The warehouse industry has come a long way from godowns and mismanaged empty spaces to become the backbone of the manufacturing and growing e-commerce industry in India. The warehousing sector is a fast-evolving sector in India, undergoing dynamic changes, with both the nature of the business and technology driving it.
Going by current industry estimates, the warehouse space in India will grow from the current 909.5 million sq. ft. to approximately 1,439 million sq. ft. by the end of 2019. A report by property consultant JLL India released in March 2018 stated that the warehousing sector will attract investments of about Rs 43,000 crore and create 2 lakh job opportunities in the next three years, driven by GST implementation and growth of the e-commerce sector.
With the Indian economy budding, warehousing systems and logistics are becoming key in generating smooth trade activities for the retail and manufacturing sectors. The rudimentary function of a structured warehouse is to store goods in a way that they are available at a moment’s notice, at any stage of the retail process.
However, this is a very basic definition. Warehouses of today face a very different set of challenges including product complexity, shorter delivery cycles, and mass customization. They need to have a software-centric approach that drives optimised operations, helps in cost reduction, seamlessly integrates with the automation system, is adaptable to changing business needs and works towards real time intelligent decisions.
GreyOrange – a multinational firm that designs, manufactures and deploys advanced robotics systems for automation in warehouses, distribution and fulfilment centres – has recently introduced a warehouse execution software platform called GreyMatter.
The platform leverages Artificial intelligence (AI) and Machine Learning (ML) to provide intelligent solutions to operationalize cost and give the warehouse a competitive advantage.
It helps optimize large and complex operations and aids them in adapting to changing business demands, enabling future-ready warehouses. It compliments existing WMS/WCS capabilities by real-time decision-making and helps in end-to-end optimizations.
Over and above this, GreyMatter also provides granular control and visibility across people.
Introducing: The Robot Butler
With deep domain expertise, world class hardware and software engineering and the passion to solve complex business problems, GreyOrange is advancing the way logistics and supply chain processes are being optimized across the world. One such radical design which the company’s software GreyMatter provides is a goods-to-person robot, which enables warehouses to manage high-speed operations by automating order picking and fulfilment.
The Butler PickPal, is a collaborative robot, which works alongside a warehouse operator to pick, consolidate and fulfill orders, and together can achieve 500-600 picks per hour; easily doubling the throughput from the same picking station. It addresses the challenges arising from the global boom in e-commerce as orders need to be fulfilled faster and accurately with more cost-efficiency as competition intensifies. Vertical and horizontal e-commerce industries that operate with a huge number of high-mix SKU inventory, require the shortest order-to-dispatch time and accurate piece-picking.
Akash Gupta, Chief Technology Officer, GreyOrange says, “Working closely with our customers, we see that the order picking process for e-commerce products take up a high percentage of the resources of warehouse staff. As companies face increasing challenges in hiring employees, the adoption of automation is the answer to increase productivity, reduce costs and improve the turnaround time. The Collaborative Robots market is poised for exceptional growth over the next years, growing to 34 percent of the global robotics spending by 2025. The material handling segment is expected to experience the largest growth in collaborative robot instalments as more companies deploy them into their processes. We are excited to participate in this segment to help unlock the next level of efficiency in last-mile delivery for e-commerce operations.”
Designed to revolutionise the auto-fulfilment process, the Butler PickPal remarkably reduces the time taken during order fulfilment, by identifying and picking products from shelves quickly and accurately.
The innovative combination of a scanning system and a 6-axis robotic arm delivers a unique solution that cuts down the time required for processing and picking orders. The Butler PickPal uses sophisticated Machine Vision algorithms to identify the SKUs to be picked from shelves. Using AI-based order processing, it can manage up to 48 orders at the same time.
Apart from this, it can also handle different packaging types such as boxes, pouches, bottles and vacuum-sealed packages and can grasp items up to 4kg. Using Machine Learning it devises the strategy to pick each item from the densely packed SKU inventory using a versatile gripper. It can identify and handle over 100,000 SKUs of the most popular products commonly found in its e-commerce operations.
Different Sizes for Different Operations
The new Butler PickPal will be deployed in selected sites by mid-year. One of these sizes is the Butler XL, capable of managing a variety of payloads from 100 to 1,600 kgs. This goods-to-person Butler system lets warehouses run high-speed operations by automating inventory storage (putaway) and order fulfilment. It has been deployed in distribution centers in Japan, Hong Kong, India, Europe and the Americas for industries such as 3PL, e-commerce and retail. The robotics systems handle a variety of items including apparel, home furnishings and personal care, reducing cost per shipment and enhancing productivity of warehouse operations by more than four times.
Its versatility is ideal for handling bulk inventory in factory warehouses, Omnichannel fulfilment centers and large distribution hubs. A wide range of loads from raw materials to finished goods, including automotive components, manufacturing material and liquids can be moved on and put or picked from pallets, drums, sacks, crates and cases.
Sid Chatterjee, Vice President – Products, GreyOrange says, “We are delighted to add the Butler XL to the growing Butler family. The entire Butler range operates with minimal supervision using our software platform, GreyMatter, developed by GreyOrange to revolutionise warehouse operations by connecting people, process and technology more efficiently using Artificial Intelligence. In real-time, it integrates and delivers all of the functionality, intelligence and services required for optimum warehouse operations.”
Advantages of Using a Robot
One of the key advantages of the expanding Butler family is its ability to manage multi-floor operations with the use of an elevator. This provides greater flexibility in handling material and inventory on multiple floors, and optimises space utilisation vertically in a warehouse.
Many warehouses store large and heavy pallets or slow-moving inventory on one floor, while fast-moving goods are generally placed on a separate level. Since GreyMatter manages Butlers across floors, the auto-fulfilment improves order-to-dispatch time tremendously, with enhanced inventory traceability, increased fulfilment accuracy and minimising order returns.
Another advantage is that it can lead to improved efficiency. Putaway and picking processes often take up the majority of resources of warehouse staff – between 50-70 percent. Using the Butler system can lead to faster stock availability, improving efficiency multifold and shortens delivery times from days to just hours.
Also, it is easy to add the Butler system to existing operations as it requires minimal changes to infrastructure. The Butler range shares a similar footprint and can navigate within the same width of aisles. This versatility makes it easy to configure the Butlers to work in different parts of a warehouse for end-to-end autonomous fulfilment.
Several units of the new Butler XL will be integrated in sites by mid-year. It is expected to set new standards in operational efficiencies in picking velocity and productivity.
