Smart factories use these 9 technologies to navigate industry 4.0
With over 200 years of history, manufacturing has always been affected by technological developments and shifts throughout its existence. From the first industrial revolution to the introduction of the first computers half a century ago, manufacturing had to adapt.
In the last decade, changes and technological advancements happened at an unprecedented speed. Fortunately, they encouraged innovations in manufacturing, and forward-thinking companies didn’t waste any time adopting them. But to top it all off, the COVID-19 pandemic raised some serious questions about the resiliency of supply chains and the flexibility of operations in factories. It is not about thinking of the future anymore, it’s about surviving the present.
If you’re looking to take the steps towards developing a smart factory that can thrive in the age of Industry 4.0, read on to learn about the technologies that allowed factories and machines to become smarter, autonomous, and more efficient, and how they’re being applied in various industries.
If you want to step into industry 4.0 but you’re not sure where to start, we’d love to take a look at your manufacturing processes and help you create custom solutions for you. Let’s talk!
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What does industry 4.0 refer to?
The fourth industrial revolution is a result of all the new technologies being adopted in manufacturing. As computers and systems become more advanced and autonomous, they replaced humans not just on the assembly line, but in decision-making too.
The Internet of Things, Cloud computing, Artificial Intelligence, Machine Learning, and Big Data are some of the technologies that allow for better information flow by combining data from multiple factory levels and analyzing it. This results in increased automation, predictive maintenance, self-optimization of processes, and new levels of efficiency that ultimately translate into increased customer and employee satisfaction and less waste in terms of time, resources, and processes.
A short history of the 4th industrial revolution
Industry 4.0 is called the fourth industrial revolution for good reason. Let’s take a look at its history to see how we managed to get from steam engines to autonomous robots in the constant pursuit of creating better, smarter factories.
The first industrial revolution started in the middle of the 18th century and lasted until around 1830. It enabled the move from human and animal labor to the earliest types of mass production allowed by water and steam engines.
The second industrial revolution (The technological revolution) took place from the late 19th century into the early 20th century and allowed for even greater and more efficient mass production. It was made possible by the advancements in telecommunication (the telegraph and the phone) and a small degree of automation was made possible by the first assembly lines (powered by oil, gas, and electricity) and the introduction of steel.
The third industrial revolution started to take off slowly around the middle of the 20th century. It was made possible by the introduction of the earliest computers and methods of data analysis. Automation increased and data could be shared much easier.
The fourth industrial revolution, also known as Industry 4.0 gained most of its momentum in the past decade. The term Industry 4.0 was coined in 2011 and the shift was made possible by the introduction of cyber-physical systems in manufacturing. The computers that were used in the 3rd industrial revolution and now interconnected and autonomous. The information flows freely between all factory levels and decision-making is more transparent due to that. Data is stored in the cloud and Artificial Intelligence becomes better and better as it improves itself through feedback cycles. Ultimately, the smart factories of today are more efficient and create better products with fewer costs and resources.
Technologies in manufacturing that shaped Industry 4.0
Industry 4.0 in manufacturing is based on a few principles like interconnectivity between devices, sensors, and people, transparency in information and the removal of knowledge silos, technical assistance from robots, and decentralized decision-making by autonomous cyber-physical systems. These are all made possible by nine main technologies:
IIoT (Industrial Internet of Things) – In the Internet of Things, physical devices connected to the web can communicate with each other and share information. The IIoT allows devices from all factory levels to communicate, share data and act upon it with minimum human involvement. For example, most devices in a smart factory use sensors which provide data, and upload it to the cloud where AI can analyze it and make decisions. Companies that use this, have smoother supply chains, less downtime in production, and better quality assurance for the products they sell as well as those that they use.
Cloud – Cloud computing is at the base of Industry 4.0 – this is where all data resides, making it possible for cyber-physical systems to access it as quickly as possible and in an organized manner. Cloud is essential for any smart factory. The more advanced the machines and sensors, the more data they will use, creating the need for bigger and bigger digital storage space. Cloud is the answer to this, as it stores the most data efficiently.
Big Data, AI & ML – In the factories of Industry 4.0, Big Data allows for the collection of large quantities of processed information from all factory levels (production line, business units, and even third-party sources). Artificial Intelligence and Machine learning allow the analysis of data in real-time leading to faster and more transparent decision making and automation. Systems also improve themselves over time, as more data is introduced and patterns are observed.
Additive Manufacturing and 3D Printing – In industry 4.0, 3D printing is used to prototype new products faster and cheaper, validate them and make informed decisions on what happens next. Instead of launching a full-scale version and then testing it, only to rebuild it again, manufacturers have way more flexibility in testing features. 3d printing also helps with reducing storage space and transportation costs as digital files of physical products can be stored and printed only when they’re needed.
Augmented Reality – With AR, data extracted from the cyber-physical systems can be visualized in an organized manner. It is also helpful with the visualization of physical parts of machines as well as training content. Maintainance and quality assurance are also improved, both in products and services.
Simulation and Digital Twins – Digital twins are essential in the smart factories of Industry 4.0. They are digital profiles of physical objects or processes that exist in the factory. Their “simulated” digital version allows for a better understanding of them and the possibility of improving their performance and even predicting maintenance issues.
Horizontal and Vertical integration – Free flow of information is essential in a smart factory and these two types of integration make it possible while also avoiding the formation of knowledge silos that existed in old systems. In other words, all processes are integrated and data is exchanged between all of them.
Cybersecurity – With the integration of big data in manufacturing, the issue of cybersecurity is raised as a result. But with all the capabilities and architectures that are available, companies can and should increase data protection and minimize any risk.
Advanced Robotics – The new generation of autonomous robots paired with the latest technologies (AI, sensors, and machine vision) can perform complex tasks and take action by themselves on information they receive and analyze from other connected devices.
Applications of technologies in manufacturing – Smart factory examples
AI & ML in sales helps Mercedes bring in qualified leads
Artificial Intelligence and Machine Learning in smart factories help with the collection of data and real-time analysis leading to more informed decision making. This doesn’t only apply to the production line, as this Mercedes example shows us.
Mercedes is using Azure Machine Learning to bring together both internal and external data such as registration numbers, economic indicators, legislation issues, and sales information. “All this helps the brand’s salespeople to make the right offer, to the right person, at the right time.
Big data helps Heineken eliminate inefficiencies in their supply chain
With big data, manufacturers collect, analyze and forecast the processes in the supply chain making it more flexible and more efficient.
Heineken is an example from the brewing industry. Big Data helps them understand the relationship between external drivers (consumer demands, economic volatility, competition information) and internal drivers (E2E optimization, costs, planning landscape, silos) and to create a shared forecast.
“Through data analytics, the brewer can adjust production when there is high inventory, long production or replenishment lead-times, and seasonal variances in the demand for its products.”
With digital twins, Unilever predicts and improves all factory operations
Digital twins in industry 4.0 are a digital simulation of any physical object or environment. Unilever created a digital twin of their whole factory, which allowed them to test changes and improvements at all factory levels. So if, for example, they are going to make changes to the machines on the production line, in the digital simulation they can see how this affects everything in the product cycle after that.
“The digital twin has used data on how long it takes to produce one batch of liquid, such as shampoo or detergent, to predict the correct order of processes to get the most efficient batch time. The less time each batch takes, the higher the production capacity of the plant, fully utilizing the asset and avoiding having to invest in capability elsewhere.”
Are you ready to step into Industry 4.0 and future-proof your factory?
All these changes are here to stay. With all the technologies in manufacturing and the fact that they are so widely available, there is no excuse anymore to stay out of the fourth industrial revolution. They are not buzzwords anymore and definitely not fads. Big Data, IoT, AR, AI, and ML are here to help you improve your manufacturing processes, and create better products with fewer resources and in less time. Ultimately, these all lead to more satisfied clients for your factory.
Are you willing to take the first step into transforming your factory but you’re not sure where to start? We would love to have a chat, take a look at the bottlenecks in your production cycle, and create custom solutions for you. Write us a short message and we’ll reach out to you ASAP to talk more about how we can help you.