advantages that enable them to
thrive in the post-disruption world.
A D A P T
Recover faster than
their peers.
Recover Faster
Respond more quickly and
effectively to the immediate
challenges posed by disruption.
I D E N T I F Y
Respond Faster
Stay On Top
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
All reasons why ARTIFICIAL INTELLIGENCEis necessary for future success
of organizations
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
BUT FIRST…Do you know w hat i s takes to implement AI ?
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
1. RAW Data
Connection to SourcesLarge amounts of QUALITY data.
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
1. RAW Data
Connection to SourcesLarge amounts of QUALITY data.
2. Store the Data
Deep LearningSubset of ML which make the
computation of algorithm feed by large
amount of stored data
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
1. RAW Data
Connection to SourcesLarge amounts of QUALITY data.
2. Store the Data
Deep LearningSubset of ML which make the
computation of algorithm feed by large
amount of stored data
3. Apply Machine Learning
Behavior can Change on
New InformationSubset of AI which use stat istical methods to
enable machines to improve with experience
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
1. RAW Data
Connection to SourcesLarge amounts of QUALITY data.
2. Store the Data
Deep LearningSubset of ML which make the
computation of algorithm feed by large
amount of stored data
3. Apply Machine Learning
Behavior can Change on
New InformationSubset of AI which use stat istical methods to
enable machines to improve with experience
4) Apply Artificial Intelligence
AI Requires a Closed LoopA technique which enables machines to
mimic human behaviour
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
1. RAW Data
Connection to SourcesLarge amounts of QUALITY data.
2. Store the Data
Deep LearningSubset of ML which make the
computation of algorithm feed by large
amount of stored data
3. Apply Machine Learning
Behavior can Change on
New InformationSubset of AI which use stat istical methods to
enable machines to improve with experience
4) Apply Artificial Intelligence
AI Requires a Closed LoopA technique which enables machines to
mimic human behaviourThe FASTER
your loop
spins,
the SMARTER
your AI is.
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
J U M P I N I N V E S T M E N T S F R O M T H E P R E V I O U S Y E A R
Inventory & Networking Optimization Tools55%
Cloud Computing & Data Storage
Robotics & Automation
Sensors & Automatic Identification
Predictive & Prescriptive Analytics
Artificial Intelligence Technologies
54%
53%
52%
45%
35%
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
J U M P I N I N V E S T M E N T S F R O M T H E P R E V I O U S Y E A R
Inventory & Networking Optimization Tools55%
Cloud Computing & Data Storage
Robotics & Automation
Sensors & Automatic Identification
Predictive & Prescriptive Analytics
Artificial Intelligence Technologies
54%
53%
52%
45%
35%
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
AI driven order wave building that
allows for over provisioning unit sorter,
allowing for larger pick waves.
O R D E R V O L U M E
AI forecasting used to predict
labor needs.
L A B O R
AI assisted inventory management that
adjusts inventory location over time base
on real time feedback and historic trends
resulting in faster pick routes.
C O N S U M E R S
A I C A N H E L P W I T H
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
OK…What can w e do r ight now ?
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
N E X T S T E P I S L E A R N I N G T H E M A C H I N E
Step 1:Connect Data
Start finding an integrator that can connect,
collect and translate lower-level systems data.
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
N E X T S T E P I S L E A R N I N G T H E M A C H I N E
Step 1:Connect Data
Start finding an integrator that can connect,
collect and translate lower-level systems data.
Have them work with your vendors and
understand what data is available.
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
N E X T S T E P I S L E A R N I N G T H E M A C H I N E
Step 1:Connect Data
Step 2: Store & Clean Data
Hindsight
Early levels of feedback within 90 days
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
N E X T S T E P I S L E A R N I N G T H E M A C H I N E
Step 1:Connect Data
Step 2: Store & Clean Data
Hindsight
Early levels of feedback within 90 days
You need at least 1 year of continuous
stored data
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
N E X T S T E P I S L E A R N I N G T H E M A C H I N E
Step 1:Connect Data
Step 2: Store & Clean Data
Hindsight
Step 3:Identify Patterns
Insight
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
N E X T S T E P I S L E A R N I N G T H E M A C H I N E
Step 1:Connect Data
Step 2: Store & Clean Data
Hindsight
Step 3:Identify Patterns
Insight
Step 4:Make Predictions
Foresight
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
N E X T S T E P I S L E A R N I N G T H E M A C H I N E
Step 1:Connect Data
Step 2: Store & Clean Data
Hindsight
Step 3:Identify Patterns
Insight
Step 4:Make Predictions
Foresight
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
M A C H I N E L E A R N I N G W I L L P R O V I D E Y O U
Historical Data Current Month Predictions
T O D A Y
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
A N A T O M Y O F A I
Your Machine Learning Algorithm
Perceive Environment
Detect patternsUnderstand, decide,
and updateVisualization
T H E A I F E E D B A C K L O O P
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
WHAT CAN I SEE & USEWith Arti f ic ial I n tel l igence
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
T H I S I S W H A T T H E O U T P U T L O O K S L I K E W I T H A I
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
Questions?
Come visit us at sdi.systems
Anyone invested into any automation /
robotics they want to talk about ?
Anyone invested into any automation /
robotics they want to talk about ?
C O M E V I S I T U S A T w w w . S D I . S Y S T E M S
Questions?
Anyone invested into any automation /
robotics they want to talk about ?
Anyone invested into any automation /
robotics they want to talk about ?
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