Rise of the Machines

Working with Robots for Efficiency and Productivity
Written by Ryan Cartner

The history of human innovation is punctuated with key moments that have forever altered the course of industry. From the beginning of the industrial revolution, to the invention of the computer, the internet, and robotic automation, it is technology that has driven industry forward. In 2017, the union of automation, data collection, and analytics is changing everything.
It’s a major remodelling of the way automation is done and it’s revolutionizing industry in every sector. Those bold enough to take on the challenge of adopting these new technologies will rapidly outpace their competition by cinching up loose ends, eliminating waste in every sense, and operating with the consistency, precision and efficiency of a well-oiled, smart machine.

For decades, industrial robots have consistently become faster and more capable of making finer movements with more precision with each generation. In industries like manufacturing, mining, agriculture, and logistics, automation systems were adopted to increase productivity, and so speed and efficiency were paramount. Medical and scientific laboratories needed robots that could make very fine movements with a very high level of proficiency. Demand fuels innovation and so robotics engineers built robots that were fast and precise. Today, engineers are building robots that are smart.

Let’s look at examples of smart robots in action. First, we’ll look to the logistics industry, specifically warehouse management, for a case study that is the essential media darling of modern industrial robotics. In 2012, Amazon acquired a robotics company called Kiva for 75 million dollars. Now, Amazon warehouses are managed by 300lb robots. Rather than workers walking the aisles of a giant warehouse, some spanning as many as 800,000 square feet, and tracking down items to fulfill orders, this job has been reassigned to robots that can drive between and under tall racks of product. The robot can position itself beneath a rack, lift the rack off the ground, and transport it to a queue where a worker can retrieve it.

In the past, the general role of robots in industry was the completion of simple repetitive tasks. The role of Amazon’s robot army is the completion of a task that is far from simple, and far from repetitive. In order to navigate the aisles of these massive warehouses, they need the ability to sense their surroundings to avoid collisions with racks and with other robots. They need to be able to move efficiently in an environment full of moving obstacles. They need the ability to find a path between their present location and the location of a particular rack. The capacity for these robots to collect data about their environment, analyze that data, and make decisions based on their analysis is what makes the future of industrial automation so bright. The result is a 20 percent savings in operating costs, and a stunning 50 percent growth in inventory space by building narrower aisles that wouldn’t suit workers but that suit robots just fine.

After Amazon bought Kiva and made their robots proprietary, a number of competitors formed. Now, the new generation of warehouse management robots don’t need to see each other in order to avoid collisions. They can instead communicate with each other and organize into efficient formations by knowing the positions of their peers. As these machines move around a warehouse and record patterns that are too complex even for humans to notice, they will learn better formations and more efficient paths to take than humans could even teach them. Today’s robots don’t simply replace humans and increase production; they have the capacity to do things that humans could never do, and in some cases, things that humans never even thought to do.

Beyond warehouse management, Amazon also plans to use automation for shipping. Amazon Prime Air is the company’s autonomous drone delivery service. Still in development, they started a small pilot program in the UK delivering small items from warehouses to recipients with quad-copter drones. Eventually, self-driving delivery trucks will be a reality. It is only a matter of time before autonomous delivery is here.

In the manufacturing industry, the entire production process is adapting to incorporate smart robotic modules that integrate into a more efficient, more productive system. Product lines are equipped with various sensors to capture information about products as they make their way through each stage of the manufacturing process. Each module works autonomously, adjusting its behaviour based on the information received. A single failure in a traditional manufacturing production line can cascade; if one piece is out of place, the next robot in line will fail to pick it up. If an object has the wrong orientation, the painting station will waste paint. In an intelligent system with smart autonomous robots, information about each stage in the process can be communicated to other modules, meaning that the painting module will know the orientation of the piece, and could potentially adjust its own orientation to compensate, or skip the piece altogether to reduce waste. Audi, the German automobile manufacturer, operates out of smart factories. Every stage is modular and interconnected, and giant robotic skids, functionally similar to Amazon’s Kiva bots, move large parts between modules.

There are even robots designed for manufacturing applications that are trained rather than programmed. Baxter is a collaborative robot designed by Rethink Robotics to work alongside humans. Rather than programming this robot to perform a specific task, it learns through training. In the past, robots were programmed by highly trained, highly paid specialists. Baxter is trained to perform tasks by literally holding his hand through the operation the first time. Robots are capable of performing highly complex tasks with pinpoint precision the exact same way over and over again, minimizing human error and increasing efficiency and productivity across all aspects of a business, but typically do so from inside cages, separate from the rest of the workforce. Baxter and other collaborative robots like him are bringing these advantages out of their cages to work alongside, and with, their human counterparts.

Sensory feedback is a vital component of modern industrial robotics. Being able to gather and share information about a process gives a system the ability to change course dynamically based on changing conditions. In the medical robotics industry, robotics engineering firm Kuka has been working toward developing automation for the operating room of the future. Robotic components they have engineered for healthcare cover specialized rehabilitation applications, minimally invasive surgery, tumour treatment at the molecular level, and advanced diagnostics. Their systems incorporate everything from robotic surgical tools to the packaging and distribution of medicine. All of these modules can be integrated into a singular system – a smart hospital.

In the mining industry, giant autonomous trucks are hauling loads of mined material weighing hundreds of tons without a driver in the cab. They work out where to go using GPS, and avoid obstacles using laser and radar sensors. On-board intelligence enables them to make decisions based on sensory information about how to navigate around the work area and to manoeuvre safely around other vehicles and personnel. Hauling material is the largest cost to a mining operation, and autonomous trucks are roughly 15 percent less expensive than trucks with drivers. While workers take breaks and change shifts and are generally unpredictable in the way they drive and park for loading, autonomous trucks suffer none of these drawbacks. They can work around the clock. In fact, mining company Rio Tinto has 73 of these behemoth robots hauling iron ore 24 hours a day in four of their Australian mines.

Beyond hauling, mining operations use robotic automation for everything from drilling and blasting to mapping unknown territory. Using radar, laser and visual imaging sensors on robotic drones, highly accurate 3D maps of a mine interior can be modeled and examined without any danger to miners.

In the middle of the 19th century, the invention of the steam engine kicked off the industrial revolution by allowing humans to build factories without access to water for generating power. In the beginning of the 20th century, Henry Ford brought us the mass production model. And in the 1970s came the first industrial automation platforms for manufacturing. These revolutionary innovations changed the course of history by generating immense, global economic growth by providing a means to increase productivity in industry. Intelligent automation systems might be the fourth great industrial revolution. Currently, roughly 10 percent of manufacturing tasks are done by robots, and within 10 years that number is expected to climb to 25 percent. This means that by 2025, workers and robots will collaborate to become 15 percent more productive.

Moving forward, industrial operations will become more interconnected, more aware, and more intelligent. Autonomous robots will be system omniscient, collecting sensor data from every single aspect of a business’s operation, and using that data to manage processes. A combination of sensors, data analytics, and interconnectivity is the key to highly intelligent, highly productive business operation and to a new revolution in industry.



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