Technology advances democratize automation
There are 3 prerequisites for manufacturers to readily access automation:
The solution must easily learn how to do routine tasks on the shop floor.
The solution has to be affordable.
The solution should be easy to incorporate into the workflow and easy for workers to use.
The industry is seeing progress on all three fronts. Thanks to technological advancements, we can now:
Have robots perform routine tasks without extensive modifications to processes
Robots use deep learning programs to tell them what to do. Historically, these programs trained on tons and tons of real-life data.
A sorting and picking system, for example, needs to learn thousands upon thousands of ways in which an object can be oriented on the conveyor belt so the robot can figure out how to manipulate the object. If a particular real-life scenario wasn’t already programmed in the robot’s deep learning model, it was stumped, and the assembly line stopped working. That’s no longer the case.
Synthetic data and digital twins – artificial equivalents of real-life datasets and processes, respectively – are coming to the rescue. They are filling in the picture by generating data that the computer vision model can now use.
CAD software generates thousands of permutations of what objects look like on the assembly line; the computer vision algorithm learns these data points and creates the model.
No longer do manufacturers need to have an enormous collection of real-life datasets. Today’s custom models work by complementing the data that manufacturers already have with synthetic data.
Use computing resources judiciously where and when needed
For near-instantaneous decisions, data needs to be gathered and processed in real-time on the shop floor. Advances in edge computing enable data to be gathered, processed and acted upon in real-time.
While this is possible, most manufacturing operations that can be automated don’t need split-second data processing at the edge. In such instances, Machine Learning (ML) models can be trained in the cloud and outfitted into robots on the shop floor. The robots can do their tasks even without an internet connection.
The ability to choose where heavy-duty processing needs to take place – on-premises or in the cloud – helps manufacturers use only as much computing resources as are needed. Hybrid cloud computing accommodates the varied computational needs of manufacturers instead of a more expensive one-size-fits-all approach.
Work with off-the-shelf hardware
Most automation applications need expensive specialty hardware equipment, but powerful software helps manufacturers overcome this stumbling block. Very often, companies can use commodity equipment as a foundation for automation and layer software intelligence on top of the data feeds to drive automated processes.
Not having to commission specialty equipment that might need to be upgraded periodically lowers the total deployment cost and makes it easier to access automation.
Deliver user-friendly automation that improves worker productivity
Manufacturers want automation to work for them, not the other way around. Automation must be easy to use with simple one-click operations where possible.
For managers, a robotic system that is flexible and can do multiple jobs instead of being dedicated to just one task is also a bonus. This ability can maintain high productivity by decreasing the amount of time spent on task-switching.
Today’s automation takes these human-centric factors into account and delivers cobots, collaborative robots that work alongside humans to get the job done. Robotics-as-a-service providers can deliver simple plug-and-play solutions that operators can use without losing time and productivity by having to reboot their entire workflow.
What this means for manufacturing
These technological advancements are good news for manufacturers looking to automation to ease labor pressures.
Manufacturers can now:
Decrease the net cost of automation deployment
Combining off-the-shelf hardware with custom software and a new approach to how equipment is purchased and installed vastly decreases the initial cost of deployment. Manufacturers using robotics as a service (RaaS) providers can completely eliminate capital expenditures. The operating expenditures they incur add value by saving skilled labor for more challenging work and improving worker productivity.
Get more from one robot
The Rapid Machine Operator (RMO) from Rapid Robotics takes advantage of all of these technologies and more to create a turnkey robotic solution that deploys in days, for a fraction of the cost of a capital purchase that might take months to deploy. Layering software solutions and cloud computing into an off-the-shelf robots also enables 24/7 support, and transforms the "as a service" component of the offering into an always on engineering consultancy for manufacturing customers.
Such flexibility is a boon for specialty manufacturers who might not have the engineering staff they would otherwise need to support a large scale automation deployment. Leaning into automation helps them save time and money.
Prepare for changes down the line
Modular robotic systems mean manufacturers can plug-and-play today while being prepared for what’s coming around the corner. Any new tech stacks won’t need a complete overhaul; manufacturers can simply build on an already strong foundation.
Conclusion
Automation is revolutionizing manufacturing, and manufacturers can reap the benefits of accelerating positive changes.
RaaS companies like Rapid Robotics provide fast, affordable solutions to manufacturers who need automation that can adapt to their changing needs. We evaluate manufacturers’ processes and suggest robotics where it can work best. We’re invested in ensuring that your RMO remains updated and operating at peak efficiency for as long as it’s needed.
Learn more about how Rapid Robotics uses software to reduce costs, speed up deployment, and ensure that customers have the most effective and affordable robotic automation solutions. Schedule your free 30-minute automation consultation now.
