Each of the so-called industrial revolutions were undeniably giant leaps for society. The first IR was started by the mechanisation and invention of the steam engine. The second provided assembly lines and mass production. The third focused on automation, mainly in electronics, including semiconductors development. The fourth, which we are currently experiencing, is the biggest improvement, reflected in the concept and idea of connecting devices. Applications that come with this opportunity are almost infinite, as well as the data that is generated.
The Fourth Industrial Revolution isn’t the only phrase that is totally brand new. The Internet of Things (IoT) has recently appeared and gained a lot of momentum too. It derives from a whole cohort of devices or sensors that collect information on different subjects, which can be further processed or forwarded for analysis.
Data collection and sensors improvement make up an important achievement and combined with Data Engineering – skills, knowledge, and project best practice, can provide robust and comprehensive systems designed to solve the most sophisticated challenges.
Industrial Internet of Things
Although Internet of Things and Industry 4.0 are described as two separate concepts, there may be an underlying perception that they both have something in common. Indeed, there are numerous examples where both are tightly coupled and cannot exist without one another as key digital transformation technologies. Let us examine four main characteristics that define Industry 4.0:
- Vertical networking of smart production systems allows timely reaction to recent changes in stocks or demands and is therefore more customer-specific.
- Horizontal integration via a new generation of global value networks provides optimisation across the entire supply chain - from production management and warehousing to logistics and marketing with logging, transparency, and flexibility.
- Through-engineering across the entire value chain involves a thoughtful process of new product development or modifications. It integrates all supply chain elements to provide a well-coordinated product life cycle.
- Acceleration through exponential technology takes all information into account and tries to optimise all aspects of the enterprise, including flexibility, cost-saving and innovations using new technologies.
In light of these definitions, it is natural to assume that the Internet of Things intersperses with Industry 4.0. In fact, the first two parts considering vertical and horizontal integration are perfect examples of this situation. Certainly, IoT can be found in the other two, but we will focus on the main applications.
Thanks to the combination of IoT and Industry 4.0, brand new phrases were coined: Industrial Internet of Things (IIoT) and Smart Manufacturing (SM). Their meaning is generally the same (although SM is a broad subset of IIoT – Industrial Internet of Things) and so in this article, they will be used interchangeably.
What they bring is a totally new, distinct, and high-tech area of business. Companies that specify or pivot in this direction base their supply chains or even products on big data.
Through cloud computing, they generate, fetch, and process a tremendous amount of information that becomes their bread and butter. Such big data is created via connected devices to the system. Often equipped with multiple sensors, they gather relevant information about manufacturing processes like stock amounts, robot location or assembly procedures progress.
This input, in most cases, is sent to the cloud systems that can conclude valuable data insights and store historical data for further analysis. Moreover, some of the decisions can be sent back to the devices to indicate ensuing tasks. There is even an area of industry - Edge Computing, which specializes in decision making development right inside the appliances so they can interact with the environment in real-time, effectively becoming smart devices.
Technologies driving Smart Manufacturing
Without a doubt SM wouldn’t take place without any technical development. There are a few new concepts and advanced topics worth considering that have accelerated this progress. Some of them include:
Artificial Intelligence (AI)
In fact, AI has been among us for a long time. The first scientific papers appeared in 1943, but the real power has yet to be discovered. Its purpose is to create algorithms and advanced structures that, based on the data provided, can make decisions. This includes both simple decision trees and extremely advanced neural networks created by the Google AI team.
Machine learning (the biggest part of AI) has made humans thrive in almost every aspect of their lives. Integrating AI in business processes has been the key to an improved customer experience, leading to higher customer satisfaction.
The same applies to IIoT, where decisions can be made in a much smarter way. Imagine warehousing robots that are approaching each other - every situation of that type requires an individual decision on whether to stop, continue, or turn. Another fine example is deciding whether a transaction/process is fraudulent. Understandably, implementing AI models into devices may be an incredible opportunity for a company.
The applications of self-driving cars or drones are expanding every day, and now quickly turning into a reality with user experience set to skyrocket. These innovations are still a major advantage from a business perspective, with delivery and transport industries set to go through the biggest revolution of all time.
The same applies to logistics and supply chain management. Reduced driver congestion caused by fewer driver errors and increased efficiencies will impact supply chain management overall.
Blockchain technology is now thought to be a key driving force behind digital transformation. Despite it being a digital technology with main applications in finance (i.e., cryptocurrencies), industries that require a stringent set of rules and procedures may benefit from it too. Scrutiny, quality assurance, or transparency are aspects that achieve completely different levels.
Industrial manufacturing firms can only benefit from improved quality control and customer satisfaction. Blockchain can profoundly affect companies from mining, food & beverage, healthcare, aviation, or cargo transportation, to name just a few, and is forming a part of their digital transformation.
Its main focus is to develop devices’ intrinsic ability to make decisions on the go, as well as process gathered data. It doesn’t come down to training sophisticated neural networks, but rather much simpler calculations.
Nonetheless, this functionality provides real-time results based on the environment. Let us consider inventory management and in particular, Amazon Smart Factory. Amazon’s Smart Factory robots know where to go to pick items from the shelves, despite obstacles and other machinery. Then, algorithms recognise exactly where to store a particular object, without any human interference. Amazon’s new technology allows them to perform tasks that a few years ago required much more time.
Digital transformation of physical objects or business processes into their binary counterparts may still maintain a science-fiction status. Despite the nascent stage, Digital Twins are gaining notoriety. Thanks to optimization algorithms that come with the digitalization of procedures can improve efficiency, including reducing time and costs of product development. First implemented by NASA, the concept is now widely used in many companies within industries such as aviation, electronics, or energy & utility.
IoT inside Smart Manufacturing (with examples)
Here are some examples of the above technologies driving Smart Manufacturing involve IoT:
- AI: farming robots deciding whether to activate irrigation systems based on soil moisture and other environmental variables
- Autonomous devices: warehousing robots analysing sensor data (live data from location sensors) and avoiding crashes with each other or with massive shelves
- Blockchain: plane parts manufacturing operation - sensors and robots can be integrated into co-working, blockchain-based networks and assure reliability for crucial aeroplane engines or wings procedures
- Edge Computing: sorting robots can support logistics chains in classifying parcels properly based on their weight and size within seconds
- Digital Twins: automotive industry can make use of multiple sensors while testing new vehicle prototypes - from air resistance to tyre traction, and then send it to their digitized version to calculate eventual adjustments
Apart from some generic examples, let’s look at some companies that use IoT technologies in their Industry 4.0 projects or products:
Airbus: Factory of the Future
An aerospace corporation has recently launched its new Smart Factory project. It involves a lot of IoT in the manufacturing process. Assembling a plane is a sophisticated procedure that needs thousands, if not millions, of parts.
What this initiative brings is using many sensors attached to the whole assembly line to oversee every step; even employees are given wearable high technology, e.g., smart glasses, and by showing and analyzing data caught by cameras, can tremendously reduce procedures risk.
John Deere revolutionizing autonomous vehicles
It is acknowledged that Google leads in self-driving technology. Nevertheless, many people say that John Deere is the true innovator. The company has advanced technology enough to produce autonomous electric tractors. Along with complex assembly lines, all tractors are equipped with multiple IoT sensors and devices.
These tools allow a boost in efficiency and reduce costs. Additionally, everything happens with extreme precision (within 2.5 centimetres, which is unbelievable when considering large farming vehicles)
Siemens: IoT as a Service
A German conglomerate that is well known for its huge offer of home appliances, from coffee machines to dishwashers. The company also specializes in industries such as healthcare, energy, and city infrastructure - in many cases, it was enough to involve IoT into their products (e.g., a Smart Factory using IoT to produce automated machines for companies like BMW or Bayer).
Furthermore, in recent years they have been developing software called MindSphere. Based fully in the cloud, it can aggregate and leverage data from different sources (like factory components) and by using advanced data analytics and Artificial Intelligence, its main focus is to provide great insights for other Industrial IoT (IIoT) companies.
The Internet of Things and Industry 4.0 are very broad subjects that, at first glance, do not seem to have very much in common. Beneath the surface, however, there exists a very powerful symbiosis.
As we have seen in this article, cooperation of these two concepts and technologies can enhance operational efficiency. Companies that are major players in the market are continuously investing in areas like the Internet of Things, Smart Manufacturing, and Industry 4.0. Although it may look just like another part of the strategic plan, it is a very smart and thoughtful step into gaining many profound benefits.