Autonomous Devices for Digital Warehousing

Written by Helmi Salleh, ADLSM

by Helmi Salleh, ADLSM

Autonomous Devices for Digital Warehousing

Written by Helmi Salleh, ADLSM

by Helmi Salleh, ADLSM

by Helmi Salleh, ADLSM

Most warehousing activities and processes are still performed manually. However, new technologies such as augmented and virtual reality, drones, robots, autonomous vehicles, IoT, and wearables will without a doubt transform the world of warehousing. With the support of artificial intelligence, big data, and advanced predictive analytics, warehouse planning and analysis is expected to evolve to the next level.

Digital technologies have the potential to create sustainable value for all stakeholders involved in the warehousing process. The following examples show how various technologies can boost warehousing efficiency and output quality.

Internet of Things (IoT)

The internet of things, or IoT, is a system of interrelated computing devices, mechanical and digital machines, objects, animals or people that are provided with unique identifiers (UIDs) and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction.

A thing in the internet of things can be a person with a heart monitor implant, a farm animal with a biochip transponder, an automobile that has built-in sensors to alert the driver when tire pressure is low or any other natural or man-made object that can be assigned an IP address and is able to transfer data over a network.

Increasingly, organizations in a variety of industries are using IoT to operate more efficiently, better understand customers to deliver enhanced customer service, improve decision-making and increase the value of the business.

The IoT offers a number of benefits to organizations, enabling them to:

• Monitor their overall business processes;
• Improve the customer experience;
• Save time and money;
• Enhance employee productivity;
• Integrate and adapt business models;
• Make better business decisions; and
• Generate more revenue.

Autonomous Mobile Picker

Swift is an autonomous, material-picking robot, offering features like no other. With integrated obstacle detection technology, Swift navigates multiple aisles to move safely and accurately. Swift is capable of picking and transporting products at human-level speeds and enables you to scale operations more cost-effectively. Swift can work alone or simultaneously as a fleet to transform your pack and ship operations into a competitive weapon.

Swift easily integrates into warehouse operations without requiring changes to existing infrastructure. Navigating multiple aisles and picking at or above human-level speeds, Swift enables users to cost-effectively streamline operations and handle the increasing pressures of e-commerce. Swift Autonomous Material Picker/suction grip is designed for grabbing lightweight objects that would be typical in many warehouse pick-and-place environments, as shown in the pictures below.

The robot can navigate by itself, detect and avoid obstacles, stop safely, and manoeuvre a warehouse with agility. It can work safely in conjunction with human pickers, can travel at up a jogging speed, turn on a dime, and pivot in place to fit between aisles. It uses the company’s RapidVision technology to see and locate objects in 3D in real time. This is done via depth sensors and computing to gather 3D geometric information. This data is then matched to data collected with the Flash scanner. The easily transportable Flash scans products to create a uniform item database, while also teaching Swift how to recognize the products it retrieves. It collects data on SKUs including weight, cube, high-resolution 2D images, and 3D geometry models, then stores this information in a database, allowing Swift to recognize and pick the correct item.

Goods-to-Person Picking Robots

While many logistics and manufacturing operations still rely on manual and paper-based picking systems, autonomous mobile robots can now eliminate a lot of unnecessary walking. These machines typically carry carts and can be programed to travel flexible routes in the warehouse to move product between workers and stations. Pickers must walk some distance to the picking area, find the good that are wanted and then walk some distance back. It’s about eliminating walking as that typically represents half the time of the picking task. A Butler Robotics system enabled complete visibility on stock in hand and movement and better control of inventory. Complex handling capability was secured enabling bulk breaking and handling multiple order consolidation. Supply chain cost per shipment reduced in order preparation. Faster Picking and Put away results in significant reduction in turnaround time resulting in on-time dispatch and increased productivity.

Autonomous Inventory Robots

Autonomous mobile robots also offer new opportunities for inventory monitoring. When combined with RFID-tagged products and equipment, these machines can now conduct their own inventory sweeps autonomously at schedules determined by the warehouse.

People might typically do inventory counts every three months, but they can now do it every two hours with real-time data to make better storage and layout decisions about their facility. It not only reduces the need for manual inventory counts but also offers real-time mapping to managers can easily visualize product storage. A dedicated RFID tracking solution can continuously verify inventory counts, spot and address problems or discrepancies before they become bigger issues, as well as search for a specific tag if product gets lost or misplaced to prevent unnecessary searches or expedited re-orders.

Conclusion

The implementation of autonomous robots could primarily drive value by reducing direct and indirect operating costs and increasing revenue potential. Autonomous robots can reduce labour costs and increase productivity by continuously working around the clock without fatigue. Employee safety can be improved in highly hazardous environments, and insurance and injury leave costs can be reduced significantly. Autonomous robots can test, pick, pack, sort, build, inspect, or transport materials of various sizes and weights faster and more efficiently than ever.


References

Craig G. (2018). “4 types of Autonomous Mobile Robots, and their Warehouse Use Cases”. Retrieved from https://www.supplychaindive.com/news/4-types-of-autonomous-mobile-robots-and-their-warehouse-use-cases/529548, accessed 11/9/2018.

Ee Soon Sern, DLSM. (2018). “Autonomous Mobile Robotics for Effective Warehousing”.Retrieved from SIPMM: https://sipmm.edu.sg/autonomous-mobile-robotics-effective-warehousing, accessed 11/9/2018.

Grey Orange (2018) “Enabling distribution efficiency for Consumer Product Goods Company”. Retrieved from https://www.greyorange.com/case-study/distribution-center-robotic-automation, accessed 11/9/2018.

I AmRobotics. (2018). “I Am Swift”. Retrieved from https://www.iamrobotics.com/products/swift, accessed 11/9/2018.

Margaret R. (2018). “Internet of Things (IoT)”. Retrieved from https://internetofthingsagenda.techtarget.com/definition/Internet-of-Things-IoT, accessed 11/9/2018.

Naveen J. (2017). “The Power of Robots in a Warehouse”. Retrieved from https://www.allerin.com/blog/the-power-of-robots-in-a-warehouse, accessed 11/9/2018.

Sabine M. (2017). “Drones, Autonomous Vehicles, Robots – The future of warehousing”. Retrieved from https://sabinext.com/drones-autonomous-vehicles-robots-the-future-of-warehousing, accessed 11/9/2018.

Surendran, DLSM. (2018). “Adopting New Technologies for Effective Warehousing”.
Retrieved fromSIPMM: https://sipmm.edu.sg/adopting-new-technologies-effective-warehousing, accessed 11/9/2018.

About the Author: Helmi Salleh has substantive years of experience in the professional field of warehousing and logistics operations. He is a member of the Singapore Institute of Purchasing and Materials Management (SIPMM). Helmi holds the Diploma in Logistics and Supply Management (DPSM) from SIPMM. He completed Advanced Diploma in Logistics and Supply Management (ADLSM) course on October 2018 at SIPMM.

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