IoT or Die: How Manufacturers Rethink Their Operations

IoT or Die: How Manufacturers Rethink Their Operations: Manufacturing is one of the most progressive niches when it comes to optimizing processes, cutting costs and introducing new technologies. Decades ago, the most significant cost-saving opportunity was labor. That’s why so many manufacturers moved their factories to China and took advantage of cheap labor costs and the inviting policies of the Chinese government.

However, that’s no longer the reality. China’s average wage is slowly rising, and there’s a limit to how little you can pay and how few people you can hire. That’s why this is just one of the pieces of the puzzle called manufacturing optimization. Companies have been steadily increasing their investment in technological know-how, with the ultimate goal of getting rid of human labor, when this becomes economically viable.

With the expansion of digital technologies, Internet infrastructure and affordable processing power, IoT has taken the rightful place as the next ‘big thing’ in optimized manufacturing.

The IoT development company Itransition takes a closer look at some of the IoT technologies that shape the world of manufacturing today and change the way we think about connected environments and synergies between people and technology.

Eyeballing the Future with Machine Vision

Sensors that monitor various stages of the process are an essential part of any modern manufacturing facility. We’re not surprised by temperature and air sensors. However, there’s a rapidly expanding niche of sensors that take advantage of both software and hardware advances of the recent decades.

It’s called machine vision (MV), a subset of software and hardware disciplines that enables machines to extract information from images. These technologies are often used in quality assurance to track inconsistencies within the manufacturing process. Just like many other IoT facets, modern computer vision couldn’t be possible without machine learning. It dramatically improves the accuracy and usability of image processing systems and can be integrated within any manufacturing process as a software add-on to an already existing system.

Modern requirements of IoT-enabled manufacturing also drive MV implementations in robotics to help automated bots navigate manufacturing facilities and take part in the manufacturing process. This enables an even more in-depth integration of automated systems into the manufacturing process.

Robotics

We all know about the robots involved in manufacturing, as this is a pretty standard concept nowadays. Robots have taken over repetitive and hard work that requires consistency and accuracy. But while there are many niches within the manufacturing process occupied by robots, there’s still room for improvements.

IoT and the connected nature of modern manufacturing environments allow software to push the productivity limits even further. Predictive maintenance (PM) is one of these new frontiers that combine the robust sensor ecosystem of a factory with machine learning capabilities of the particular software that monitors the production process.

PM is the process of analyzing the gigabytes of data generated by robots and other integrated systems to predict when one of the particular elements within the manufacturing process is going to fail. This way, the operational staff can perform maintenance work on robots, sensors or other parts of ‘the conveyor’ that are likely to fail in the nearest future.

In turn, this drives better performance and lowers costs for manufacturers that won’t have to unexpectedly shut down any of the processes directly involved in manufacturing, as with a prediction you can schedule maintenance and allocate resources accordingly.

Cobots is another fascinating development. These are robots that can work together with people in the same environment. A modern connected manufacturing plant doesn’t restrict the workflow to areas where people and robots operate. On the contrary. When people can work with robots together, both robots and people are more productive, as the manufacturing process is simultaneous. In fact, productivity has been increasing along with the adoption of robotics within manufacturing.

All of this is enabled by various sensors, including those that can detect pressure when a person interacts with the robot and those that allow a robot’s awareness, such as the machine vision solutions that we mentioned.

Smart Factory Floors & Warehouses

We discussed this trend in our overview of the technological advances that drive eCommerce. Manufacturing overshadows eCommerce when it comes to creating connected production environments and ‘smart warehouses’ since they need a much higher level of integration – they don’t just move an item around, like in a standard eCommerce supply chain.

They need to be able to connect the means of production and the supply chain in a much more robust and diverse manner. No wonder it is projected that over $200 billion will be spent on IoT solutions for supply chain management in 2017 alone.

One of the more specific developments that are more relevant to manufacturing IoT is the growth of machine-to-machine technologies (M2M). They are responsible for communications between the machines and serve as a bridge connecting various parts of the supply chain.

For example, a wirelessly connected production line robot that informs the delivery bot that it’s done with the part so that the bot could come and pick it up. All of this has a massive impact on the supply chain, as the level of orchestration between machines is much better when there aren’t any humans involved – machines are more precise and process information faster than humans.

You no longer need to search for mobile app development services to create an app that lets your logistics personnel control this process. Even the relatively recent put-to-light and pick-to-light technologies become irrelevant in this scenario. Everything is done automatically.

Of course, manufacturing is still impossible without humans. We still need people to maintain the machines and interact with them where a sufficient level of M2M integration hasn’t yet been reached.

But as machines get more complicated and expensive, it’s important to have a process that allows people to be adequately integrated into their environment. This is where AR and VR technologies become necessary.

VR & AR: Play Hard, Work Harder

Virtual and augmented now form a different reality for manufacturing. These technologies can complement each other and work separately to deliver a much more stable production environment and outcomes.

There are plenty of sophisticated assembly processes that still require humans, as robots don’t have the finesse or can be too expensive for a company. Needless to say, it takes a lot of time to teach someone a single process like that and, in the end, this won’t guarantee the absence of any human errors.

AR is slowly introduced as an augmentation for workers involved in processes like these. Similar applications are also being explored for maintenance purposes, when a person without the necessary skills can perform maintenance, using guidelines presented via an AR headset.