As demand for smarter, safer and more efficient manufacturing continues to rise, advanced automation is answering the call, transforming the factory floor of tomorrow and leading to a high level of consistency and reliability in products. Expedited by the COVID-19 pandemic, demand has spurred a cultural shift among manufacturers leading toward accelerated adoption of new technologies.
From smart sensors to smart edge devices and cloud infrastructure, the impact that the Industrial Internet of Things (IIoT) has had on the manufacturing industry cannot be understated. IIoT enables more intelligent, predictive and proactive processes that lead to enhanced overall efficiencies.
Here’s a closer look at the smart manufacturing technologies that are revolutionizing the future of factories for the better.
We have now reached a point where, as a society, we are less afraid of robots or automation “taking away” human jobs because we’ve realized the immense benefits to be gained. It’s generally accepted that robots that work in tandem with humans—collaborative robots (co-bots)—have huge potential for keeping workers safe and happy.
Re-assigning tedious and/or repetitive tasks to a robot can shift the average manufacturing position to one that is more decision-based than task-oriented, as in the past. Humans can take on projects that require judgment calls or creativity, leaving heavy lifting and/or less engaging work to robotics—therefore improving safety and reducing injuries.
Furthermore, while these robots are very complex machines, it often does not require a degree in computer science to learn how to re-program them to do more than one task. It’s common now to see more “general purpose” robots with computer vision that can adapt to different environments and be quickly re-programmed to serve more than one function.
Overall, this is improving morale, reducing stress and increasing job satisfaction among workers—something that is hugely important at a time when labor is extremely tight: job openings in the manufacturing industry are more than twice as high as they were last year, according to the US Labor Department.
Robotics as a Service
Automation is an equalizer; a rapidly growing trend advancing the use of robots in smaller factories is Robotics as a Service (RaaS). In fact, the global RaaS market was valued at $12.6 billion in 2020 and is expected to surpass $41.3 billion by 2028, according to a recent report published by Coherent Market Insights. Similar to Software as a Service (SaaS), manufacturers using RaaS get the benefits of robotic process automation by leasing robotic devices and accessing a cloud-based subscription service rather than purchasing the equipment.
With RaaS, manufacturers can avoid paying off an expensive piece of equipment, dealing with maintenance issues and other headaches of full-on ownership. Manufacturers can simply contact a company that supplies RaaS and have them set up the entire automation at a fraction of the price of purchasing and owning their own robotic devices.
The factory of the future will be home to a huge number of sensors, which then gather an immense amount of data. The expense of communicating that data back to the cloud is both slower and more costly than processing it closer to the source—at the edge.
For example, a continuous temperature-monitoring system at the edge may be able to analyze the data it’s processing and send an alert or notification when there is an out-of-the-ordinary temperature level. This allows for much faster data analysis, and ultimately faster action, because you’re not waiting for the data to be sent to the cloud.
New connectivity options like Long Range Wide Area Networks (LoRaWAN) are enabling edge computing at a much faster rate in the manufacturing industry, making it an effective and efficient connectivity option for data analysis in factories.
One area that has a large amount of potential is in reshoring manufacturing jobs and, thus, making it more local and flexible. In the coming 5-10 years, the increased number of robots and other technologies could make a reality mass customization/lot sizes of one and regionalized manufacturing. Rather than a factory being dedicated to making a million of one item, perhaps a factory could be dedicated to making items that fit exact customer needs.
For example, a customer could upload a photo or 3D model to a local factory via the cloud, which a robot could use to manufacture a shirt from start to finish that fits their exact measurements. The shirt may then arrive back to the customer in just a day or two because it does not have very far to travel—a significant improvement on the current model of mass production where orders are often shipped overseas before reaching the customer.
This would help eliminate some of the wasteful aspects of manufacturing across the entire supply chain—wasted resources, lengthy shipping routes and returns—making the entire process more individualized and less resource-intensive.