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While some question the necessity of investing in autonomous vehicles, the potential for this nascent technology to create value and solve some long-standing logistical problems is undeniable. We will need to plan and prepare for the resulting disruption in business processes, operating costs, and economic models. We have long awaited the introduction of robotics into the supply chain. So long, in fact, that some people began to believe that autonomous vehicles and robots would never be anything more than a science fiction-style experiment. But that was because, until recently, robots were stationary, simple-functioning, expensive, blind, and relatively unintelligent. Today, thanks to the convergence of machine learning and artificial intelligence, big data, mobility, and advanced sensors, the autonomous revolution is on the horizon. The robots of the future will be smarter, lighter, and easier to program.
They will also be more flexible and affordable. Indeed, it's no longer a matter of 'if' robots will be operating delivery vehicles, distribution centers, and factories but 'when.' The scenario shown in Figure 1, where robots and autonomous vehicles play a role in virtually every step in the supply chain, from field to final consumer, is no longer far-fetched. Each discrete component of this scenario is already being created and tested; it will not be long before they are connected, and a fully autonomous, end-to-end supply chain becomes a reality.
Instead of seeing this technology as a threat, business leaders need to view it as an opportunity. Autonomous vehicles have great potential for alleviating some of the growing pressures on supply chains to respond faster and more nimbly to customer demand. Because autonomy allows machines to make decisions and act without human intervention, it will help enhance supply chain speed and productivity. Figure 4 Selection hierarchy for autonomous vehicles Without a doubt, this revolution will have profound implications for supply chains and for the practice of supply chain management. It's important that business leaders start taking steps now to understand autonomous technology and plan for the day when it provides a viable option for their business. As part of that planning process, companies need to consider two macro questions: 1.
How could autonomous technology radically change our company's operating model and value proposition? Could it lead to breakthrough supply chain performance improvements? Can our company anticipate and participate in the new 'ecosystems' that will develop around autonomous vehicles? These complementary functions and services will include such things as vehicle manufacturing, financing, and insurance; traffic management technology; workforce training;and parking, fuel, and maintenance, to name just a few. These two questions are not just complementary; they are inextricably intertwined, and one cannot be answered without considering the other.
( shows the complete autonomous vehicle landscape and ecosystem.) This article, however, will primarily consider the first opportunity—new value propositions and operating models in a supply chain context. It will also briefly introduce the business ecosystems that will emerge as companies think through, experiment with, and adopt autonomy. This latter opportunity will be discussed in greater detail in a future article.
Promise and possibility The term 'autonomous vehicle' refers to any machine that is able to move, either on its own as directed by preprogrammed software or under remote control by a human operator, to complete one or more tasks. Figure 2 identifies the remarkable—and continually growing—number and variety of autonomous machines that support logistics and supply chain activities.
Some of these vehicles are already in widespread use, while others are still in the pilot or development stage. Autonomous vehicles may be huge in size (aircraft, container ships, and highway trucks), relatively small (delivery drones and robotic picking arms), or something in between (forklifts, automated guided vehicles and order-assembly robots).
As Figure 2 shows, autonomous machines in the supply chain operate in four general environments:. In the air, usually by drone. On the ground, usually by vehicle. The 'last 100 feet,' where cargo or merchandise is transferred to the user. 'GPS-denied,' within the four walls of a warehouse, retail backroom, or even a kitchen, where tracking and guidance via global positioning systems and other technologies is not involved These autonomous systems have the potential to revamp the supply chain and create breakthrough performance improvements.
They will do so in at least three general ways:. By helping controlled environments, such as warehouses, more efficiently manage and process products through autonomous inventory management, including positioning, routing, sorting, storing, tracking, and packaging.
By increasing transportation efficiency through autonomously moving goods from factories, retail centers, and distribution centers to homes, offices, or other locations of choice. By increasing information gathering, sharing, and integration to ensure an optimally performing system. From an internal operations perspective, every pathway and node of the supply chain can be rethought with an eye toward utilizing autonomous vehicles to achieve radically better efficiencies and cost reductions.
Point-to-point long hauls, local routing, yard management, and cycle counting in the distribution center (DC) and store backrooms are all opportunities that offer significant returns on investment (ROIs) in autonomous assets. For example, recently UPS stated that if drones cut just one mile per day from each of its drivers' delivery routes, it would result in US$50 million per year in fuel savings. From an external, customer-facing perspective, autonomous vehicles could help retailers and delivery companies meet customers' delivery requirements based upon their preferences and economics. For example, 'smart' carts, such as Canvas's robotic carts, could help labor-strapped retailers better serve customers who want to pick up their orders in store. A customer could walk in at any time and scan the order information at a kiosk; a cart would immediately bring the order to the customer, eliminating the need for appointments or waiting for an employee to become available to look up the order and retrieve it from a backroom. Other 'goods-to-person' technologies include mobile delivery bots with a storage container that consumers must open to retrieve their orders—Starship's delivery bots, which can navigate city streets right to a consumer's designated pick-up location, are in pilot testing now.
And, of course, there are UPS' ultra-fast, deliver-anywhere drone package deliveries, which also are in a proof-of-concept pilot now and could soon be in widespread use. The scope of potential applications for autonomous vehicles in the supply chain is vast. Here are just a few general scenarios where autonomous vehicles offer the greatest promise: 1. Data gathering and analysis—During natural disasters, it can be difficult to obtain up-to-date data on conditions without putting human lives at risk.
Drones could continually gather that information and relay it in real time to human decision makers. Capacity challenges—The U.S. Transportation market is facing significant capacity challenges due in part to the driver shortage. Self-driving trucks with no restrictions on daily operating hours could alleviate the driver shortage and relieve some of the capacity crunch. High labor costs—Last-mile delivery is often one of the most expensive segments of an e-commerce transaction because it requires lots of labor. By reducing the need for operators, self-driving delivery vans could bring down the cost of last-mile delivery.
Speed and efficiency—Autonomous scheduling and dispatching of on-demand deliveries and transportation would reduce lag times and enable faster, more accurate responses than those that could be generated manually. Mobility and safety—Autonomous vehicles could make it feasible for disabled employees to get to work, thereby expanding the labor pool for warehouses and other supply chain jobs. Drones could also carry out dangerous work such as inventory counting in the high racks that are increasingly common in today's warehouses. As these scenarios suggest, the introduction of autonomous technology will require companies to completely rethink their operating models and value propositions. For example, if autonomous vehicles are introduced to the freight transportation industry, it would mean that human assets would no longer be the limiting factor. The lifting of this constraint means that new, creative operating models would become possible. Without human drivers and hours-of-service limitations, assets would become usable 24 hours a day.
As a result, a consortium of shippers might, for instance, collectively bid on a transportation asset, and each would fractionally own the asset or pay a specified share of the cost of the move. If that model arose, companies would also have to remodel their operations to consider how they could structure service-level agreements to keep that container or trailer filled at all times while using and paying for a fraction of it. They would also need to consider whether there is some monetary advantage to be gained from the large amounts of data created by an autonomous vehicle. Part of an ecosystem In order for companies to successfully and safely implement autonomous technology into their supply chain, they must also address a number of applications, issues, and requirements. These adjacent concerns include such considerations as how the technology will change the customer interface, how will employees interact with the technology, regulatory compliance, operating rules, data integration, and much more. One crucial concern that must be addressed is how human beings will interact with the system.
Various researchers and organizations have different perspectives on how autonomous systems will or should be designed. Some, like Google's autonomous car division, have adopted an approach that keeps humans completely out of the loop.
Others argue for keeping humans in the system and letting autonomous systems and humans jointly make decisions. The reason for keeping humans involved is so that they can manage novel or unexpected situations.
But if companies do decide to involve human beings in the system, they need to carefully and purposefully lay out what their roles should be. Some research has shown that humans are not effective monitors of autonomous systems because they get bored or complacent if they aren't part of the system's operation. For safety, it will be necessary to ensure that any humans involved stay engaged. Additionally, there will be a need to consciously balance employees' concerns about automation with the requirements of the business.Recently the Teamsters trucking union demanded that UPS agree not to use drones or self-driving vehicles to automate deliveries. The union worries that drones could reduce the need for drivers and thus eliminate jobs.
However, UPS and other delivery companies are struggling with growing delivery volumes driven by the rise of digital commerce, a situation exacerbated by a worsening shortage of truck drivers. The challenge for these companies will be to use technology to mitigate the labor shortage without alienating employees and potentially triggering a strike or other labor action. Another human-related consideration will be how a fully autonomous system affects the customer service experience. Generally, delivery of the product to the customer is the crucial point in the supply chain where the company receives the most feedback on the end user's experience. Utilizing automation, though, removes points of 'human interaction.'
People may not convey their feedback and feelings to a robot accurately, or the robot may not be able to interpret the user's true feelings. Until robots can understand body language, facial expressions, and the difference between sincere speech and sarcasm, businesses will have to ensure they have a system in place to stay connected with their customers. It's also critical to consider how autonomous vehicles integrate with and influence other functions, policies, and technologies. So far, most enterprises look at autonomous technologies in isolation.
Yet even if the activity performed by the autonomous vehicle is geographically limited, it will impact other operational and administrative areas. (For an example, see the sidebar on 'The complications of implementing warehouse drones.' ) Another related consideration is what technical and operating standards will autonomous vehicles need. Autonomous vehicles depend on a composite of technologies including: computer processing, sensors, battery technology, the Internet of Things, machine learning, wireless communication, and software applications and algorithms—just to name a few. How do we get them all to 'play well together'? How we answer that question will deeply influence our approach to autonomy in the future. Should there be an open platform that companies can plug into and create their own apps for specific purposes?
This would be analogous to the way many apps have been developed based on Apple's iOS operating system. In my view, a common operating system for autonomous vehicles that would facilitate 'plug and play' applications will be critical. Such an overlaying architecture would prevent vehicles—whether drones, trucks, delivery bots, or anything else—from operating in conflict with each other. Common standards would provide the ability to gather information from any kind of sensor, make sense of that data, and respond in a way that is predictable and conforms to established norms.
For safety's sake it will also be important to build in algorithms that govern how a vehicle will react or behave in specific situations or environments. At the same time, companies will also need to keep on top of the new complementary market opportunities that are formingaround autonomous vehicle technologies. The complications of implementing warehouse drones Warehouse drones provide a real-life example of how even a seemingly simple autonomous vehicle implementation can affect a wide range of systems, technologies, and employees.
Basically, warehouse drones are aircraft with some kind of computer-vision technology; they take pictures of bar codes associated with storage slots and collect information about the items in those slots. They may also have computing capabilities on board.
Because the drones perform a single function—inventory counting—within the four walls of a DC, people may assume that getting timely, accurate data is all that's at stake. But there are many other factors involved. One is worker safety when drones are operating nearby; in the United States, this requires compliance with Occupational Safety and Health Administration (OSHA) regulations. Another is that many warehouses and DCs lack built-in technology infrastructure; the company may have to install sensors, transmitters, and other equipment to work with the drone. Depending on the facility's design, it may be difficult to manage location tracking of the drones. That's because it is a 'GPS-denied' environment, and end users must employ other methods of tracking and guidance. At the very least they will have to use specialized indoor location services softwareto map the facility in three dimensions to give drones an accurate assessment of their position.
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In addition, any time the flight paths change the drones will have to be 'retrained.' In addition, drones run on batteries; the more tasks they perform, the faster the batteries run down. Operators must therefore decide whether the drones will simply take and store photos, locally process data, and/or transmit information to a cloud-based system—keeping in mind that each added function cuts battery life, and that the more functions drones perform, the more replacement batteries and time and labor will be spent changing them. Then there are other requirements, such as maintenance and repair and the development of a drone fleet 'command center.' Even training personnel is an issue.
Navigating these vehicles in a 1.2-million-square-foot DC is not like a video game! One of the critical factors in scaling this technology for warehouse applications, therefore, will be a strong local understanding and support for robotics, including having people with the skills and knowledge to mesh all of these technologies together. Parasuraman and D.H. Manzey, 'Complacency and Bias in Human Use of Automation: An Attentional Integration,' Human Factors: The Journal of the Human Factors and Ergonomics Society, October 20, 2010. Tech Pro Research, 'Autonomous transportation research: Predicting impact on industries, companies, and personal lives,' February 2018.
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