{"id":25732,"date":"2017-11-15T21:50:11","date_gmt":"2017-11-16T02:50:11","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-rctom\/submission\/augmented-reality-a-game-changer-for-the-logistics-of-tomorrow\/"},"modified":"2017-11-15T21:50:11","modified_gmt":"2017-11-16T02:50:11","slug":"augmented-reality-a-game-changer-for-the-logistics-of-tomorrow","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/augmented-reality-a-game-changer-for-the-logistics-of-tomorrow\/","title":{"rendered":"AUGMENTED REALITY: A GAME-CHANGER FOR THE LOGISTICS OF TOMORROW"},"content":{"rendered":"

Warehousing operations is big business. <\/strong>It is a\u00a0$141B business in the US alone and accounts for 10% of all logistics costs [1].\u00a0<\/strong><\/p>\n

Estimates suggest picking items from shelves represents 65% of those costs, or $92B (Figure 1) [2].\u00a0The process is still heavily manual. Pickers carry a hand-held scanner with them, searching for the right item, scan it and place it in a cart. It is slow and error prone. Errors must be prevented as they typically result in high follow-up costs including re-stocking and administrative costs.<\/p>\n

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Figure 1<\/figcaption><\/figure>\n

Augmented Reality: an Opportunity to Increase Productivity in Warehouse Operations<\/strong><\/p>\n

AR is a not-so-new, yet underutilized technology that allows the superimposition of information in the user\u2019s line of sight [2]. It can help warehouse operations in three major ways: optimized picking, warehouse planning and quicker training of resources [3].<\/p>\n

Optimized picking<\/u><\/p>\n

Augmented Reality and head-mounted displays free up the pickers\u2019 hands, allow the display of the picking list in the picker\u2019s eye-sight, automatically scan barcodes, optimize indoor routing and help locate items on the warehouse shelves. Through a reduction in error-rate and search time, optimized picking is the most obvious advantage of AR in warehouses [2].<\/p>\n

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Image 1<\/figcaption><\/figure>\n

Warehouse planning<\/u><\/p>\n

As warehouses become more complex and house new value-added services, AR can help experiment, in \u201creal-life\u201d, proposed changes to the warehouse layout and processes. It converts 2D plans to a 3D and life-sized environment, which speeds up the process of planning and reduces the occurrence of \u201crun-time errors\u201d [2].\u00a0<\/u><\/p>\n

Quicker training<\/u><\/p>\n

The distribution industry is one of the largest occupational segment of the temporary staffing market [4]. Between 11% and 18% of workers are temporary [4]. They each need to learn the layout of the plant and must go down the learning curve before being fully operational. AR can accelerate the ramp-up period of these workers by walking them through their first shift step-by-step, with much lesser need for training.<\/p>\n

Intel\u2019s results with AR suggests an opportunity of at least ~$25B for the logistics sector<\/strong><\/p>\n

\u201cIn its distribution center in Arizona, Intel successfully deployed the Pick-by-Vision solution xPick, developed by Ubimax.\u201d Ubimax is a market leader for industrial wearable computing solutions.<\/p>\n

According to the latest results, Intel improved its KPI of \u201cpick-time-per-box\u201d by 29%, with minimal ramp-up time. [5]<\/p>\n

Video of the Project<\/a><\/p>\n

\u201cOn the very first use without any training, order pickers were already 15 percent faster using Vision Picking compared to the picking process with hand-held scanners.\u201d [5]<\/p>\n

These early results not only encouraged Intel in its endeavor to stay relevant through implementing AR in its daily activities, but also suggest a tremendous opportunity for cost takeout in the US logistics sector. A reduction of 29% in warehousing operation costs could amount to ~$25B [1]. Error-rate is also down to almost 0%. [5]<\/p>\n

This promises to attract players to implement this technology. DHL, a global supply chain company already started rolling-out AR in its warehouses and noticed a similar 25% increase in productivity [2], further confirming the optimization potential.<\/p>\n

Intel\u2019s management seems to be aware of the threat of non-sustainability of this cost advantage, and is moving quickly to implement AR in its warehouses across the globe [5].<\/p>\n

Warehouse Operations: Only the Tip of the Iceberg<\/strong><\/p>\n

Although a tremendous opportunity for AR in supply chain lies within warehouse operations, managers must consider the transportation cost bucket ($889B). As a starting point, two applications should be explored: transportation optimization and last-mile delivery. [1]<\/p>\n

Transportation optimization<\/u><\/p>\n

AR can achieve more effective pick-ups through reduction in transportation time, detection of potentially damaged items and facilitated completeness checks. AR devices could detect the number of pallets or parcels that have been picked-up, assess their status and confirm that the order is complete. [1] It can also assist truck drivers in heavy traffic through heads-up displays and optimize the cargo loading process through the projection of loading instructions on a head-mounted display.<\/p>\n

Last-mile delivery<\/u><\/p>\n

\u201cEstimates suggest that drivers spend between 40 % and 60% of their time away from the distribution center not driving.\u201d They are instead searching for boxes or where to deliver them. [1] AR could assist drivers in their day-to-day job by decreasing the reliance on memory from the loading process, displaying exactly where in the truck is the next package to be delivered. The so-called \u201clast-meter\u201d delivery could also be improved through enhanced close-quarter navigation and crowd-sourcing of delivery data (i.e., Where exactly is Soldiers Field Park Building 3?).<\/p>\n

What does the future hold: enhanced humans or humanized computers?<\/strong><\/p>\n

As Intel and other firms keep \u201cenhancing\u201d its human employees with technology, and other hardware firms keep \u201chumanizing\u201d their computers through machine learning and AI, one could question what the real future of logistics is.<\/p>\n