While most of the touted benefits of the Internet of Things (IoT) have yet to be seen, its impact is predicted to be total. From health care to manufacturing, the ever growing use of IoT devices is, to some, signaling the beginning of a fourth industrial revolution – Industry 4.0. As with the previous industrial revolutions that have followed, Industry 4.0 is expected to vastly change the way many industries work and how they manage their workflows. More specifically, it is expected to eliminate a large portion of human intervention that is currently required for the production of goods in factories and the through manually conceived supply chains. By way of sensors, A.I. and connected computing, IoT is expected to greatly automate the vast majority of commercial processes.
What is Industry 4.0?
Industry 4.0 is a term that is used to describe the industrial revolution that is said to be currently occurring. What does this industrial revolution entail? Largely driven by the Internet of Things and machine learning, the Fourth industrial revolution is one that will automate tasks previously not possible – or things not previously thought possible. This includes things like troubleshooting errors not before seen or the optimization of supply chains by analyzing and learning from sensor data. Industry 4.0 is the proliferation of smart Machine learning systems throughout all industries.
But this isn’t really tangible. It is helpful, then, to understand Industry 4.0 by contrasting it with the previous industrial revolution. Of course, automation and computing were a large part of the last industrial revolution, however, it was not “smart”. Things could be automated, but they could not fix themselves if the automation broke. Equally, they could not identify bottlenecks found within business processes or find opportunities to increase efficiency all on their own. Industry 4.0 promises to solve these issues.
The most popular example of Industry 4.0 in action is the smart factory. A traditional factory relies on hardcoded procedures and processes to source, manufacture and, finally, deliver to final goods. However, within the fourth industrial revolution, the factory will be able to understand and analyze itself and how it handles these processes in a way previously not possible. It will not only be able to find ways to optimize its current processes, but it will be able to allocate the proper resources, whether they be human or robot, to implement the optimized processes. Therefore, the smart factory will be able to operate itself largely without human intervention. By comprehensively connecting its manufacturing equipment with low-cost sensors with a machine learning system, it will be able to identify bottlenecks in its own procedures and workflows.
Yet, this applies outside of the factory as well. The supply chain, like the factory, can be tracked, monitored and optimized. With automated systems, driverless trucks could be mobilized to quickly optimize a supply chain in the event of disruptions such as poor weather, accidents or conflicts. Furthermore, with the growing popularity of drones as a method of fulfillment, they too, can be automated to supplement a burdened supply chain.
However, this carries with it, large social implications and a difficult caveat. Industry 4.0 is just another (big) step in the process of the automation of all jobs. Yet, there is currently no framework in place to deal with a future where there will be fewer jobs than people able to fill them. Considering that millions of people in the United States alone rely on the transportation industry to earn a living, legislation will eventually need to be put into place to protect the income of these people. Of course, some countries such as Canada are already starting research into guaranteed income, most are not. Inevitably then, there will be a middle point of uncertainty where workers will both be without jobs and without guaranteed income before we reach a sort of “Trekian” utopia.
How does Industry 4.0 Work?
While this may help us understand the impacts of Industry, it doesn’t help us understand exactly how it will work. Industry 4.0 is enabled in large part by the Internet of Things and Machine Learning. These two, working in conjunction, allow smart systems higher visibility into processes previously in the dark and, through machine learning, analyze the information to produce optimizations.
The Internet of Things
Although seemingly innocuous, IoT sensors, such as RFID tags, are to become one of the biggest driving forces of Industry 4.0. Until recently, it was impossible to coordinate and communicate with large amounts of sensors, let alone to do so cheaply. With enhanced sensor and communication technologies, sensors now allow for data collection on a large scale and allow for visibility into former data “black holes”. For instance, consider simple processes such as picking an order in a warehouse. In traditional warehouses, this process could not be tracked – a system could not optimize it because it could not “see” it. Traditionally, it would be cost prohibitive to add sensors either within the factory or on a worker to determine the kind of routes they are using to pick a product. However, with the introduction of cheap sensors, routes can be tracked and fed to a system to be automated. And this applies to all sorts of machinery and processes where sensors were previously not feasible.
IoT sensors, however, are only half of the story. Without the proper system to analyze and make sense of the data produced by these data collection points, they are useless. With machine learning, smart systems can adapt and learn from history to suggest better ways of working. To understand, let’s go back to the example of the warehouse worker. Yet, this time, the worker is tracked with IoT sensors backed with a machine learning back end. In this case, using the IoT sensors, the machine learning can analyze the worker’s routes and habits to suggest better ones. Of course, this might only shave seconds off of the total time for each pick, however, for large warehouses employing large numbers of workers, the cumulative effect of this can be huge. It is important to mention, however, that these sorts of tasks would not have been possible without the research done into Big Data, allowing computers fast access to query huge data sets to single out individual data points.
The Future of IoT
As physical processes become tracked with IoT sensors, businesses will begin to have a greater understanding of how their business procedures can be improved. However, it is inevitable that most these processes will begin to become performed, not by people, but by robots. In this case, the data collection will become even greater, but with adequate Big data powered machine learning systems, the optimizations will keep occurring. And, more importantly, they will occur less and less by way of human intervention.
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