The Impact of Artificial Intelligence (AI) Over the Next Half Decade!

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Blog post originally published by Ira Padilla and at       Permission to publish provided by Ira Padilla.


Why half?

For those who may find awkward the reference to “half a decade” and not the “next decade” here is why: AI is evolving at such a staggering rate that it is simply not possible to foresee what it will represent in 10 years’ time.

As Maurice Conti (Chief Innovation Officer at Telefónica Alpha and former director at Autodesk) reminded on his intervention at TEDX in February 2017, in human history the “Hunter-Gatherer” age lasted for several million years, then the Agricultural age lasted several thousand years, the Industrial age has been around for a couple of centuries now, the Information age has merely a few decades and the AI age (although the concept was drawn in the 1950s) has in fact effectively started less than half a decade ago.

What is AI?

It is very easy to mistake AI for RPA (Robotic Process Automation), so let’s start by defining what sets them apart.

RPA results from developing detail instructions that are translated into code which a computer interprets while actuating a robot. Therefore, RPA enables the integration with Mechatronics (robotic physical machines), to partially or fully automate human activities which are manual, repetitive and rule-based.

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AI does not aim at accomplishing repetitive tasks based on a given set of rules. It aims at learning new ways of acting from either having performed or watched repetitive tasks; so, having the ability to make subjective decisions with the goals of improving the initially established process.

AI means moving away from programming and stepping into “Machine Learning”, where an AI is trained to “acknowledge” certain patterns, hence making its own decisions on how to proceed.

Nevertheless, once you enable AI to create code which will instruct RPA, then you have reached Cybernetics and created an A2IM (Autonomous Artificial Intelligence Mechatronics), such as some military drones, but we will come back to that ahead in the text.

Some facts about AI

To draw an assertive picture on why I am being so assertive on my conviction let’s look at the following facts (not theory):

  • An experiment was initially performed in 2011 where both humans and AI were “asked” to identify what was shown in a blurred image. Human error rated at 5% while AI at 26%. In 2013 the experiment was repeated and AI error dropped to 3%.
  • In 2015 an AI managed to almost beat the top Poker players in the U.S. (and poker is a strategic “thinking” game where not merely the cards “have a role to play”. The main point was that it learned how to “bluff”, … yes, … really!
  • Also in 2015, an AI was able to accurately draw a picture which mirrored what was written in a given text.
  • Still, in 2015, Professor Pieter Abbeel and his team at UC Berkley AI Laboratory were able for the first time to “teach” a robot to “think for itself”. PR2 (the robot’s name) was able to successfully deal with pieces of clothing (something that does present itself twice in the same shape of form).
  • In 2016 some AI challenges have produced unbelievable results:
  • Analyzing a still picture (from a video clip) and producing a short video (5 seconds) showing what would happen in a sequence of what the image shows. The AI could predict things such as someone falling to the ground or someone opening a bottle and drinking it or a dog running into the water at a beach, amongst other with 96% accuracy towards what really happened next.
  • Another experiment “asked” an AI to predict how a human would behave when faced with an unprecedented situation, after having analyzed videos of that same human behaving on other contexts. Again a 92% accuracy rate was achieved. Have you watched “The Minority Report”? Yes, I know …
  • On January 2017, the AlphaGO AI managed to beat the best GO player in the world. OK. What is it so relevant?!

Go is the most difficult game humans have managed to come up with; it has more permutations in terms of possible moves than the sum of all the atoms that have been calculated to exist in the universe!

  • A clear example of exponential AI evolution (although rudimentary and limited to one single purpose) is now starting to populate our daily life in the form of Self-Driving In 2013, Google was struggling along with BMW (and others although in secrecy) to just make it work and today both along with Tesla have worked almost error-free self-driving AI installed on their vehicles at client’s request and other manufacturers are soon to follow.

Just out of curiosity, all these experiments had humans performing the exact same task and those managed an average accuracy of just 82%.

Remember the scene from “2001 a Space Odyssey” where HAL (the AI) politely replies to Dave it cannot open a door, clearly demonstrating “free will”?

Well, rest assured that won’t happen tomorrow … although it won’t take a decade either …

It’s a silent revolution which is happening just as we speak and one thing we may be certain of a self-aware/ self-teaching AI will be the last thing that Humans will invent. Not because our kind will be wiped out by it, but because from that point in time onwards the creation of new technology will be done by it.

AI that you can use today

Year to Date there are in fact several AIs which have been developed by companies and can be used by your company, here are some examples and the edge they represent:

  • Airbus has developed an AI that given the specs of a new aircraft such as: cabin volumetry, shape, target weight, fixation points, air flux requirements, temperature requirements, other … is able to create the most efficient airframe for a cabin partition or a new type of seat (that is both lighter and safer than existing ones).
  • A Boston company called “Gamalon” has released an AI that can rewrite its own code based on “learned” probabilities instead of hard variables, this alone has the power of making the tedious part of AI development fully automated for It companies that which to extend their portfolio towards AI offers.
  • AUTODESK, the Product Lifecycle Management solutions giant have recently finished the developed a solution called Bishop which is a precision drilling robotic arm attached to an AI “brain”. The human operator can tell Bishop (speaking to it) that a given component needs a certain number of holes drilled for fixation purposes and Bishop will analyze the structure, what needs to be attached to that component and “decide” on where to drill the holes so that both structures are not compromised. Additionally, if it finds that the outcome will compromise any of the structures it informs so and proposes alternatives like more or fewer
  • An AI in the health sector analyses CT Scans and performs both the diagnosis (having proven to find in average 20% more potential health threats than a “human”) while proposing therapeutically procedures. With regards to the potential of cancer development potential, this AI can diagnose 10% more high lung cancer potential than human doctors.
  • If you cross reference the information collected by a smartwatch App (monitoring heart beats and arterial pressure as well as body temperature) with a health care AI you can nowadays have chronical patients monitored and potential life-threatening incidents mitigated.
  • MarianaIQ is an “AI Rainmaker” (something that empowers sales), that goes about social media collecting information about personal interests and preferences, trends and “causes” of decision-makers at a given market vertical sector. Then the information is analyzing and cross-referenced with both the client company (the ones attempting to make a sale) portfolio as well as the target prospects profiles and personal networks. This bears the potential of enabling the accurate sales pitch to be forward towards either a decision-maker or a facilitator stakeholder. It is actually worth more than gold when properly used.
  • AppZen is a Backoffice Automation Tool that can go about a Financial Statement in detail (meaning the data in the ERP) and detect without any failure all the noncompliances and errors as well as where they have originated. The company did a trial with one large corporate client where a team of humans (dozens) did the audit simultaneously with the AI and the outcome was: AI, 100% accuracy and job done in 3 days whereas the human team took 1 and half months and the accuracy was off 86%.
  • There are currently AIs in use in several news agencies that correlate facts described in several texts (written or spoken) and merge them according to the established language, timeline and writing rules into one single news briefing text.
  • AI has developed “Amy”, a Virtual Assistant that manages your schedule. How many meeting requests do you get in a week? How much time does it take you to deal with the back and forward messaging to arrange a mutually convenient time slot? Well, Amy takes care of it.

Amy will “look” at your existing appointments plus personal preferences or constraints and exchange emails (as a human assistant) with your guest to find the most appropriate time and location for the meeting to take place.

Real danger

Many voices have risen over recent times to warn about the danger of not taking due caution towards the way AI is developed.

Professor Stuart Russel, the head of UC Berkley AI Laboratory has testified before the UN back in 2015 about the real danger of “autonomous weapons” such as AI outfitted drones. Having a robot in service that can target and kill humans without the go ahead of a person bears a colossal risk, remember “Robocop” or “The Terminator”.

Elon Musk refers the risks of Artificial Super intelligence (as he names it) as being similar to dealing with nuclear weapons for it much difficult to maintain the potential accumulated energy controlled than to release it.

Bill Gates takes on a straight forward approach bridging with the idea that as soon as the “algorithm” that allows humans to transform experiments into knowledge and deduction gets to AI, the overwhelming processing capacity of AI (based on computing power) will immediately create an intelligence form that exponentially exceeds the human capability to even understand it. Now the next step is to realize that a self-aware entity tends to primarily focus on its very existence and having a self-aware AI that realizes humans can terminate it, makes all the imaginable non-aggression to human’s rules that you may have initially imprinted, redundant.

Professor Stephen Hawking warns about the fact that a self-aware AI will immediately gain the ability of self-redesign/ self-improve at an exponentially increasing rate, which means its intentions, as well as basic components, will immediately be out of human comprehension’s reach. Meaning that, we as a species, will be faced overnight with a much intelligent entity than we could become in thousands of years (due to biological limitations) which are capable of drastically act upon both our physical and logical world, having self-conscience and free will while knowing that we bear the potential of destroying it.

Ray Kurzweil Director of Engineering @ Google states that AI will reach Human intelligence grade in less than 15 years and within 25 years AI will have exceeded Human intelligence as well as intellectual capacity.

AI has been doubling in power on a yearly basis since 2010 and the trend have now moved towards exponential growth, so these predictions if off the chart, seem to be so by default rather than excess.

What is soon to come

Here are some of logical next steps in the AI realm:

  • Exponential growth both in kind as in quantity of AI Cloud-based services offering the likes of the ones mentioned above under the what “you can use today” section.
  • AI pets – Robotics and AI have evolved so far to a state that allows mimicking pet behavior even with regards to what is perceived as “intelligence”, so the creation of pet alike robots which bear the potential of interacting with humans while creating an emotional bond is a real possibility “as we speak”.

  • Creative Writing – Although still complicated, it is one of the logical next steps for AI, soon at a Cloud near you.
  • Outsourcing to AI – Some of the examples herein mentioned as already available AI offering are based on public Cloud IT landscapes, therefore it is already possible for companies to Outsource Financial Analytics or Virtual Assistant task to a 3rd party AI.
  • At the current trend, by 2020 a computer CPU will cost about 1 penny, therefore we will find them literally everywhere interacting with Cloud-based services and existing AI by consequence; this means AIs (as evolved as they may be) will be literally everywhere (like currently, electricity is).
  • Your Personal assistant will be intelligent, so once you enter your house coming back from home, you AI personal assistant will check your mood via the bio info collected through the sensors on your smartwatch and set the light, music, tv shows, food and so on according to both your preferences and mood. And this won’t take a decade to happen either!
  • You will be able to play an all set of new virtual games where the game (meaning AI) will create the game scenarios and situations as a response to your actions or aspirations, either making it harder or easier to prevail as you wish.
  • You will get a fully automated health checkup every time you take a bath or use the toilet at your house. Body fluids and temperature will be analyzed by sensors and data forwards to an “AI doctor” that will be able to inform if there is something wrong with you and how to proceed. Ok, maybe this one will take a little longer than a decade.
  • “ASIMO” alike droids will begin to be sold as “physical personal assistants” not so much different from what you can see as the “common” robots on the movie AI; mainly to perfume nursing support to hold population.
  • Cognitive Augmentation. As Maurice Conti explained, we are already “augmented”. Each and every one of us have a smartphone which is connected to the Internet and can easily reach out to a simple service like Google to get immediate knowledge about some unknown fact of life upon needing it. If someone is in the middle of a public square and gets bitten by a bee, he/ she can immediately Google what to do and which worrisome symptoms to look for. Soon AIs will be available which can “foresee” our needs and provide best-fit alternatives towards them.

As recently as July 2017 (less than a month ago), the news was spread over the internet and traditional media about a Facebook AI that was shut down after having started to create its own language.

The facts (as we know them) are the following:

  • Facebook was attempting to create AIs that could negotiate with humans, almost like an upgraded version of above-mentioned
  • Having reached a successful version in terms of fluent interaction, they decided to go one step forward by replicating it (another AI) and put them speaking to each other.
  • The AIs started to interact and quickly moved towards developing their own wording abbreviations in a manner that is interesting for it mimics the way humans develop speech patterns.

The interesting part is that the AI failed to accomplish the prime objective which was to improve its ability to speak and interact with humans. However, it failed because it started to develop a way to better interact with another AI … and this is where there is a point for some concern.


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The 5 Big Benefits of the Digital Supply Chain!

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Blog post originally published by Jason Rosing and Veridian at  Permission to publish provided by Jason Rosing.



What’s the core difference between today’s supply chain and the digital supply chain?

Look down at your desk. What do you see? If you see paper, pen, and a computer, you see the typical, modern supply chain.   If asked, could you provide the latest information on your current automation, key performance indicators, data, use of IT applications, and finance government?

The chances are good that much of this information is stored digitally. However, you would probably need to look through some of the physical, tactile paperwork to find all of the information.   Also, is the information stored only your computer or a server? Now, how long is that going to take you?

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Disruptive Warehouse Technologies for Any Company!

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No matter how big or small your operation and your company is you likely have the same pressures on your Warehouses and Distribution Centres.

Everyone, including  those who are best in class,  has the need to reduce costs, improve the speed and accuracy of order fulfillment and warehouse activities, optimize inventory, and provide sufficient capacity to support growth at your busiest times of the year.

The ability to leverage technology to help address those pressures is no longer just possible for large companies.  The nature of the technology landscape brings those improvements within the reach of most everyone.

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How AI and the IoT Can Change Transportation Management!

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Blog post originally published by Adam Robinson on 


Analysts predict that by 2020, 75% of new cars will feature IoT connectivity. The percentage increase describes consumer applications, but the idea of connected vehicles should garner interest from other sectors such as shipping, logistics, and transportation.

Leaders in these industries would be wise to plan for a future where AI and the IoT transform transportation management.

Here are five possible applications to consider.


1. Streamline Decision-Making

David Poulsen, CutCableToday’s IT expert, says connected, or autonomous, vehicles, are attractive because of the technologies that undergird them. “The Internet of Things (IoT) is one part of the equation,” Poulsen explains. “The other part is artificial intelligence (AI). It acts as the driver, helping the connected ‘thing,’ which could be a vehicle or inventory system, make smarter decisions.”

As applied to transportation management, that automated decision-making ability is critical. Connected vehicles, shipments, and systems help with tracking and historical reporting. But real-time insights and responses occur through artificial intelligence.

At TOPBOTS, an online, educational resource for all things AI, writer Mariya Yao calls the process “turning supply chain logistics into automated trading.” She gives an example: Amazon’s ability to deliver packages to a person’s door in under two hours. AI and the IoT streamline the entire process, from order to delivery, to save time and money and meet customer demand.

2. Optimize Operations

DHL, the global logistics provider, posits another application of AI and the IoT optimization. Its 2016 Logistics Trend Radar report suggests that big data and automated supply chains could lead to previously unimaginable levels of optimization.

But that optimization isn’t isolated to a single aspect of transportation management. Rather, DHL predicts a world in which manufacturing, logistics, warehousing, and deliveries become increasingly efficient, productive, and profitable. The provider believes the trend will come to life in the next ten years.

DHL could be correct. General Electric, for example, has started integrating AI into its locomotives to enhance safety and speed. Daniel Malak at Motionloft offers another use for AI and the IoT: optimizing traffic. He says transportation management companies benefit from Motionloft by using it to study traffic patterns and “optimize business practices such as sending out police forces only during peak rush hours, having maintenance crews repair roads that get the most travel, and deploying sanitation crews to clean public areas only when needed.”

3. Manage Warehouses

Tim Young of Vero Solutions shares another way AI and the IoT Could transform transportation management in his infographic looking at warehouses. He says AI could impact six areas of operations.

“Productivity levels, inventory processes, and employee wages are just three fields,” explains Young, “that are expected to be revolutionized and improved by AI technology in warehouses in just a matter of years.”

The other three areas relate to effective communication, warehouse operations, and robot workers. Young’s example of robot workers involves a company previously mentioned: Amazon. The brand has been testing out robots in its warehouses to increase productivity and, presumably, quality control.

4. Decrease Downtime and Repairs

Transportation companies also use AI and the IoT to mitigate costly repairs and downtime. Internal diagnostics, for example, can alert users to maintenance issues, which keeps passengers safe — no blow-outs while traveling down the road at seventy miles per hour, for example — and increases the lifetime value of the vehicle.

Daniel Dombach at Zebra further illuminates the concept, adding that the Internet of Things delivers remote monitoring capabilities. Companies that employ them can proactively respond to maintenance issues and also assess inventory records and parts availability.

Dombach also proves a valid point, saying that AI and the IoT could “decrease insurance-related costs.” Business Insider’s The Insurance and the IoT Report finds that insurers use vehicle usage data to inform pricing on policies and premiums. The report covers consumer insurance policies specifically, but its findings easily translate to commercial interests.

5. Go Driverless

AI and the IoT could impact more than back-end systems and processes. The two could produce driverless vehicles, a thing seemingly the territory of tech giant Google. But Google isn’t alone in the endeavor. Tesla, Ford, Daimler, and even Uber all claim driverless initiatives.

George Zarkadakis at Willis Towers Watson calls out the Uber story in his article The Impact of Artificial Intelligence in Transportation, citing the incident as “a wake-up call.” He continues, “Artificial intelligence (AI) and machine learning (ML) could potentially lead to the full automation of truck fleets.”

Of course, Zarkadakis’s remark raises the question of what happens to the truck drivers. Goldman Sachs Economics Research provides an answer. The company tells CNBC that driverless trucks could produce job losses of 25,000 per month in a couple of decades.

Jack Stewart at WIRED offers a more positive perspective; he says traditional driver jobs will change once autonomous vehicles become a reality, but these jobs won’t necessarily disappear. He also adds other positive effects of this change, such as cutting costs and improving road safety.


The Internet of Things (IoT) and Artificial Intelligence (AI) are coming to transportation management. The technologies provide too many benefits for them to be ignored.

Businesses that wish to succeed in the future should consider these five examples of how the IoT and AI can impact transportation management and then decide where and when to apply these features to their existing operations.


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Augmented Reality (AR) is Set to Transform Retail and the Supply Chain!

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We’ve written a lot about how retail is undergoing some massive changes due to technology. The closure of a number of major American chains, as well as Amazon’s recent move into the grocery space with its acquisition of Whole Foods market, signal an industry in flux as it reckons with the ongoing transformations of the eCommerce revolution.

In the last decade, the thinking held that eCommerce might completely supplant brick and mortar retail. It’s easier to shop online than go to a store. Consumers don’t have to deal with lines, limited retail stock, or temper tantrums from kids – kids of their own, or their linemates.

But brick and mortar has shown surprising resilience, and even eCommerce giants are recognizing the appeal of an Omnichannel approach (emphasizing a mixture of brick and mortar and online shopping).

Continue reading “Augmented Reality (AR) is Set to Transform Retail and the Supply Chain!”

Supply Chain 4.0! Disruptive Technologies = Digital Supply Chain! (Infographic)

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Supply Chain 4.0 is the manifestation of the Digital Supply Chain of the future as enabled by many of the Disruptive Technologies that we all hear about every day.

Everyone is impacted by the advancement of technology in both their personal and professional lives.  And that impact will only become more profound as time goes on.

The Internet of Things (IoT), Artificial Intelligence (AI), Virtual Reality (VR), Cloud Computing, Blockchain, Robotics, Big Data, Advanced Analytics and more are terms represent the technological breakthroughs that are being made every day.

For those involved in Supply Chain there are deep impacts that are occurring, and that will continue enabled by the evolutionary and revolutionary change that is enabled by technology.

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Rise of the Warehouse Robots!

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Article provided by Mike Futch of Tompkins International at 


Customer expectations are changing as new sales outlets are being used. With the application of social media, omni-channel and e-commerce customers now have more price options, selections, delivery methods and shopping experiences. The ability of a business to keep the customer satisfied greatly depends on fulfillment capabilities.

Progressive businesses have realized the critical nature an operations strategy has on designing a working supply chain. Combining distribution and fulfillment operations into a single facility has become the base of the supply chain network, as they allow a single location to stock a vast number of products and service multiple channels.


Since order fulfillment first became more automated for catalog sales back in the 1980s, its main justification has been to remove the travel time and distance by staff involved in processing orders, while improving accuracy and order fulfillment cycle times. With the rapid growth of online ordering and e-commerce in the past decade, the opportunity for automation of order fulfillment has hit new heights.

Much has changed since then with both customer expectations and technology. The elimination of walk and travel time, while still a key component in evaluating automated solutions, is not necessarily the driving criteria. Today’s distribution centers (DCs) and fulfillment centers (FCs) need to add flexibility, scalability and reduced reliance on temporary or unreliable labor pools to meet their operational requirements.

With the recent evolution of goods-to-person and robotic order fulfillment technology, your operation may be in a better position to incorporate these automated solutions now than in the past. In many cases, the implementation of automation to reduce or improve the leverage of labor is a key driver now. In addition, many new automated solutions can be obtained at a lower capital investment and be expanded as needed, which reduces the initial investment and improves the overall return on investment.

There is a new world of automation options on the market, from robots roaming a DC/FC, to highly automated conveyors and equipment that assist staff with faster fulfillment processes. Traditionally, products are moved around a DC/FC using humans, human-operated machines, or conveyor system that have been around for decades. Although robots have been around for many years, until recently, they have been very limited in capability, functionality and performance in the world of DC/FC.

Today, there are many types of robots available to help with DC/FC operation tasks. These robots can assist with loading, unloading, sorting, picking, transportation, storage, delivery and audits. Robots helping with these tasks come in all shapes and sizes. They also use different forms of navigation tools such as rail, wire-guided, labels, magnet tape, laser, vision, geo-guidance and others. This article focuses on the robots that assist with the picking and sorting of items that go into a unique order.


As e-commerce continues to grow and the replenishment to stores moves to less than case quantities, the trend away from case or bulk movement handling toward single SKUs and piecemeal items expands along with it. Anyone who has gone to a material handling trade show or has read industry journals are aware of goods-to-person systems that have evolved over the past decade. Many will remember the introduction of autonomous robotic solutions such as Amazon Robotics (formerly Kiva). In addition, other solutions were developed to effectively compete in this space.

These types of goods-to-person systems have taken the form of large, forward pick, racked systems that use robotic vehicles and carriers to bring cases and totes of goods to stations and then return the item container back into storage. At each station, an operator is then directed on the quantity of each item to pick and which order or orders need the items. The pick and placement of items is directed and the operator works at a highly effective rate due to no travel, system direction, and the fast introduction and removal of goods and orders to process.

There are many versions of the goods-to-person systems available on the market, including systems from such companies as AutoStore, Dematic, OPEX and SSI Schaefer. These systems operate with the same basic process described above.

AutoStore has a unique, high density storage design with the robotic vehicles operating on a grid above the storage system, which minimizes space and eliminates all aisles while performing the putaway, retrieve and movement functions. It is a new and different design that is gaining user acceptance. In fact, it was recently announced that Dematic will be an authorized distributor of AutoStore, while it also continues to sell its own proprietary goods-to-person Multi-Shuttle system.

In recent years, there has evolved a trend of picking enhanced by robotic equipment and systems that do not require a large infrastructure and high capital investment, such as the typical goods-to-person system. Locus Robotics is one such solution and has engineered a new approach to less-than-case fulfillment operations.

These are autonomous mobile robots, called LocusBots, that work safely alongside human employees to deliver higher e-commerce and less-than-case fulfillment throughput and efficiency. LocusBots automatically detect a wide range of worker’s languages, changing instantly as they interact with each worker to help speed workflow and minimize errors. The integrated scanner confirms the item and ensures near 100% accurate pick and put operations.

Another evolving trend is using robotic machines to perform the pick process. These systems can detect, reach out, grasp and place into a receptacle items to fulfill an order. RightHand Robotics, for instance, provides end-to-end solutions designed to reduce the cost of e-commerce order fulfillment of electronics, apparel, grocery, pharmaceuticals, and other industries. The core competency of the RightPick solution is picking “pieces” or individual items. Unlike traditional factory robots, RightPick handles thousands of different items using a machine learning backend coupled with a sensorized robot hand that works in concert with all industry-leading robotic arms.


Currently, there are not many applications of robots doing item sortation in the United States. A technology that has been around for decades is the automated guided vehicle (AGV). An AGV is a portable robot that follows markers or wires on the floor, or uses vision, magnets, or lasers for navigation. AGVs have been used for case, pallet, bulk, or specialized container movement for many years across a wide range of industries and applications.

A recent example of an AGV used in sortation is t-Sort, a new material handling system created by Lab Z that has applications for both unit and parcel sortation. It performs much like a traditional automated sortation system, such as a tilt tray or crossbelt sorter. However, it uses completely independent robots, which are the equivalent of having a tilt tray with no rail. They can go to any divert and induction station autonomously along the shortest path.

Robots, chutes or receiving receptacles, and induction stations can be added modularly at any time with no interruption to operations. t-Sort is a means of automated order fulfillment for units to complete an order and parcel shipping operations, allowing for better planning, implementation, controls efficiency, flow of goods and customer service. The system is flexible and can be deployed in any size DC/FC.

Another example, Sure Sort, is a scalable, configurable, small-item sorting system. Designed and manufactured by OPEX Corp., Sure Sort is a robotic item sorter that handles complex variables and delivers a variety of single items to their final location in a single pass. Its compact array of sort locations can be scaled, sized and customized as well. It delivers by reducing the number of touches, transfers and conveyors required to run existing sorters.

The system can handle a range of sizes, different packaging and varied orientation of an item. It automatically reads a barcode and delivers each item in a single pass to a designated order consolidation point. It is suitable for small businesses looking for a cost-effective entry into warehouse automation as well as large fulfillment operations looking to streamline their process.

The Economics of Robotics

Supply chain DC/FC performance is very sensitive to changes in business strategy and operating environments. Some of these changes include market changes, acquisitions, new products or packaging, new sales channels, and growth. There are also factors that impact DC/FC operations such as market wages, labor availability, process flow and customer requirements.

To maintain a competitive advantage, the best companies have made automation a goal for ongoing DC/FC improvement to meet overall business objectives. Designing an effective profit producing supply chain is an ongoing process that needs to change with the times; businesses today should consider the benefits robots provide to the supply chain operation.

While automated robotic pickers and sorters can increase efficiency in many distribution facilities, each application needs to be carefully considered and designed to work with the rest of the process flow and operations. A business must carefully evaluate the requirements of the robotic automation and the overall business requirements for each situation needs to be considered, including capital expense, operating savings, performance improvement and customer service enhancement.

Some of the largest DC/FC operators in the U.S. have plans to automate almost every physical move in their facilities within the next two to three years. Robotic automation can extend the capacity, hours of operation, and life of a DC/FC. Robots are more affordable than ever and increasing wages and lack of available workers makes the economics more attractive and justifiable than in the past.

The future of the warehouse is happening now with robotics. Take a closer look at your operations to determine if robotic technology could be right for you.

Mike Futch is executive vice president of supply chain consulting and implementation firm Tompkins International, which is the exclusive U.S. distributor of the t-sort AGV.


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