emerging technologies - fortna · 2017-10-19 · emerging technologies for the distribution center...

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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