Return to Video

What happens inside those massive warehouses?

  • 0:10 - 0:15
    For the next few minutes
    I want to talk to you about...
  • 0:15 - 0:18
    or share with you a
    breakthrough new approach
  • 0:18 - 0:21
    for managing items of
    inventory inside of a warehouse.
  • 0:21 - 0:24
    We're talking about a Pick,
    Pack and Ship setting here.
  • 0:24 - 0:27
    So as a hint,
  • 0:27 - 0:31
    this solution involves
    hundreds of mobile robots,
  • 0:31 - 0:33
    sometimes thousands
    of mobile robots,
  • 0:33 - 0:36
    moving around a warehouse.
    And I'll get to the solution.
  • 0:36 - 0:37
    But for a moment, just think
  • 0:37 - 0:40
    about the last time
    you ordered something online.
  • 0:40 - 0:42
    You were sitting
    on your couch
  • 0:42 - 0:46
    and you decided that you
    absolutely had to have this red t-shirt.
  • 0:46 - 0:48
    So click you put it
    into your shopping cart.
  • 0:48 - 0:50
    And then you decided
    that green pair of pants
  • 0:50 - 0:52
    looks pretty good too, click.
  • 0:52 - 0:54
    And maybe a blue
    pair of shoes, click.
  • 0:54 - 0:56
    So at this point you've
    assembled your order.
  • 0:56 - 0:58
    You didn't stop to think
    for a moment that
  • 0:58 - 0:59
    that might not be a great outfit.
  • 0:59 - 1:01
    But you hit
    Submit Order.
  • 1:01 - 1:05
    And two days later, this package
    shows up on your doorstep.
  • 1:05 - 1:08
    And you open the box and like
    Wow, there's my goo.
  • 1:08 - 1:11
    Did you ever stop to think about
    how those items of inventory
  • 1:11 - 1:16
    actually found their way inside
    that box in the warehouse?
  • 1:16 - 1:18
    So I'm here to tell you
    it's that guy right there.
  • 1:19 - 1:23
    So deep in the
    middle of that picture
  • 1:23 - 1:25
    you see a classic
    Pick Pack Worker
  • 1:25 - 1:29
    in a distribution or
    order fulfillments setting.
  • 1:29 - 1:33
    Classically these pick workers
    will spend 60 to 70% of their day
  • 1:33 - 1:35
    wandering around
    the warehouse.
  • 1:35 - 1:37
    They'll often walk
    as much as 5, 10 miles
  • 1:37 - 1:40
    in pursuit of
    those items of inventory.
  • 1:40 - 1:44
    Not only is this an
    unproductive way to fill orders,
  • 1:44 - 1:48
    it also turns out to be an
    unfulfilling way to fill orders.
  • 1:48 - 1:52
    So let me tell you where I
    first bumped into this problem.
  • 1:52 - 1:56
    I was out in the Bay area
    in 1999-2000, the dot com boom.
  • 1:56 - 2:00
    I worked for a fabulously
    spectacular flame out called Webvan.
  • 2:00 - 2:02
    (Laughter)
  • 2:02 - 2:05
    This company raised hundreds of
    millions of dollars with the notion that
  • 2:05 - 2:07
    we will deliver
    grocery orders online.
  • 2:07 - 2:12
    And it really came down to the fact
    that we couldn't do it cost effectively.
  • 2:12 - 2:16
    Turns out e-commerce was something
    that was very hard and very costly.
  • 2:16 - 2:20
    In this particular instance we were trying
    to assemble 30 items of inventory
  • 2:20 - 2:24
    into a few totes, onto a van
    to deliver to the home.
  • 2:24 - 2:28
    And when you think about it,
    it was costing us $30.
  • 2:28 - 2:31
    Imagine, we had an
    89-cent can of soup
  • 2:31 - 2:34
    that was costing us $1 to
    pick and pack into that tote.
  • 2:34 - 2:38
    And that's before we actually
    tried to deliver it to the home.
  • 2:38 - 2:40
    So long story short,
    during my 1-year at Webvan,
  • 2:40 - 2:44
    what I realized by talking to
    all the material-handling providers
  • 2:44 - 2:48
    was that there was no solution designed
    specifically to solve each base picking.
  • 2:48 - 2:52
    Red item, green, blue, getting
    those 3 things in a box.
  • 2:52 - 2:55
    So we said, you know, there's just
    got to be a better way to do this.
  • 2:55 - 2:58
    Existing material handling
    was setup to pump
  • 2:58 - 3:02
    pallets and cases of
    goo to retail stores.
  • 3:02 - 3:05
    Of course Webvan went out of business
    and about a year and a half later,
  • 3:05 - 3:09
    I was still noodling on this problem.
    It was still nagging at me.
  • 3:09 - 3:11
    And I started
    thinking about it again.
  • 3:11 - 3:16
    And I said "Let me just focus briefly
    on what I wanted as a pick worker."
  • 3:16 - 3:18
    What my vision for
    how it should work.
  • 3:18 - 3:20
    (Laughter)
  • 3:20 - 3:22
    I said "let's focus
    on the problem."
  • 3:22 - 3:25
    I have an order here and what
    I want to do is I want to put
  • 3:25 - 3:28
    red, green and blue
    in this box right here.
  • 3:28 - 3:30
    What I need is a system where I put out
    my hand and poof!
  • 3:30 - 3:33
    the product shows up
    and I pack it into the order,
  • 3:33 - 3:35
    and now we're thinking,
  • 3:35 - 3:39
    "this would be a very operator-centric
    approach to solving the problem.
  • 3:39 - 3:43
    This is what I need. What technology
    is available to solve this problem?"
  • 3:43 - 3:47
    But as you can see, orders can come
    and go, product can come and go.
  • 3:47 - 3:52
    It allows us to focus on making the
    pick worker the center of the problem,
  • 3:52 - 3:56
    and providing them the tools to make
    them as productive as possible.
  • 3:56 - 3:58
    So how did I
    arrive at this notion?
  • 3:58 - 4:02
    Well, actually it came from
    a brainstorming exercise,
  • 4:02 - 4:05
    probably a technique
    that many of you use,
  • 4:05 - 4:07
    It's this notion of
    testing your ideas.
  • 4:07 - 4:09
    Take a blank sheet of course,
  • 4:09 - 4:13
    but then test your ideas
    at the limits. Infinity, zero...
  • 4:13 - 4:16
    In this particular case, we
    challenged ourselves with the idea:
  • 4:16 - 4:19
    wWhat if we had to build a
    distribution center in China,
  • 4:19 - 4:21
    where it's a very,
    very low cost market?
  • 4:21 - 4:25
    And say, labor is cheap,
    land is cheap.
  • 4:25 - 4:26
    And we said specificall:
  • 4:26 - 4:29
    "what if it was zero dollars
    an hour for direct labor
  • 4:29 - 4:32
    and we could build a million
    square foot distribution center?"
  • 4:32 - 4:34
    So naturally that
    led to ideas that said:
  • 4:34 - 4:36
    "Let's put lots of people
    in the warehouse."
  • 4:36 - 4:38
    And I said: "hold on,
    zero dollars per hour,
  • 4:38 - 4:41
    what I would do is "hire"
  • 4:41 - 4:45
    10,000 workers to come to the
    warehouse every morning at 8:00 am,
  • 4:45 - 4:48
    walk into the warehouse and
    pickup 1 item of inventory
  • 4:48 - 4:50
    and then just stand there.
  • 4:50 - 4:53
    So you hold Captain Crunch,
    you hold the Mountain Dew,
  • 4:53 - 4:54
    you hold the Diet Coke.
  • 4:54 - 4:56
    If I need it, I'll call you,
    otherwise just stand there.
  • 4:56 - 5:00
    But when I need Diet Coke and I call
    you guys talk amongst yourselves,
  • 5:00 - 5:04
    Diet Coke walks up to the front,
    pick it, put it in the tote, away it goes."
  • 5:04 - 5:09
    Like wow, what if the products
    could walk and talk on their own?
  • 5:09 - 5:11
    That's a very interesting
    very powerful way
  • 5:11 - 5:14
    that we could potentially
    organize this warehouse.
  • 5:14 - 5:16
    So of course,
    labor isn't free,
  • 5:16 - 5:19
    on that practical
    versus awesome spectrum.
  • 5:19 - 5:21
    (Laughter)
  • 5:21 - 5:24
    So we said mobile shelving.
    We'll put them on mobile shelving.
  • 5:24 - 5:29
    We'll use mobile robots and
    we'll move the inventory around.
  • 5:29 - 5:33
    And so we got underway on that and
    then I'm sitting on my couch in 2008.
  • 5:33 - 5:37
    Did any of you see the Beijing
    Olympics, the opening ceremonies?
  • 5:37 - 5:40
    I about fell out of my
    couch when I saw this.
  • 5:40 - 5:42
    I'm like, that was the idea!
  • 5:42 - 5:46
    (Laughter and Applause)
  • 5:46 - 5:50
    We'll put thousands of people on
    the warehouse floor, the stadium floor.
  • 5:50 - 5:54
    But interesting enough, this
    actually relates to the idea
  • 5:54 - 5:59
    in that these guys were creating some
    incredibly powerful impressive digital art,
  • 5:59 - 6:01
    all without computers,
    I'm told,
  • 6:01 - 6:04
    it was all peer-to-peer
    coordination and communication.
  • 6:04 - 6:05
    You stand up,
    I'll squat down.
  • 6:05 - 6:07
    And they made
    some fabulous art.
  • 6:07 - 6:10
    It speaks to the
    power of emergence
  • 6:10 - 6:14
    in systems when you let things
    start to talk with each other.
  • 6:14 - 6:18
    So that was a little
    bit of the journey.
  • 6:18 - 6:22
    So of course, now what became
    of the practical reality of this idea?
  • 6:22 - 6:23
    Here is a warehouse.
  • 6:23 - 6:27
    It's a pick, pack and ship center
    that has about 10,000 different SKU's.
  • 6:27 - 6:31
    We'll call them red pens,
    green pens, yellow Post-It Notes.
  • 6:31 - 6:35
    We send the little orange robots
    out to pick up the blue shelving pods.
  • 6:35 - 6:37
    And we deliver them
    to the side of the building.
  • 6:37 - 6:40
    So all the pick workers now
    get to stay on the perimeter.
  • 6:40 - 6:42
    And the game here is
    to pick up the shelves,
  • 6:42 - 6:46
    take them down the highway and
    deliver them straight to the pick worker.
  • 6:46 - 6:48
    This pick worker's life
    is completely different.
  • 6:48 - 6:51
    Rather than wandering around
    the warehouse, she gets to stay still
  • 6:51 - 6:53
    in a pick station like this
  • 6:53 - 6:57
    and every product in the
    building can now come to her.
  • 6:57 - 7:00
    So the process
    is very productive.
  • 7:00 - 7:04
    Reach in, pick an item,
    scan the bar code, pack it out.
  • 7:04 - 7:06
    By the time
    you turn around,
  • 7:06 - 7:09
    there's another product there
    ready to be picked and packed.
  • 7:09 - 7:12
    So what we've done is take
    out all of the non-value added
  • 7:12 - 7:15
    walking, searching,
    wasting, waited time,
  • 7:15 - 7:19
    and we've developed a very
    high-fidelity way to pick these orders,
  • 7:19 - 7:23
    where you point at it with
    a laser, scan UPC barcode,
  • 7:23 - 7:26
    and then indicate with a light
    which box it needs to go into.
  • 7:26 - 7:30
    So more productive, more
    accurate and it turns out
  • 7:30 - 7:34
    it's a more interesting office
    environment for these pick workers.
  • 7:34 - 7:37
    They actually complete
    the whole order.
  • 7:37 - 7:39
    So they do red, green and blue
    not just a part of the order.
  • 7:39 - 7:43
    And they feel a little bit more
    in control of their environment.
  • 7:43 - 7:46
    So the side effects
    of this approach
  • 7:46 - 7:47
    are what really surprised us.
  • 7:47 - 7:49
    We knew it was going
    to be more productive.
  • 7:49 - 7:53
    But we didn't realize just how
    pervasive this way of thinking
  • 7:53 - 7:58
    extended to other
    functions in the warehouse.
  • 7:58 - 8:03
    But what effectively this approach
    is doing inside of the DC
  • 8:03 - 8:08
    is turning it into a massively
    parallel processing engine.
  • 8:08 - 8:10
    So this is again a
    cross fertilization of ideas.
  • 8:10 - 8:12
    Here's a warehouse
    and we're thinking about
  • 8:12 - 8:16
    parallel processing
    supercomputer architectures.
  • 8:16 - 8:18
    The notion here is that you have
  • 8:18 - 8:21
    10 workers on
    the right side of the screen
  • 8:21 - 8:25
    that are now all independent
    autonomous pick workers.
  • 8:25 - 8:29
    If the worker in station 3 decides
    to leave and go to the bathroom,
  • 8:29 - 8:32
    it has no impact on the
    productivity of the other 9 workers.
  • 8:32 - 8:37
    Contrast that, for a moment, with the
    traditional method of using a conveyor.
  • 8:37 - 8:39
    When one person
    passes the order to you,
  • 8:39 - 8:41
    you put something in
    and pass it downstream.
  • 8:41 - 8:45
    Everyone has to be in place
    for that serial process to work.
  • 8:45 - 8:48
    This becomes a more robust
    way to think about the warehouse.
  • 8:48 - 8:52
    And underneath the hoods gets
    interesting in that we're tracking
  • 8:52 - 8:54
    the popularity
    of the products.
  • 8:54 - 8:57
    And we're using dynamic
    and adaptive algorithms
  • 8:57 - 9:01
    to tune the floor
    of the warehouse.
  • 9:01 - 9:06
    So what you see here potentially
    the week leading up to Valentines' Day.
  • 9:06 - 9:10
    All that pink chalky candy has
    moved to the front on the building
  • 9:10 - 9:14
    and is now being picked into a
    lot of orders in those pick stations.
  • 9:14 - 9:18
    Come in two days after Valentine's Day
    and that candy, the leftover candy,
  • 9:18 - 9:20
    has all drifted to the
    back of the warehouse
  • 9:20 - 9:25
    and is occupying the cooler
    zone on the thermo map there.
  • 9:25 - 9:28
    One other side effect of this
    approach using the parallel processing
  • 9:28 - 9:31
    is these things can
    scale to ginormous.
  • 9:31 - 9:33
    (Laughter)
  • 9:33 - 9:35
    So whether you(re doing
    2 pick stations, 20 pick stations, or
  • 9:35 - 9:39
    200 pick stations, the
    path planning algorithms
  • 9:39 - 9:41
    and all of the inventory
    algorithms just work.
  • 9:41 - 9:46
    In this example you
    see that the inventory
  • 9:46 - 9:48
    has now occupied all the
    perimeter of the building
  • 9:48 - 9:50
    because that's where
    the pick stations were.
  • 9:50 - 9:52
    They sorted it
    out for themselves.
  • 9:52 - 9:55
    So I'll conclude with
    just one final video
  • 9:55 - 9:58
    that shows how
    this comes to bear
  • 9:58 - 10:01
    on the pick worker's actual
    kind of day in the life of.
  • 10:01 - 10:05
    So as we mentioned, the process is
    to move inventory along the highway
  • 10:05 - 10:08
    and then find your way
    into these pick stations.
  • 10:08 - 10:11
    And our software in the background
  • 10:11 - 10:13
    understands what's going on
    in each station,
  • 10:13 - 10:16
    we direct deposit
    across the highway
  • 10:16 - 10:19
    and we're attempting to
    get into a queuing system
  • 10:19 - 10:22
    to present the work
    to the pick worker.
  • 10:22 - 10:25
    What's interesting is we can even
    adapt the speed of the pick workers.
  • 10:25 - 10:29
    The faster pickers get more pods
    and the slower pickers get few.
  • 10:29 - 10:32
    But this pick worker now is
    literally having that experience
  • 10:32 - 10:34
    that we described before.
  • 10:34 - 10:36
    She puts out her hand.
    The product jumps into it.
  • 10:36 - 10:38
    Or she has to reach in and get it.
  • 10:38 - 10:41
    She scans it and
    she puts it in the bucket.
  • 10:41 - 10:45
    And all of the rest of the technology
    is kind of behind the scenes.
  • 10:45 - 10:49
    So she gets to now focus on the
    picking and packing portion of her job.
  • 10:49 - 10:52
    Never has any idle time,
    never has to leave her matt.
  • 10:52 - 10:56
    And actually we think
    not only a more productive
  • 10:56 - 10:59
    and more accurate
    way to fill orders.
  • 10:59 - 11:03
    We think it is a more
    fulfilling way to fill orders.
  • 11:03 - 11:06
    The reason we can say
    that though is that workers
  • 11:06 - 11:08
    in a lot of these
    buildings now compete
  • 11:08 - 11:11
    for the privilege of working
    in the KIVA zone that day.
  • 11:11 - 11:14
    And sometimes we'll catch
    them on testimonial videos
  • 11:14 - 11:16
    saying such things as,
  • 11:16 - 11:20
    they have more energy after the
    day to play with their grandchildren,
  • 11:20 - 11:25
    or in one case a guy said, "the
    KIVA zone is so stress-free
  • 11:25 - 11:28
    that I've actually stopped taking
    my blood pressure medication."
  • 11:28 - 11:30
    (Laughter)
  • 11:30 - 11:34
    That was at a pharmaceutical distributor.
    So they told us not to use that video.
  • 11:34 - 11:37
    (Laughter)
  • 11:37 - 11:40
    So what I wanted to leave you
    with today is the notion that
  • 11:40 - 11:43
    when you let things start
    to kind of think and walk
  • 11:43 - 11:48
    and talk on their own, interesting
    processes and productivities can emerge.
  • 11:48 - 11:51
    And now I think next time
    you go to your front step
  • 11:51 - 11:54
    and pick up that box that
    you just ordered online,
  • 11:54 - 11:56
    you break it open and
    the goo is in there,
  • 11:56 - 11:59
    you'll have some wonderment
    as to whether a robot
  • 11:59 - 12:01
    assisted in the picking
    and packing of that order.
  • 12:01 - 12:03
    Thank you
  • 12:03 - 12:08
    (Applause)
Title:
What happens inside those massive warehouses?
Speaker:
Mick Mountz
Description:

more » « less
Video Language:
English
Team:
closed TED
Project:
TEDTalks
Duration:
12:06

English subtitles

Revisions Compare revisions