ever wonder how amazon gets your
packages to you so quickly
it's done with a symphony of machine
learning automation
and our amazing associates join us as we
see that in action
in an amazon fulfillment center welcome
to an amazon robotics sortable
fulfillment center
[Music]
this fc is one of more than 50 worldwide
where robots work alongside our amazing
employees
let's go inside at amazon we're customer
obsessed
we're also obsessed with the safety of
our employees in april of 2020
amazon began enhancing its temperature
screening process
by implementing thermal camera systems
throughout multiple business lines in
north america
now that our temperature is not detected
as high we're free to continue the tour
[Music]
today we're going to follow the path of
products from where they're received
stowed then picked packed and put on a
truck for distribution
the inbound process starts with
forecasting and ordering
before anything arrives to the fc
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powered by aws amazon's forecasting
engine is used for over 400 million
products daily let's go to the receiving
area
as you'll see we put a lot of energy
into our logistics
it's a symphony of people aws
software and other high-tech components
the result is a coordination between our
great employees
and the finely honed computer systems
we've evolved for more than 20 years
our employees are the heart and soul of
our operation some are military veterans
some are active members of the community
some are employees that work here with
their loved ones
they're all amazing trailers full of
vendor and small and medium business
seller items
arrive at these bay doors by appointment
employees
unload the trailers and begin the
process of staging items
located at their receiving workstations
this fc carries millions of items of
inventory
and using the service known as amazon
aurora we manage our
inventory transactions and other
relational database needs
at this station you can see how our
inbound associate receives a product
and how those products are stowed in our
inventory
amazon robotic drive units are activated
when an associate logs into their
workstation to perform their task
storage pods arrive facing the correct
side to stow items into inventory
every time an associate touches a
product they scan a unique barcode for
that item which we call the amazon
standard identification number
or asin that's stored in our inventory
system so we know what the quantity and
location of that item is
at any given time to manage our
inventory history
we use amazon neptune a fast reliable
fully managed graph database service
from aws
now you might expect that we'd organize
this in a way where similar items are
stowed together
for example all electronics would be
stored in the same section
however at amazon we've found that it's
more efficient to stow products using a
randomized method
that's why you'll see a variety of items
in each inventory bin
once that process has been completed a
physical and digital match is created in
our systems
so just a few seconds after an item is
stowed you can order it on amazon.com
looking at a station next door we see a
great example of computer vision helping
with automation
when an associate scans an item you'll
see magenta lights over some of the bins
in the pod
this lets the associate know not to
place that item in those locations
as artificial intelligence driven logic
has determined that the bin is full that
placing an item there may negatively
impact the pods overall weight
distribution or that a visually similar
item is there and may cause confusion
later when an associate needs to pick
the item
the associate can then place the item in
any of the other bins
but computer vision doesn't stop there
it will also detect what bin the
associate reached into
and knows where that item is placed as
one final step
it will take a picture of the pod and
use image recognition to count the
number of items in the bin
making sure the count matches what is
recorded in our tracking systems
when the machine learning model has low
confidence it sends images to people to
classify
and train more ground truth data for our
machine learning model which operates in
amazon sagemaker and amazon
sagemaker ground truth from aws
this allows us to perform ongoing
inventory reconciliation
avoiding the scheduled inventory counts
that are often done at least once a year
at other organizations
now what's up with those robots we see
moving the pods around
there are thousands of robot drive units
spread throughout each floor
helping associates fulfill customer
orders daily
amazon robotics operate in dedicated
fenced-off areas within the fc
which account for about 65 of the
facility's total square footage
the drive units travel to various
locations in rfc to pick up mobile
shelves of product
and deliver them to employees who are
working at ergonomic workstations
to navigate they read 2d barcodes on the
floor
and locations are tracked in real time
using our own created robotic operating
software
our amazon robotics team has developed
more than 100 services to support
operations
and uses aws extensively in the amazon
fulfillment centers
only specially trained individuals
wearing custom safety equipment are
allowed to enter this area
but on our virtual tour we're allowed to
walk through this restricted area
each sortable fc has over one million
unique items helping us with our goal to
provide
earth's largest selection
you may be thinking okay robots are
great but i just ordered an item how's
it picked
to answer that let's go to a pick
station here we see a similar layout as
our stow station
once you hit the buy button on
amazon.com
our systems will cue the robots to find
the inventory pod with the item you
ordered
once that item has been identified the
robot will bring it to our associate
a screen at the associate station will
show them a picture and quantity of the
item they need to pick
the same visual bin inspection system is
used as during stow
except this time instead of lighting up
bins where items should not be placed
the system lights up in a white light
where that item is
the associate identifies and grabs the
item placing it in the yellow toad
signified by the green light
and pushes the button acknowledging that
the item was placed there
when the system detects that the tote is
full the light flashes
and the associate pushes the full tote
back to a series of conveyors and
replaces it with a new one that was
automatically brought to their station
at this stage associates are picking
items for different customers in batches
the two types of picking processes we
focus on are single item orders and
multiple item orders
the single item orders contain only one
item per customer order
we fill up a yellow tote full of single
item orders weighing up to 25 pounds
the single item order yellow totes will
then be routed to the singles pack lines
for packaging
the multiple item orders contain more
than one item per order
if your multiple item order of six items
are all in this building
then it's possible that your order is
being picked up by up to six different
people picking items from six different
robots
which all need to be brought together
for your single shipment
your items will be placed in any
available yellow tote and routed to our
multiple item order assembly stations
it's at that point that we will reap in
your individual items into one customer
order
then once all of your items are together
it's packing time
to help improve efficiency and also
reduce environmental impact of the
packaging
the size of boxer envelope is
automatically selected by a machine
learning algorithm
even the correct length of tape is
determined by machine learning
and automatically dispensed if needed
protective packaging materials are added
a barcode is placed on the package it's
sealed up
and away we go that barcode will be
important for the next stage that we
call
slab but what if i order two items and
those items are in two different fcs
do i get one box or two the answer is
it depends our first priority is to get
you the item at the date and time that
we promised when you placed the order
the second priority is to do that at the
lowest cost possible
and with the lowest environmental impact
so we can continue to pass on lower
prices to you
with those two things in mind we use
machine learning to figure out if it's
optimal to ship to you from each fc in
two different packages
or ship an item from one fc to the other
combine them there
and ship to you in a single package
you're now seeing our slam line in
process
slam is an acronym which stands for scan
label
apply and manifest the technology here
scans that barcoded sticker placed on
the package in pack
and immediately knows to print the
correct shipping label on the package
this is the first time your name and
address are placed on the package
so how do we know which carrier to use
that's also determined by machine
learning
in the space of a few seconds an
algorithm is run to determine the
optimal delivery carrier
to get you the package on time and at
the lowest cost possible
there are also quality control measures
in place here following this
the box is weighed and the weight is
checked against the item's known weight
if the weight is off the order will be
routed to a special location
from there an associate will open the
package and take the applicable action
we're now entering the final stages
after passing all of those quality
control measures the package is routed
onto another series of conveyors to a
location where the label is scanned
the conveyors then automatically send
each package down the correct
shoot where it will be packaged on a
semi-trailer for shipment to another fc
or a sortation center for final delivery
to you
there are approximately 17.5 miles of
conveyor belts in this fc
in order to run reliably every single
day they're monitored via aws
iot services aws iot green grass
helps here by allowing devices to act
locally on the data they generate while
still taking advantage of the cloud
events in particular from the machinery
are sent to lambda functions in aws
the trigger step functions these
workflows
then coordinate rme operations to
maintain the equipment
perform inspections replace faulty
motors and belts
and other types of activities
we even collaborate with some of our
automation suppliers using aws
ml models to predict equipment failures
and address issues before they arise
[Music]
thank you for visiting our amazon
sortable robotics fulfillment center
we hope you enjoyed our virtual tour