Warehouse Automation
Assembly Line
World’s most advanced robotic warehouse (AI automation)
UPS Worldport: Inside the Giant Logistics Powerhouse
PepsiCo installs its first automated warehouse in Poland with Mecalux
PepsiCo, a global leader in food and beverages, has installed its first automated warehouse in Poland, its most sustainable in Europe. Automation facilitates production with the push system, which involves manufacturing in advance to meet anticipated demand.
The facility was designed in line with the push system, which involves manufacturing in advance to meet anticipated demand. While this method reduces unit costs, it requires sufficient space to manage large production runs. With 9,000 locations, PepsiCo’s new finished goods warehouse receives a large number of pallets daily, loaded with ready-to-ship bags of potato crisps for clients. “The production process is fully integrated with the automated warehouse. Each potato crisp bag is transported from the manufacturing area to final packaging, ready to be picked and loaded onto the lorry,” says Pietrusa.
Transporting goods internally between storage and production is now faster thanks to electric monorail and conveyor systems for pallets. These solutions also connect the warehouse with the docking area, facilitating the shipment of thousands of pallets a day. The electric monorail deposits pallets ordered by clients into five double-channel live roller conveyor lines. Each channel has a 34-pallet capacity. SKUs are grouped according to delivery route, vehicle type, client and shipping priority, among other factors.
Inside the World's Most Advanced Robotic Warehouse (AI Robots)
Mytra Unveils Breakthrough Robotics and AI to Transform Warehouses and Boost Economic Productivity
Mytra, the company supercharging industrial productivity with first-of-its-kind three-dimensional robotics, launched with $78 million in total financing through the Series B stage and several commercial partners, including Albertsons Companies. Founded by ex-Tesla and Rivian robotics and manufacturing leaders, the company will automate the most common industrial task: moving and storing material. Mytra is backed by several investors, including Greenoaks, who led the company’s Series B, Eclipse, who led the previous seed and Series A rounds, in addition to Co-founder and Chairman of Okta Frederic Kerrest’s 515 Ventures, and individual investors, Garry Tan, Lachy Groom, among other individual and corporate partners.
Mytra systems are infinitely customizable, shapeable, scalable, and high-density, allowing them to automate complex pallet and case handling without the complexity of forklifts, pallet jacks, conveyors, elevators, and other automation. This radical simplicity is enabled by three key breakthroughs:
- Simplified offering: Unlike other solutions that involve thousands of parts and saddle customers with technical debt, Mytra comprises only three individual components: bots, a simple and repeating matrix structure, and edge-intelligent software, which simplifies the deployment process, reduces cost, and avoids single points of failure.
- 3D movement: Mytra is the first system that allows for full 3D movement at up to 3000 pounds from any cell to any adjacent cell in any direction. This achieves the physics-limited maximum level of flexibility.
- Software: Mytra’s software platform optimizes bot routes, manages inventory, and continuously learns and improves, adjusting to changing customer needs. This approach entirely abstracts the hardware layer and makes material flow fully software-defined, allowing operators to unlock endless new applications and future-proof their operations.
New AI-powered dynamic slotting simplifies warehouse reslotting with click of a button
Distribution center technology provider, Lucas Systems, announced its next generation of Dynamic Slotting, a warehouse game changer for providing in-the-moment reslotting decisions, thanks to the powerful use of AI. Lucas Systems’ software will intelligently sift through an abundance of warehouse data to serve up optimal slotting recommendations. The results take minutes to generate, whereas traditional slotting analysis often takes months to complete using engineering resources or consultants.
Dynamic Slotting’s recommendations identify product moves that offer the biggest potential payback. Hundreds of parameters are taken into account including demand seasonality, item size, SKU velocity and costs. Its similarity detection prevents placing related items side by side to reduce picking errors. Lucas Systems’ Dynamic Slotting promises 20-40% increase in throughput because it recommends best locations for inventory based on SKU velocity, SKU affinity, product/slot information, pick paths and other data.
UPS relies on Geekplus during automation journey
UPS Supply Chain Solutions, which has been in warehouse and distribution for more than 30 years, is in the midst of a large push toward automation in its 35 million square feet of warehouse space globally. UPS SCS has been working with Geekplus to automate North American facilities for the past few years. The most recent project is the UPS Velocity facility in Louisville.
Warehouse automation also helps UPS SCS deal with customer growth. Stearman told the audience about a customer that needed 50-percent more capacity. Immediately. In a six-week period, his team brought in additional Geekplus QR-based robots and racks to meet that need. With other warehouse automation providers, he said, something like that could have taken anywhere from 6 to 18 months.
Boosting logistics process at ABB’s instrumentation factory in Italy with robotic automation
Inside the Automated Warehouses of Retail Titans
Covariant Announces a Universal AI Platform for Robots
Covariant is announcing RFM-1, which the company describes as a robotics foundation model that gives robots the “human-like ability to reason.” “Foundation model” means that RFM-1 can be trained on more data to do more things—at the moment, it’s all about warehouse manipulation because that’s what it’s been trained on, but its capabilities can be expanded by feeding it more data. “Our existing system is already good enough to do very fast, very variable pick and place,” says Covariant co-founder Pieter Abbeel. “But we’re now taking it quite a bit further. Any task, any embodiment—that’s the long-term vision. Robotics foundation models powering billions of robots across the world.” From the sound of things, Covariant’s business of deploying a large fleet of warehouse automation robots was the fastest way for them to collect the tens of millions of trajectories (how a robot moves during a task) that they needed to train the 8 billion parameter RFM-1 model.
Agility Robotics Brings Operational Visibility to Deployment of Digit Fleets with the Launch of Agility Arc™
In its first iteration, Agility Arc will provide customers with operational visibility into critical KPIs like uptime, throughput, Mean Time Between Incidents (MTBI), and robot status, allowing customers to understand what’s happening in the workcell and how Digit is performing. Additionally, Agility Arc will provide industry standard APIs to simplify integration with existing Warehouse Management Systems (WMS), Warehouse Execution Systems (WES), and Manufacturing Execution Systems (MES) among others.
Amazon to invest in start-ups that combine AI with robotics
Amazon’s $1bn industrial innovation fund is to step up investments in companies that combine artificial intelligence and robotics, as the ecommerce giant seeks to drive efficiencies across its logistics network. The industrial innovation fund is seeking to invest in start-ups that can support the ecommerce group’s aims of becoming “more efficient, safer for our associates, and increase the speed of delivery to our customers”, Bossart said.
Amazon has innovated in robotics before: in 2022, the company said it had invested more than €400mn in technologies that include industrial robotics and sorting systems in its European warehouses. It has deployed 750,000 mobile robots across its operations network.
New AI model could streamline operations in a robotic warehouse
Getting 800 robots to and from their destinations efficiently while keeping them from crashing into each other is no easy task. It is such a complex problem that even the best path-finding algorithms struggle to keep up with the breakneck pace of e-commerce or manufacturing.
The researchers built a deep-learning model that encodes important information about the warehouse, including the robots, planned paths, tasks, and obstacles, and uses it to predict the best areas of the warehouse to decongest to improve overall efficiency. Their technique divides the warehouse robots into groups, so these smaller groups of robots can be decongested faster with traditional algorithms used to coordinate robots. In the end, their method decongests the robots nearly four times faster than a strong random search method.
The technique also streamlines computation by encoding constraints only once, rather than repeating the process for each subproblem. For instance, in a warehouse with 800 robots, decongesting a group of 40 robots requires holding the other 760 robots as constraints. Other approaches require reasoning about all 800 robots once per group in each iteration.
OSARO Debuts AI-Powered Robotics for Mixed-Case Depalletization
The OSARO® Robotic Depalletizing System is a direct replacement for manual pallet unloading — even complex mixed-case pallets. The system combines OSARO SightWorks™ Perception with advanced robotics hardware to automate the incoming inventory process and improve safety, boost efficiency, reduce labor costs, and minimize inventory shrinkage.
Skechers Launches High-Tech Warehouse With Hai Robotics' Automated Goods-to-Person System
Skechers USA, a leading global footwear and apparel company, turns to Hai Robotics (“Hai”), a leading global provider of Automated Storage and Retrieval Systems (ASRS), as they launch their new distribution center in Minato City, Tokyo, Japan. Using Hai’s automated goods-to-person system, Skechers is maximizing warehouse operational efficiency, fulfillment speed, and order accuracy.
Within Skechers’ facility, the HaiPick System covers 139,705 square feet and is operated by 69 HaiPick Autonomous Case-handling Mobile Robots (ACRs), which are integrated with Manhattan Associates’ cloud-native warehouse management system (WMS). ACRs are highly intelligent, tall pieces of equipment that autonomously navigate narrow aisles of an ASRS constructed of almost any industry-standard racking or shelving with a vertical reach extending up to 32 feet. The robots pick containers off the shelving — transporting up to 8 at any given time for maximum order-batching efficiency — and deliver them to human-operated workstations.
RightHand Robotics Signs Multi-Year Agreement with Staples® to Deploy AI-Powered Picking Robots in Fulfillment Centers
RightHand Robotics, a leader in autonomous AI robotic picking solutions for order fulfillment, announces a multi-year agreement with Staples Inc., America’s leader in workspace products and solutions. The agreement allows Staples to deploy and install the company’s RightPick™ item-handling system to automate operations for higher service levels and Next-Day Delivery to over 98% of the U.S.
Self-Driving Vehicles Are Finding a Home in Industrial Operations
Kimberly-Clark credits hundreds of autonomous forklifts with helping the consumer-products company keep Kleenex facial tissue, Cottonelle toilet paper and other goods flowing to stores despite labor shortages during the Covid pandemic. Sharpie maker Newell Brands says the vehicles are helping deliver safety improvements and cost savings across the company’s operations.
Kimberly-Clark has more than 300 autonomous forklifts at its North American warehouses, up from about 30 in 2019, said Sarah Haffer, vice president of customer logistics for the company’s North America consumer division. Haffer said Kimberly-Clark’s warehouses with autonomous forklifts have provided some of the most consistent service levels to its retail customers. “We have been able to manage through Covid with real stability and beyond in terms of throughput and capabilities,” Haffer said.
Newell Brands, whose products also include Coleman outdoor recreation equipment and Rubbermaid food storage goods, uses more than 200 autonomous forklifts across its facilities. Newell Chief Executive Chris Peterson said robotic vehicles have reduced incidents of damage to goods and are delivering “significant cost savings.”
Accelerating Automation in Logistics with Simulation - A DHL Case Study
Coca-Cola Bottlers Japan Inc.－Akashi Mega DC
The Season of More: Unwrapping Our Plan for Speed, Accuracy and Availability
To start, we’ve invested in an AI-powered inventory management system that positions products according to customer demand. It’s patent-pending, so we’re confident it has set us up for success heading into the season and will continue to do so as holiday shopping kicks into high gear. For example, our AI can recognize a top-selling toy in a particular region, and automatically send more items to those stores. And if a toy is selling better in the Midwest compared to the East Coast, we can reposition inventory to that area of the country.
Additionally, we continue to rapidly expand the use of next-generation technology in our distribution centers. This year, over 15% of stores will receive merchandise from automated distribution centers, helping to get items off trucks and onto the sales floor faster and more efficiently. These centers play a pivotal role in stocking our stores while making it easier for associates to unload trucks and sorting products for hours. Instead, they can simply bring department-ready pallets directly to the sales floor, accelerating how quickly we can deliver products to stores and customers.
How to Train Autonomous Mobile Robots to Detect Warehouse Pallet Jacks Using Synthetic Data
This use case will again take a data-centric approach by manipulating the data, as opposed to changing the model parameters to fit the data. The process begins by generating synthetic data using NVIDIA Omniverse Replicator in NVIDIA Isaac Sim. Next, train the model with synthetic data in NVIDIA TAO Toolkit. Finally, visualize the model’s performance on real data, and modify the parameters to generate better synthetic data to reach the desired level of performance.
For this first batch of synthetic data, the team used the LOCO dataset, which is a scene understanding dataset for logistics covering the problem of detecting logistics-specific objects to visualize the real-world model performance.
Amazon Introducing Warehouse Overhaul With Robotics to Speed Deliveries
Amazon is introducing an array of new artificial intelligence and robotics capabilities into its warehouse operations that will reduce delivery times and help identify inventory more quickly. The revamp will change the way Amazon moves products through its fulfillment centers with new AI-equipped sortation machines and robotic arms. It is also set to alter how many of the company’s vast army of workers do their jobs. Amazon says its new robotics system, named Sequoia after the giant trees native to California’s Sierra Nevada region, is designed for both speed and safety. Humans are meant to work alongside new machines in a way that should reduce injuries, the company says.
Amazon said it would also start to test a bipedal robot named Digit in its operations. Digit, which is designed by Agility Robotics, can move, grasp and handle items, and will initially be used by the company to pick up and move empty tote containers.
📦 Inside Walmart’s Warehouse of the Future
“What this technology does for us is increases capacity, increases the accuracy of our loads, increases the speed of the supply chain and lowers cost,” said David Guggina, executive vice president of supply chain for Walmart. It is “also completely reshaping the way that our associates work within the distribution center.”
Kyle Silberger transferred from unloading trucks manually to what Walmart calls an “automated cell operator” about a year ago. “It’s easier physically and harder mentally,” said the 30-year-old who has worked at the warehouse for nine years. “It’s sort of autopilot on the loading dock,” he said, describing his former role.
GreyOrange Ranger Assist - Assisted Picking CoBot (warehouse automation solution)
🦾 Amazon’s New Robots Are Rolling Out an Automation Revolution
Proteus is part of an army of smarter robots currently rolling into Amazon’s already heavily automated fulfillment centers. Some of these machines, such as Proteus, will work among humans. And many of them take on tasks previously done by people. A robot called Sparrow, introduced in November 2022, can pick individual products from storage cubbies and place them into larger plastic bins—a step towards human-like dexterity, a holy grail of robotics and a bottleneck in the automation of a lot of manual work. Amazon also last year invested in a startup that makes humanoid robots capable of carrying boxes around.
Amazon’s latest robots could bring about a company-wide—and industry-wide—shift in the balance between automation and people. When Amazon first rolled out large numbers of robots, after acquiring startup Kiva Systems and its shelf-carrying robots in 2012, the company redesigned its fulfillment centers and distribution network, speeding up deliveries and capturing even more business. The ecommerce firm may now be on the cusp of a similar shift, with the new robots already starting to reshape fulfillment centers and how its employees work. Certain jobs will be eliminated while new ones will emerge—just as long as its business continues growing. And competitors, as always, will be forced to adapt or perish.
Packaging Automation: Making the Financial Case
The more you scrutinize the processes and all affected points in the supply chain and their associated value, the greater the possibility of a final ROC meeting corporate goals. It’s also essential to understand that every CFO or controller will have a firm grasp on the cost of money to the business as well as specific time targets for the realization of return. Many of our clients have realization targets of around two years. This is a much shorter timeframe than 40 years ago, which was closer to five years.
As you begin the documentation process, be aware that you should specify downstream equipment to easily recover from an upstream accumulation release. Typically, designers require that downstream equipment outproduce the immediate upstream process by 10-20%. Furthermore, as you start to block layouts for new equipment, it may require an ongoing line balancing by determining and coordinating the takt time of each corresponding step, ensuring that each phase in the process is more or less in sync with the next.
Amazon Turns to AI to Weed Out Damaged Goods
The AI checks items during the picking and packing process. Goods are picked for individual orders and placed into bins that move through an imaging station, where they are checked to confirm the right products have been selected. That imaging station will now also evaluate whether any items are damaged. If something is broken, the bin will move to a worker who will take a closer look. If everything looks fine, the order will be moved along to be packed and shipped to the customer.
Amazon so far has implemented the AI at two fulfillment centers and plans to roll out the system at 10 more sites in North America and Europe. The company has found the AI is three times as effective at identifying damage as a warehouse worker, said Christoph Schwerdtfeger, a software development manager at Amazon.
Comau’s MATE-XT wearable exoskeleton supports ergonomic well-being at John Deere’s parts distribution center in Brazil
Comau has equipped John Deere with multiple MATE-XT wearable exoskeletons to help sustain worker well-being, alleviate physical stress and reduce the ergonomic risk within its parts logistics operations. MATE-XT accurately replicates all movements of the shoulder, helping employees perform their jobs comfortably by reducing muscle fatigue without limiting mobility or adding bulk. Its ergonomic design can be easily adjusted to fit different people with different body types – changing the length of the shoulder straps and the required level of assistance based on the worker or the job at hand is quickly achieved in a few simple steps. Working closely with John Deere to implement the exoskeleton within its daily operations, Comau provided a hands-on training course held at John Deere’s 75,000m2 parts distribution center in Campinas, in the state of São Paulo.
Even when working with small and lightweight objects, the apparently minimal effort of repeated manual movements can take a toll on the body. To help John Deere quantify the benefits of using MATE-XT, Comau performed an electromyographic analysis of the ergonomic risk factor. MATE-XT kept the muscle at a rest stage for 98.5% of the activity time (compared to only 2.4% of the time without MATE-XT).
Warehouse Software Automation to Robotic Automation: Choosing a Scalable Solution that Matches Your Pace
In the past, the logistics chain was much more straightforward; warehouses delivered the bulk products on pallets to stores, and then consumers would travel to stores to select and purchase the items. Today, eCommerce fulfillment workers need to access thousands of SKUs that are ordered in random quantities and combinations and at random times. At the same time, warehouses struggle to attract workers in the current labor shortage.
Robotic automation in e-commerce fulfillment centers improves efficiency, productivity, and profitability while reducing labor costs in the warehouse. Traditionally, the most significant barrier to entry for warehouse automation was the cost, along with the necessary changes in infrastructure to accommodate it. Many robotic solutions require significant upfront capital investments.
How a universal model is helping one generation of Amazon robots train the next
In short, building a dataset big enough to train a demanding machine learning model requires time and resources, with no guarantee that the novel robotic process you are working toward will prove successful. This became a recurring issue for Amazon Robotics AI. So this year, work began in earnest to address the data scarcity problem. The solution: a “universal model” able to generalize to virtually any package segmentation task.
To develop the model, Meeker and her colleagues first used publicly available datasets to give their model basic classification skills — being able to distinguish boxes or packages from other things, for example. Next, they honed the model, teaching it to distinguish between many types of packaging in warehouse settings — from plastic bags to padded mailers to cardboard boxes of varying appearance — using a trove of training data compiled by the Robin program and half a dozen other Amazon teams over the last few years. This dataset comprised almost half a million annotated images.
The universal model now includes images of unpackaged items, too, allowing it to perform segmentation across a greater diversity of warehouse processes. Initiatives such as multimodal identification, which aims to visually identify items without needing to see a barcode, and the automated damage detection program are accruing product-specific data that could be fed into the universal model, as well as images taken on the fulfillment center floor by the autonomous robots that carry crates of products.
Walgreens Turns to Prescription-Filling Robots to Free Up Pharmacists
Walgreens Boots Alliance Inc. is turning to robots to ease workloads at drugstores as it grapples with a nationwide shortage of pharmacists and pharmacist technicians.
The nation’s second-largest pharmacy chain is setting up a network of automated, centralized drug-filling centers that could fill a city block. Rows of yellow robotic arms bend and rotate as they sort and bottle multicolored pills, sending them down conveyor belts. The company says the setup cuts pharmacist workloads by at least 25% and will save Walgreens more than $1 billion a year.
The ultimate goal: give pharmacists more time to provide medical services such as vaccinations, patient outreach and prescribing of some medications. Those services are a relatively new and growing revenue stream for drugstores, which are increasingly able to bill insurers for some clinical services.
Amazon Shows Off Impressive New Warehouse Robots
Proteus is our first fully autonomous mobile robot. Historically, it’s been difficult to safely incorporate robotics in the same physical space as people. We believe Proteus will change that while remaining smart, safe, and collaborative.
Proteus autonomously moves through our facilities using advanced safety, perception, and navigation technology developed by Amazon. The robot was built to be automatically directed to perform its work and move around employees—meaning it has no need to be confined to restricted areas. It can operate in a manner that augments simple, safe interaction between technology and people—opening up a broader range of possible uses to help our employees—such as the lifting and movement of GoCarts, the nonautomated, wheeled transports used to move packages through our facilities.
Fabric Micro-Fulfillment Center in Dallas, Texas
Amazon Robotics Builds Digital Twins of Warehouses with NVIDIA Omniverse and Isaac Sim
Automation: Why software is the star
As fulfillment centers and warehouses become more highly automated facilities with multiple types of automation, software’s role looms larger. Issues like coordinating multiple systems around cut-off times and service levels, as well as knowing when and how to scale automated systems to accommodate peaks in demand, are two leading reasons why.
One way a warehouse execution system (WES) coordinates the allocation of work across automated systems is with smart order release, which instead of the big “waves” of work, releases work to systems in smaller chunks with the current status and capacity of multiple zones of automation in mind. This order release function can be thought of as the starting point for orchestration, with WES’s ties to lower-level control systems alerting of any unexpected events, or bottlenecks, that might be developing, with some software offering “load balancing” features to help adjust to the present reality on the floor.
With robotics solutions, software plays at multiple levels. Autonomous mobile robot (AMR) vendors, for example, don’t just make robots, they also offer fleet manager software, performance monitoring and analytics. Some vendors are also expanding into broader orchestration with functions like pack-out lines. Of course, artificial intelligence (AI) is in many robotics solutions, so the system can continuously learn over time when it comes to issues like path optimization, or how to best grasp and manipulate items.
Ocado showcases 3D printing innovation
Ocado has unveiled a new approach to building the robots in its fulfilment centres, which it hopes will dramatically improve efficiency and reduce operating costs. The company has developed a 600 Series bot, which it said can be built cheaper and is lighter than the current 500 Series bot. According to Steiner, the 600 Series grocery fulfilment bot “changes everything”. Ocado designed the 600 Series using topology optimisation, similar to the technique used in the aerospace sector to make aircraft parts strong but light. It then used additive manufacturing, in partnership with HP, to make 3D prints of the parts required to build the 600 Series.
A remote village, a world-changing invention and the epic legal fight that followed
The twisted tale of the battle between Norway’s AutoStore and the UK’s Ocado for robotic grocery picking supremacy.
How warehouse automation robotics transformed the supply chain
This technology reduces the cost per vehicle and helped teams redesign the factory to be more efficient. “Navigating vehicles around a manufacturing facility is costly, challenging and prone to human error,” said Jerone Floor, vice president of products and solutions at Seoul Robotics. AI-enabled warehouse orchestration engines can also improve coordination between robots and humans. Experts like Vecna Robotics’ Cherewka believe this has become increasingly important when facing new global supply chain challenges and growing consumer demands.
Medicine piece-picking robot for Hitachi Transport System
In Amazon’s Flagship Fulfillment Center, the Machines Run the Show
More than the physical robots, the stars of Amazon’s facilities are the algorithms—sets of computer instructions designed to solve specific problems. Software determines how many items a facility can handle, where each product is supposed to go, how many people are required for the night shift during the holiday rush, and which truck is best positioned to get a stick of deodorant to a customer on time. “We rely on the software to help us make the right decisions,” says Shobe, BFI4’s general manager.
When managers wanted to figure out how many people they needed at each station to keep up with customer orders, they once used Excel and their gut. Then, starting in about 2014, the company flew spreadsheet jockeys from warehouses around the country to Seattle and put them in a conference room with software engineers, who distilled their work and automated it. The resulting AutoFlow program was clunky at first, spitting out recommendations to put half an employee at one station and half an employee at another, recalls David Glick, a former Amazon logistics executive who supervised initial development of the software. Eventually the system learned that humans can’t be split in half.
Towards Artificial Intelligence in Warehouse Automation
GEBHARDT Fördertechnik was founded in 1952 as a mechanical engineering company and has a long-standing experience in developing and manufacturing of system solutions for intralogistics. With this broad range of knowledge GEBHARDT can deliver everything out of one hand: from planning, design, implementation and continuous support up to an optimally integrated solution for warehouse management.
When a shuttle is in motion, vibrations can occur due to used parts at the shuttle or at the high rack. These vibrations are recorded with sensors CMS01 – Gebhardt own development - and then correlated with the driving parameters which come from control units. The different sources are merged with Crosser modules on the Edge and are the basis for calculating the health status of a shuttle. In addition, the data act as input for inhouse developed predictive maintenance models. This approach minimizes the risk of failure and reduces maintenance costs.
GEBHARDT’S architecture is based on the idea of processing data directly at the edge, transferring only relevant data to the back-office system or the respective cloud solution. This saves money and allows fast processing. The data is read and processed directly at the sensors. Processing steps include time series harmonization, data enrichment or data quality improvements. The automatic learning of the system takes place in a specific step of the process chain. It was important for GEBHARDT to use standard components which can be configured easily. The software components for the implementation, execution and maintenance of the processing steps are carried out with the help of the tools from Crosser: Crosser Edge Node™ and Crosser Cloud™.