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The Distribution Experts®
For over 70 years, Fortna has partnered with the world’s top brands—companies like ASICS, O’Reilly Auto Parts and MSC—helping them improve
their distribution operations and transform their businesses. Companies with complex distribution operations trust Fortna to help them meet
customer promises and competitive challenges profitably. We are a professional services firm built on a promise—we develop a solid business
case for change and hold ourselves accountable to those results. Our expertise spans supply chain strategy, distribution center operations,
material handling, supply chain systems, performance improvement and warehouse control software.
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What does the distribution center of the future look like? It’s likely to include more than a few robots and autonomous vehicles with machine learning algorithms helping to make them better at decision making. But humans won’t be entirely out of the picture. There will be a fair number of them working alongside, managing and maintaining the machines that do the heavy lifting. Here are just a few of the technologies that are coming to the DC in the next 3-5 years.
These bots are more like conveyor replacements. They move products
and materials to the workers, reducing the amount of costly and
time-consuming travel that is the bane of today’s DC worker productivity.
Perhaps one limitation with this technology is that the picking operation
must be designed for goods-to-person picking, which can make it more
difficult to scale up and down easily.
Kiva-style Goods-to-Person Bots
Emerging TechnologiesDistribution Centerfor the
Insider’s Guide to
Business Case • Productivity – reduction in travel time• 24x7x365 availability• Labor savings• Flexibility - on-demand expansion as business grows
Self-driving vehicles and lift trucks have been around for years. The older, familiar
AGVs have simplistic routing and low level decision-making capabilities, require
fixed paths consisting of permanently mounted beacons, barcodes or magnetic
tape, which are inflexible and costly to change. Today’s AGVs are vision-guided
with improved sensors and offer more autonomy. There are no pre-programmed
routes or wires in the floor because the bots can see objects in their path and
learn new ways around the facility through machine learning.
Self-driving Vehicles and Lift Trucks
Business Case• Productivity – reduction in travel time• 24x7x365 availability• Labor savings• Flexibility - on-demand expansion as business grows• Reduced product and structure damage
Several companies, like Locus Robotics and 6 River Systems, are
tackling picking from a slightly different angle. These bots
receive an order picking assignment and then move to the
product location where a worker meets the bot to pick items
into the tote. This technology allows for routing orders through
multiple pick zones without needing conveyor. The ability
to navigate is built into the bots themselves, so they can
see objects in their path and go around them or stop and
wait for the object to pass. Effidence makes a picking cart
that follows a picker through the warehouse so the picker
doesn’t have to push/pull a heavy load. And Bionic Hive’s Squid
works in a conventional warehouse with standard pallet rack. Units climb the vertical
uprights in the racks to pick cases and deliver them to picking/packing stations.
Material Movement Bots
Each picking is one of the hardest problems to solve inside the DC.
But new solutions are getting closer to achieving what once
seemed impossible. Lights-out autonomous bots often include a
picking extension or arm, with varying levels of machine learning
so that the bots can execute tasks and make decisions on their
own. At this level, the bots have potential applications that go
beyond picking to include packing and sorter induction.
Lights-Out Picking Bots
Co-bots include self-driving shuttles designed for heavier payloads, enabling
batch picking with help of a human with the addition of multiple totes and
pick carts. These can be paired with a pick cart or mobile put wall for more
efficient batch or cluster picking solutions. The
software works with a number of
different warehouse execution
systems to enable greater
autonomy and expand the
type of tasks you can assign to
the bots.
Co-Bots (Collaborative Robots)
Business Case• Productivity• Labor savings• Flexibility• Greater efficiency through cluster picking• Flexibility to scale operations up/down quickly
Business Case• Productivity• Labor savings• 24x7x365 availability• Flexibility to tackle different tasks
(picking, packing, induction)
source: MIR
source: Clearpath Robotics
source: Rocla
source: Geek+
source: 6 River Systems
source: Karis Pro
Within the DC drones can provide an effective means of
inventory cycle counting, or a way to locate missing inventory
in a warehouse. Wal-Mart is testing drones in warehouses and
reported that its drones can check a full warehouse of inventory
in about a day. That process previously took up to a full month
to do manually.
Drones in the DC
Business Case• Safety (ergonomics of people on lifts counting)• Labor savings• Inventory accuracy
source: Pinc
The technology that makes lights-out picking
bots possible are the unique grippers and arms
available. Products vary—they are sometimes
soft, fragile or irregularly shaped. They can be
transparent, reflective, or geometrically
inconsistent. All of these factors amount to infinite
variability and a significant degree of chaos for a machine to
interpret. The annual Amazon Each Picking Challenge has really
accelerated learning by bringing together some of the best
minds in robotics to develop solutions that may someday offer
a practical and affordable way to
accomplish the task.
Grippers
sour
ce: I
am
robo
tics
source: Laevo
An exoskeleton transfers force from the rest of the body, including chest and
back, to the thighs. Third-party logistics provider GEODIS is piloting the use of
an exoskeleton by Laevo. When the employee bends over, the spring pushes back
so that the load on the back is reduced by 40%. This has great implications for
safety, ergonomics and productivity, but also has potential over the long-term
to enable employers to tap into alternative labor pools, such as older workers
and those with disabilities.
Exoskeletons
Second generation Smart Glasses are addressing some
of the challenges (weight, battery life and overheating) of
earlier models that were built more for consumer
than industrial applications. Full augmented reality (AR),
where full-sized text is overlaid on top of the "real
world" scene the wearer is viewing, starts to deliver
on promise of this technology. Initially, the primary
applications for this technology are for picking - projecting visual
cues and directions for order fulfillment tasks into a wearer's field of view.
But down the road AR could be used for tasks, such as receiving,
putaway, placement of items to a
put wall, training, troubleshoot-
ing and remote maintenance.
Augmented Reality
Machine learning is what enables all of these technologies to make better decisions about the best route, the best way to pick up an item and the most efficient process, in order to truly optimize processes and workflows.
Much of the data we process to make decisions is still very unstructured – machines using algorithms can do a better job of making meaning from it and potentially make better decisions as a result. But what machines today lack is flexibility that is inherent in humans.
Google Brain was founded five years ago on the principle that artificial “neural networks” that acquaint themselves with the world via trial and error, as toddlers do, might in turn develop something like human flexibility.
In the not-too-distant future, your transportation fleet will make real-time decisions based on traffic, weather, expected delivery times and make constant adjustments and tweaks. And robo-execution software will oversee fulfillment decisions in your DC, optimizing workflow from end-to-end across people, processes, systems and equipment.
Machine Learning
Next generation distribution requires more than technology. It also requires great software to link together people, processes, systems and equipment into an overall solution. Software is what enables the DC to prioritize orders on-the-fly and optimize the work flow.
WES provides:• real-time end-to-end visibility to all these things• better insights, faster speed, greater optimization of both labor and assets• flexibility to scale operations for an unknown future• flexibility to switch technologies without ripping out the entire system (requires agnostic WES)
WES is a key enabler, but greater value comes from an overall solution that marries the right design with these advanced software features.
Warehouse Execution Software (WES)
Business Case: • Safety• Ergonomics• Productivity
Business Case: • Productivity• Accuracy - reduced error rates• Increased employee satisfaction• Safety-hands-free picking
Palletizers have been around for a while, but the ability to address
the more complex task of depalletizing multi-SKU and random pallets
has just recently been made possible through machine learning.
Kinema offers a self-training, self-calibrating software solution
for robotic depalletizing. The bots 3-D sensors “look” at a pallet to
determine the shape, size and weight of items. And its algorithms
determine fastest, most efficient way to depalletize the items.
Robotic Depalletizers
Business Case• Labor savings• Increased accuracy• Productivity• Reduced product damage
source: Soft Robotics
source: Righthand Robotics
source: Kinema Systems
This technology is still just over the horizon in terms of maturity,
but great strides are being made toward robots of the future that
can move like humans. The ability to augment a human workforce
with a robotic one is a long-time vision that is starting to take real
form and substance.
Humanoid Robots
source: Boston Dynamics
Business Case• Productivity – reduction in travel time• Flexibility - on-demand expansion as business grows• Ergonomics – Workers don’t have to push/pull heavy pick carts
source: Locus Robotics
Emerging Technologies: Maturity
GTP - AS/RSshuttle systems
Robotic Depalletizers
WES
Machine Learning
Co-Bots
Exoskeletons
Humanoid Bots
Drones
Augmented Reality
Lights-Out Autonomous Bots
Material Movement Bots
Truck Loaders
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Production Pilot ConceptualInitialImplementation
source: Daqri
source: Vuzix