This post comes to us from Adam Robinson of Cerasis, a top freight logistics company and truckload freight broker.
Imagine a world where automation comes together with technology to deliver products without human intervention. An order is placed by a consumer. 3-D printers pick up the details and print the finished product. It’s then picked by robots from the shelves, packaged and placed into a self-driving truck. The trucks leave the facility, and drones are automatically dispatched from the truck to deliver products while moving. The truck never stops until arriving for reloading.
This example generates a huge amount of data that can leverage in the supply chain. But, the same data can have a drastic impact on transportation planners and agencies around the globe. While this example may still be a few years off, it is important that you understand how the top emerging trends in automation will shape supply chains and transportation processes in the coming years.
The Standard Definition & Components of Automation
Today: There is a standard definition of automation in the supply chain. Anything that can be handled via today’s computer systems can be automated. This includes billing, generation of bills of lading, compliance reports, and even movements throughout a factory or warehouse floor.
Historically, automation has been applied to virtual processes, like order auditing or customer service reports. However, the trends in automation are changing to reflect actions that function more like artificial intelligence, not just a search and locate program on the computer.
What is it?
Additive manufacturing includes all actions in the supply chain that can enhance existing factory production, if not replace it entirely. Additive manufacturing may be handled manually, but automating this process is as simple as turning on the power and connecting to the Internet of Things (IoT).
For example, additive manufacturing might involve the use of 3-D printers to create replacement parts at the store for consumers.
Today’s status: Unfortunately, the capacity of 3-D printers remains in infancy, capable of only producing simplified parts out of liquid polymers.
Virtual Reality Comes to the Forefront.
Meanwhile, Google Glass and other virtual reality tech are changing how customers complete their orders. In addition, the same technology can be overlaid with augmented reality to give repair technicians and individuals greater resource access when making repairs, checking order contents and fulfilling orders.
For example, augmented reality glasses will soon detect package dimensions and classify the package according to dimensional pricing models.
Today’s Status: Today, this technology is limited to automated identification and data capture (AIDC) applications. Advancements in virtual reality over the past year indicate its future might be much closer than “meets the eye.”
Additive manufacturing will gradually move products from warehouses and distribution centers to be closer to end-users. As a result, the amount of last-mile traffic may increase.
Robotics Enhance Inbound and Outbound Logistics for Shippers.
Another trend in automation involves robotics. By definition, robotics are the icons of automation. They perform functions at the request of a system or person, but more of today’s robotic systems are performing duties upon request from an order fulfillment system.
The order process automatically notifies robots in warehouses and triggers the flow of processes as seen in the opening example.
Robotics Improve Inbound and Outbound Logistics.
Robotics are not isolated to warehouse pulling for outbound logistics. They can be used to manage inbound and outbound processes and strategy. Through trends in automation and robotics, supply chain companies will have the tools and resources necessary to ramp up throughput and decrease product cycle from order to delivery. Therefore, more trucks and drivers will be needed, but the looming driver shortage and capacity crunch will trigger another automation trend.
Autonomous Vehicles/ Trucks
Automation begets automation. With advances in technology and the IoT, most major companies, including Uber, Facebook, Google, and Amazon, have launched autonomous vehicle and truck pilot programs.
These driverless vehicle programs will give supply chains access to a new inexhaustible resource for moving products, overcoming the challenges inherent in the driver shortage and capacity crunch.
The driver shortage and capacity crunch are likely to come to a head in 2017, as consumers demand more product, at lower costs and faster than ever before.
Some setbacks have occurred, like the first self-driving car wreck earlier this year. With each setback and challenge, companies have pushed back to overcome the obstacles.
In response to increased interest in driverless vehicles and trucks, the National Transportation Safety Board (NTSB) has issued recommendations and created an advisory panel to review ongoing driverless vehicle advancements and maintain public safety.
Transporters and supply chains will respond to this direction by leveraging the trends in automation and power of data to ensure compliance with increased government oversight, through the agencies you represent.
Companies have already tested cross-country driverless trucks, albeit with a person ready in the cab to take over in the event of a system failure. However, the wide-scale deployment of this level of driverless trucks is far from implementation.
In the interim, more automated vehicle systems will work in tandem with drivers to enhance safety and maintain vehicle control. Similar systems are already deployed in crash and pedestrian detection systems, automated braking and tracking control in today’s vehicles. It is not difficult to apply today’s technology and automated features to the fleets and drivers of 2017.
Trends in Automation: Whats the Potential?
The potential applications of this type of technology can include real-time traffic condition monitoring and warnings, redirecting traffic before pile-ups and accidents occur, similar to Google Maps’ capacity to show traffic congestion in real-time.
Data through such systems can automatically feed back into transportation planners’ systems to automatically change signal phase and timing and enable immediate rerouting or adjustment of traffic flow on a broader scale.
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