Industry 4.0 | an overview

Which technology makes the Internet of Things possible for industry

In this guide we give a comprehensive introduction to Industry 4.0 and the Internet of Things (IoT). Take a look with us at past technological developments and the challenges of tomorrow!
Industry 4.0


  • What is the Internet of Things?
  • What separates the IIoT from the IoT?
  • What exactly is the difference between Industry 4.0 and the Internet of Things?
  • What is the Industrial Internet of Things currently being used for?
  • Why switching to Industry 4.0 is worthwhile
  • What challenges does Industry 4.0 face?
  • IIoT networks and protocols
  • IIoT data protocols
  • frequently asked Questions

What is the Internet of Things?

In short, it is the general term for connecting devices, much more than just PCs, smartphones or other telecommunications devices, to the Internet. These are often referred to as “smart devices” or smart devices, such as fitness trackers or voice assistants.
The abbreviation IoT ( Internet of Things ) is also common in German and English. The term has been on everyone’s lips for years and the industrial sector, in particular, has long since discovered it for itself.

What does IIoT mean?

This brings us to the so-called Industrial Internet of Things, which is often equated with Industry 4.0. The IIoT takes the concept of internet-connected devices and extends it to factories, manufacturing and industrial plants to share data quickly from near or far. For example, sensors can collect information and transmit it to the local network via a gateway and from there upload it to a cloud server so that you can access it from anywhere at any time. Incidentally, the direct, automatic control of networked devices is also referred to as a cyber-physical system.

What separates the IIoT from the IoT?

The main difference between IoT and Industry 4.0 lies in the application. While the former is for comfort, health and entertainment, the latter is all about collecting and processing sensor data in real-time to increase efficiency, optimize processes and save costs. It is not for nothing that one also speaks of a fourth industrial revolution.
The Industrial Internet of Things is based on a well-known form of computer-aided control, the distributed control system, which connects several autonomous devices and assigns them functions. These devices are thus able to continue to adjust and optimize the section of the production line they monitor independently, without the risk that a single fault in the system will bring the entire production to a standstill, as is the case with a centrally regulated controller would. The IIoT takes advantage of modern cloud computing to enable data sharing, visualization, and analysis—all in near real-time.
Within a few years, Industry 4.0 has developed into a huge sector. More than 60 per cent of global manufacturers now use IIoT-Tec.

What exactly is the difference between Industry 4.0 and the Internet of Things?

Although the terms Industry 4.0 and Internet of Things are sometimes used interchangeably, they are not synonymous. In fact, the Internet of Things and IIoT are part of Industry 4.0.
Industry 4.0 is generally used to describe the accelerated use of all advanced automation technologies available to industry and intelligent manufacturing today and the resulting benefits. The key components are:

  • Machine-to-Machine Communication (M2M)
  • Implementation of autonomous systems
  • Seamless cloud computing
  • Artificial intelligence and related ‘cognitive’ technologies such as image recognition

The history of the IoT and Industry 4.0

The Internet of Things may seem like a very modern concept but in fact some of the core technologies that make up Industry 4.0 date back to the 1960s. As early as 1968, programmable logic controllers (PLC’s) – essentially early industrial computers – were developed to fine-tune the manufacturing process. From the 1970s, the first industrial process control systems appeared, which gradually supplemented the manual work in the factories.
The Internet of Things as we know it today first came into focus in the following decade. In the early 2000s, the IoT gradually left research institutions such as universities and laboratories to reach the end-user. The development of enabling technologies such as Bluetooth, Near Field Communication (NFC) and 3G cellular networks accelerated the growth of this market. At the beginning of the millennium, cloud computing technologies, in particular, favoured the development of the IIoT.

What exactly does Industry 4.0 mean?

The term “Industry 4.0” first appeared in public at the Hanover Fair in 2011 to describe the use of information technology in production. The neologism was intended to place the impact of modern technologies on automation and data exchange in the wake of earlier industrial revolutions. These are:

  • The development of steam and water-powered manufacturing technology in the second half of the 18th and the first half of the 19th century,
  • The use of electrical energy, especially in connection with assembly line work between about 1870 and the beginning of the First World War,
  • The third, so-called digital revolution, with the creation of modern IT in the second half of the 20th century and the developments already described above.

What is the Industrial Internet of Things currently being used for?

Industry 4.0 can bring a variety of benefits to a wide range of industries and sectors, including:

  • Smart production facilities and buildings
  • Supply chain and inventory optimization
  • data analysis
  • condition monitoring

The IoT has already found its way into various sectors, of which pure production is by far not the only sector that can benefit from Industry 4.0. The energy industry and retail can also participate in the revolution thanks to ever-smaller smart devices and intelligent solutions.

Why switching to Industry 4.0 is worthwhile

Despite the boom, not everyone is aware of the concrete benefits Industry 4.0 is supposed to bring. Therefore, we would like to give some examples below of how the manufacturing industry has benefited from the implementation of IIoT so far:

  • Production line optimization: Industrial IoT sensors enable continuous monitoring of the production line from start to finished product. This allows operators to continuously fine-tune the manufacturing process, saving time and money.
  • Inventory and Supply Chain Management: Manufacturing depends on the delivery of raw materials and components. ⦁ Radio Frequency Identification ( RFID) tags and similar wireless technologies enable real-time tracking of components and shipments from site to site, making inventory and reconciliation monitoring much easier.
  • Packaging assessment: Industrial IoT sensors enable manufacturers to monitor the condition of packaging during transport and storage, and even assess how customers typically interact with it. The data submitted is extremely valuable because it allows for design improvements.
  • Real-time manufacturing data: By transmitting operational data, suppliers can remotely manage the factory units at any time, conveniently.
  • Maintenance data: Smart devices and sensors can issue alerts as soon as an error occurs and maintenance work is required. In the same way, malfunctions or the exceeding of limit values, such as excessive operating temperatures or excessive vibrations, can be reported. In this way, maintenance can be planned in advance, downtime can be minimized and the risk of accidents can be significantly reduced. When combined with health and safety records, such sensor data can contribute even more to safety.
  • Quality Control: Combining IIoT data from various sources, including suppliers, manufacturing processes and end-users, provides a more comprehensive picture that can be used to drive overall improvements from production and delivery processes to optimized user experience.

What challenges does Industry 4.0 face?

Industry 4.0 is basically an interaction of several network technologies. The three main challenges can therefore be summarized as follows:

  • The selection of strong signal networks, both wireless and wired
  • Adoption of standardized protocols, e.g. OPC UA
  • Network security vigilance to ward off any cyber threats

The technological requirements such as procurement of the devices are therefore the least of the problems in the transition, but there is a high demand for uninterrupted connectivity. In addition, an understanding of IT security and data storage when implementing IoT in industrial operations is essential to ensure smooth and efficient implementation.

What are the risks of the industrial Internet of Things?

As with any other digital solution, cyber security is critical for the IIoT, but with the appropriate precautions such as staff training and encryption of data transmissions, these risks can be minimized.
With this in mind, it is important to stay current with the latest technologies and updates. So you can be sure that you are always keeping up with the new developments regarding Industry 4.0 and derive the greatest benefits from them.

IIoT networks and protocols

Like any other information technology, the Industrial IoT uses a variety of protocols (data communication formats) and network types. Therefore, it is important to get clarity about each individual protocol when planning to create an IIoT infrastructure for your production facilities.

IIoT networks: how to choose the right hardware!

Internet-enabled devices each use different technologies for networks. Which of these offers the best solution depends on a number of factors, such as the distances to be bridged, the amount of data to be transmitted, the location and power consumption.
New networks are constantly being added to the list of networks suitable for Industry 4.0 and IoT. We have compiled the currently most important ones for you:


Both in private households and in the industrial sector, WLAN is the common radio transmission standard for PCs, smartphones, tablets and more. WLAN networks are integrated into networks via routers, similar to wired Ethernet networks. Most devices use the 802.11 standards defined by the IEEE Association (Institute of Electrical and Electronics Engineers), also known as Wi-Fi.


Bluetooth is a connection standard developed by the Bluetooth Special Interest Group, an interest group of more than 34,000 companies, and is also widely used in the consumer sector. It is based on ultra-high-frequency radio waves (between 2.402 GHz and 2.480 GHz) with a relatively short range. The advantage is the extremely interference-free radio transmission. It is, therefore, suitable for a number of different applications.


Zigbee is one of the leading protocols for connecting smart devices. This is a low-power network that is widely used, especially in industry. It is related to the Dotdot protocol developed by the same team and uses the IEEE 802.15.4 standard, which has a transmission range of up to 300 meters under ideal conditions. In buildings, it still reaches an impressive 75 to 100 meters. The current version 3.0 offers 128-bit encryption for secure data transmission.


LoRaWAN is the abbreviation for Lo ngRange Wide Area Network, an extremely energy-efficient MAC protocol with a transmission range of up to ten kilometres. It offers secure two-way connections over very large networks and can also be applied to digital radio transmission using FSK modulation.


The French telecommunications company Sigfox uses extremely low-power technology for a comprehensive network, similar to the Low Power Wide Area Network (LPWAN). In this way, small smart devices in continuous operation, such as electricity meters and smart-watches, can exchange data in a particularly efficient manner. The power consumption is only a thousandth of that of other radio technologies

IIoT data protocols

  • MQTT (Message Queue Telemetry Transport) is an open, low-power message protocol used to transfer simple data sets between sensors and applications. It is based on the common network protocol TCP/IP (Transmission Control Protocol/Internet Protocol).
  • AMQP (Advanced Message Queuing Protocol) is an internationally recognized open-source standard for transferring messages between devices.
  • OPC UA (OPC Unified Architecture) is an open M2M communication protocol that combines cross-platform shared data exchange in industrial automation with robust system interoperability.

Frequently asked Questions

Can the IIoT replace MES?

MES (Manufacturing Execution System) is an established hardware-based control system for complex manufacturing processes, typically used to ensure efficiency and improve productivity. This is a closed system. It, therefore, does not have the cloud-based analysis and external network functions that are important for Industry 4.0. An extension of the traditional MES with such makes sense, but a complete replacement with IIoT infrastructure is hardly worthwhile for economic reasons alone

What is the advantage of the Industrial Internet of Things for engineers?

The IIoT enables the collection and analysis of a large amount of data that can be collected in several phases of the manufacturing process. In this way, the continuous optimization and improvement of systems can be promoted.

How does the IIoT work?

An IIoT network consists of multiple sensors connected via different wireless protocols to exchange data with the cloud and each other. The basic structure of an IIoT network is as follows:

  • Devices and hardware equipped with sensors, each connected to the local network,
  • The local network itself, which in turn is connected to the Internet and cloud services,
  • Cloud-connected servers that process relevant data such as operating temperatures, mechanical faults and power consumption. Such smaller amounts of data condense over time into big data, which can be analyzed to gain deeper insights into your operations.

What is the difference between Industry 4.0 and Lean Manufacturing?

Lean manufacturing is a production organization method aimed at minimizing waste and maximizing productivity. The principles go back to the 18th century and were formulated in the early 1990s as part of an MIT study of the Japanese automotive industry. Industry 4.0 can support lean manufacturing but is not absolutely necessary for it.

How much does it cost to implement an Industry 4.0 solution?

The costs depend on how large and type of manufacturing processes you want to optimize. Therefore, there is no definitive answer to this question.

5 tips on how to quickly make your product IoT-compatible

This is how you make your products fit for the IoT (Internet of Things)! 5 strategy tips that you should consider when engineering to secure your market share in the digital transformation.

we have the most important tips for implementing your product's IoT connectivity

More and more companies want to better position their products for the digital transformation. This year alone, around 26 billion IoT devices will go online worldwide. On the one hand, making them IoT-capable is not always easy and, on the other hand, it does not always make sense. Many are trying to make their existing products smarter and more connected. This is possible in many cases, but not always the most appropriate way. Because in digital engineering, too often products are created that offer no added value either for the company or for the end-user. For the product development of a successful IoT device, the approach must be customer-centric. Furthermore, suitable digitization skills and, last but not least, the right digitization strategy are essential. Because studies show: Around 25-45 per cent of all new IoT device developments fail. In dynamic digitization, some products are very well received, while others are already doomed to fail when they are launched.
So what separates successful IoT devices from the rest? If we look at companies that are successful in digitization, we get an idea of ​​​​how products can become compatible with the Internet of Things. We can learn from this and transfer experiences of such digitization strategies to product development. Implementing IoT connectivity to digital devices can be difficult. Especially if it’s the first time. So what does it take to make an existing product IoT compatible? And what are the advantages of product development of an innovative digital device for the Internet of Things?

Digitization: check the added value of connectivity!

Before you start developing an IoT product, you should ask yourself the following questions: If the product is smart after engineering, does it add value for you and your customers? And can the product collect useful data? Most products today can already collect data in some way. However, not all of this data is of any value to you or your end-users. For companies, the following must be clarified:

⦁ Can you integrate IoT data into your business processes?
⦁ Will you be able to effectively use the data collected to improve service to your customers? Because: A new IoT device is only successful when it is clear how the data will offer added value after engineering.

Product development: Include the cost of the IoT device!

Smart devices generate costs that a conventional product would not have. It is important to include these costs in the digitization strategy for product development:

  • What are the manufacturing costs? Is it clear how the connectivity costs will be covered? Normally, this happens through a higher sales price, but more and more often through service or subscription fees over the product life.
  • What are the ongoing costs for device support? Does the product generate large amounts of data that need to be stored in the cloud? Does the product require computationally intensive cloud services such as speech recognition?
  • What support does you as a company have to provide the end-user with product defects or upgrades?

Check the marketability of your intelligent device!

From a technology point of view, you can make any product IoT compatible. But is it worth it? While a WiFi-enabled watering can certainly be a nice idea, the demand for product development of such a device would be rather limited.

  • When it is clear what value your smart system will have for you and the end-users and you know the costs, you need to ensure that the product is marketable after engineering.
  • Can the value of product development be communicated to your potential customers quickly and easily? Do you understand this and are you willing to pay for it?
  • In particular, when innovating in a new category, you should answer the following questions: What is the greatest single value that your IoT device offers to the end-user? Can you simply communicate this value in terms of your product digitization strategy?
  • Be careful with new features in your engineering strategy. Each function is associated with development costs and makes the digital product more complex. Many companies add features hoping it will make the product more attractive. But often a simpler product offers more enjoyment and thus has a higher overall value.
  • To know if your product is IoT-ready, you should develop ⦁ prototypes of your digital devices. Do not develop the whole product at once, but proceed step by step in engineering. User experience testing and surveys of existing customers will help you create a more valuable digital product and better understand potential costs. That way, you’ll spot problems where you never expected them. And the digital product that comes out will be better.

Digital engineering: What you should pay attention to when it comes to technology and design

As soon as you are sure that the digitization strategy for your product is understandable to your customers, the device has added value and the costs fit into the business model, you can start planning – taking a few other points into account.
So there are different connectivity options for your digital innovation that you have to consider. Most IoT devices connect to a network via an app via Bluetooth or WiFi. The user then controls the device via the app. However, smart home devices often also use their own protocols (eg Zigbee) and there are also more and more devices that connect to the Internet on a mobile basis (eg NB-IoT or LTE- m). Each technology has advantages and disadvantages depending on where and how the device is used and the costs that the digitization strategy can support. Safety is important here, for example. The sheer number of IoT devices and the inconsistent security practices of device manufacturers have increasingly made the devices targets of cyberattacks.

“Hardware is hard” is a popular saying among hardware engineers. However, it is becoming increasingly easier to develop a new IoT device or to make existing devices IoT-capable. Prototyping has also become easier as companies now have affordable development boards and prototyping kits at their disposal. Standardized hardware components mean that companies don’t have to start from scratch when it comes to engineering and can start testing ideas quickly.

If the ideas prove successful, standardized development boards and 3D printers can be replaced with optimized custom boards and injection moulded parts that can be produced in high volumes. These individual design and engineering phases to create a product that can be mass-produced require many different skills and high investments. Good research beforehand and prototyping to get real user feedback gives you confidence that your system is on the right track and the investment will pay off.

The single largest item of an IoT solution is often the software. For an IoT device, there is embedded software for the device hardware, IT for cloud services (IoT platforms) and app software on the smartphone or computer. All of these and other elements must interact seamlessly with one another, like in a network. This ecosystem requires a lot of coding and testing to ensure the system performs optimally under a variety of conditions.

Great design and a carefully crafted user experience are not the only things that make an attractive product. The task of setting up a new IoT device can seem daunting at times. It is therefore important to make the first user experience after digitization as convincing and simple as possible. The entire digitization process, ie every step from connecting the device and installing the IT to using the product for the first time, must be carefully planned and implemented. Support calls and product returns can erode the profits of a new product. The response rate for consumer devices is estimated at 11-20 per cent. And 95 per cent of returns are not due to defects or defects. The product can work as desired and yet it does not satisfy the user. While industrial products don’t have the same response rates, user expectations are now just as high. And since many IoT products are based on service fees or subscription models, it is important that the products are used for a long time.

After product development: How to properly deal with competitors

You have completed all of the above steps. You know what to do with your hardware and software. You know how to make your product IoT-enabled. But then you discover that someone else has already developed the product you are planning to implement. A horror scenario! What should you do now?

It’s not necessarily a bad idea to develop something that already exists. Because that means: There is already a market for the innovative product. What you need to do is position your device in a way that offers value to your customers. What can your device do that the other cannot? What overall value can you offer your end-users, ie how do you show them that you really have their needs in mind?

If you can show your customers how your product differs from those of your competitors, you can better position and sell your product in the market. Turning your product into an IoT device is not always a good idea. However, if you have a marketable product that adds value and you can integrate the necessary hardware and software, you are well on your way to creating a successful smart digital device.

Industrial IoT platform as a pioneer for medium-sized companies

Thyssenkrupp Materials Services, together with Intel as a partner, has not only networked its own production landscapes in one platform: the project resulted in toii, a digitization platform for medium-sized manufacturing companies.

“The pace of innovation has increased significantly in recent years and processes are increasingly being digitized and networked. In this environment, it is becoming increasingly important for companies to work with competent partners they can rely on for innovative solutions to secure competitive advantages and gain a foothold in Industry 4.0.” – Sebastian Lang, Managing Director of thyssenkrupp Materials IoT GmbH 
Industrial IoT platform

The networking of machines and systems is still one of the greatest challenges in the Industry 4.0 environment. It is necessary to network heterogeneous landscapes from new and sometimes decades-old systems (by means of retrofitting) within a common data model based on IoT. As one of the world’s largest suppliers of materials, ThyssenKrupp Material Services has over 4,500 production machines and systems from a wide variety of manufacturers in use in its plants. The goal was to network these assets flexibly in order to increase plant productivity and create more transparency for more efficient production.

At the same time, the respective individual production environments were to be retained. The company did not find what it was looking for on the market: the offers from the major platform providers proved to be too complex and inflexible. That’s why the decision was made to build our own, tailor-made IIoT platform with Intel as a partner for the hardware. thyssenkrupp Materials IoT GmbH (tkMIoT), a subsidiary of thyssenkrupp AG, was responsible for the project.

The modular IIoT platform incorporates edge and cloud analytics

A whole range of tasks was mapped with the toii platform, from machine data collection (including connection, transmission and storage), to production data collection from users and devices, to machine automation with bi-directional communication. The platform enables the visualization of production data, for example for benchmarking, and organizes the complex data integration from different data sources, including ERP systems.
The Manufacturing Execution System was also integrated. A particularly important part was the topic of edge analysis for production optimization and quality assurance with real-time production screening. The end-to-end platform enables AI and machine learning to be deployed at the edge, on-premises or in the cloud.

Optimally coordinated hardware and software

Thanks to the individual modules, the platform maps many application scenarios and is easily scalable. The solution consists of Intel servers and Industrial PCs (IPCs) with the necessary storage and network resources, including gateway technology for connectivity.
With IIoT, the interaction between software and hardware determines the efficient real-time processing of data. Thanks to the intensive cooperation, tkMIoT was able to rely on the optimal combination of hardware technologies: The solution consists of Intel servers and industrial PCs (IPCs) with the necessary storage and network resources, including gateway technology for connectivity.

Making success accessible to other companies

Since 2017, the platform has been successfully implemented at more than 30 locations and the entire range of machines and multi-stage production systems, but also the IT systems, have been connected to toii. ThyssenKrupp Materials Services was able to achieve clear advantages: process automation reduced downtimes by up to 50 per cent and increased production by 20 per cent compared to the previous year. In addition, many error-prone, paper-based processes have been eliminated.
ThyssenKrupp Materials IoT decided to use the solution to pave the way for production digitization and automation for other companies and to market toii as part of the Intel IoT Market Ready Solutions program. External customers include GGK, a subsidiary of the Grün Group, which relies on the platform to extensively network its production. Steel Service Krefeld introduces toii.
Lights to digitally network analogue machines and collect data for further processing.

Industrial IoT platform as a pioneer for medium-sized companies

Together with Intel as a partner, Thyssenkrupp Materials Services has not only networked its own production landscapes in one platform: the project resulted in toii, a digitization platform for medium-sized manufacturing companies.

Industrial IoT platform
Industrial IoT

The networking of machines and systems is still one of the greatest challenges in the Industry 4.0 environment. The aim is to network heterogeneous landscapes from new and, in some cases, decades-old systems (by means of retrofitting) within a common IoT-based data model. As one of the world’s largest material suppliers, ThyssenKrupp Material Services has over 4,500 production machines and systems from a wide range of manufacturers in use in its plants. The aim was to flexibly network these assets in order to increase plant productivity and create more transparency for more efficient production.
At the same time, they wanted to keep the respective individual production environments. The company did not find what it was looking for on the market: The offers of the major platform providers proved to be too complex and inflexible. That is why the decision was made to set up its own, tailor-made IIoT platform with Intel as a partner for the hardware. Thyssenkrupp Materials IoT GmbH (tkMIoT), a subsidiary of thyssenkrupp AG, was responsible for the project.

The Industrial IoT platform incorporates edge and cloud analytics

A whole range of tasks was mapped with the Industrial IoT platform, from machine data acquisition (including connection, transmission and storage) to production data acquisition from users and devices to machine automation with bidirectional communication. The platform enables the visualization of production data, for example for benchmarking, and organizes the complex data integration from different data sources, including ERP systems.
The Manufacturing Execution System was also integrated. A particularly important part were the topics of edge analysis for production optimization and quality assurance with production screening in real-time. The end-to-end platform enables the implementation of AI and machine learning at the edge of the network on-site or in the cloud.

Optimally coordinated hardware and software

Thanks to the individual modules, the platform maps many application scenarios and can be easily scaled. The solution consists of Intel servers and industrial PCs (IPCs) with the necessary storage and network resources, including gateway technology for connectivity.
With IIoT, the interaction between software and hardware determines the efficient real-time processing of data. Thanks to the intensive cooperation, tkMIoT was able to rely on the optimal combination of hardware technologies: The solution consists of Intel servers and industrial PCs (IPCs) with the required storage and network resources, including gateway technology for connectivity.

Make success accessible to other companies

The platform has been successfully implemented at more than 30 locations since 2017 and the entire range of machines and multi-level production systems, as well as the IT systems, have been connected to toii. ThyssenKrupp Materials Services was able to achieve significant advantages: Thanks to process automation, downtimes were reduced by up to 50 per cent and production increased by 20 per cent compared to the previous year. In addition, many error-prone, paper-based procedures have been eliminated.
ThyssenKrupp Materials IoT decided to use the solution to pave the way for other companies to digitize and automate production and to market toii as part of the Intel IoT Market Ready Solutions program. External customers include GGK, a subsidiary of the Grün group, which relies on the platform for extensive networking of its production. Steel Service Krefeld introduces toii. Lights to digitally network analogue machines and collect data for further processing.

Industry 4.0

Industry 4.0
Industry 4.0

Industry 4.0 is the digital transformation and automation of traditional production companies. Industry 4.0 is often referred to as the “fourth industrial revolution” or “smart manufacturing”. By digitizing machines and systems, including the Internet of Things (IoT), traditional processes and procedures should be made more intelligent and autonomous. Industry 4.0 affects a whole range of sectors such as construction, food and beverage, aerospace and the automotive industry.
Industry 4.0 increases productivity, lowers costs and improves international competitiveness. Read on to find out more about Industry 4.0. Learn more about the new technologies that are transforming traditional manufacturing operations into smart factories and get an idea of ​​the advantages and challenges facing production areas.

What is Industry 4.0?

Under Industry 4.0 means the optimization of traditional manufacturing industries through the Internet of Things (IoT) and other technologies. In addition to automating production, these new technological possibilities enable complete digital transformation. The aim is an optimized and data-driven production environment.
The driving factor of Industry 4.0 is data obtained through networking. Technologies from the field of Industry 4.0 record and collect data from production independently of company or machine systems. IoT, cloud computing, data lakes and other computer-based technologies are used. These technologies can improve traditional manufacturing industries through data-driven process optimization. Manufacturing facilities are becoming more efficient and flexible and can produce high-quality products at lower costs.

Industry 4.0 is the next after the three well-known and successful industrial revolutions. The first industrial revolution (around 1760) came about as a result of the invention of the steam engine and enabled the transition from manual to machine production. The second revolution (around 1870) is also known as the technological revolution and included numerous technical improvements such as electricity and railways. The third revolution (the 1960s) brought computerization and was characterized by the use of computer systems for mass production and automation. We are now experiencing the fourth revolution, which is driven by data and the IoT.

The term Industry 4.0 has existed since 2011 and came up as an idea and strategic initiative of the German federal government and German industry. The German economy is heavily dependent on traditional sectors such as mechanical engineering or the electrical, automotive and pharmaceutical industries. In order to remain internationally competitive, Industry 4.0 technologies are increasingly being used in German factories. 
The digitization of the manufacturing industry is also being promoted. In Germany Industry 4.0 is also associated with the term “Work 4.0”, a conceptual framework for the discussion about the future of work.
Let’s take a look at the technologies Industry 4.0 offers for smart production lines:

12 Industry 4.0 technologies

Industry 4.0 knows twelve essential industrial technologies and trends.

Additive manufacturing

3D printing and digital manufacturing to create lighter, better performing parts and systems. Additive manufacturing enables quick and individualized implementation. Manufacturing companies can manufacture the parts they need themselves, precisely when and in the required design.

Advanced Robotics

Modern autonomous robots will work side by side with humans. Robots enable new forms of collaboration, higher speed and higher efficiency. They also reduce costs and improve workplace safety.

Augmented Reality

Augmented Reality technologies can be used to control robots, for maintenance, assembly and repair work, for training purposes and quality controls or for monitoring production processes and for auditing systems. With augmented reality, companies can reduce errors, improve security, save time and cut costs.

Big data and data analysis

This means the acquisition and analysis of data from various sources, e.g. data from conventional machines and sensors or from customer relationship management software (CRM) or enterprise resource planning systems (ERP). In most cases, Industry 4.0 solutions enable manufacturing companies to systematically collect data from parts of the supply chain for the first time. With big data analyzes, managers can make data-based decisions, which leads to optimization and increased productivity.


The implementation of cloud computing technologies enables the storage, management and sharing of data. For the growing amount of data generated by smart factories, the cloud is essential. It enables scalability and improves collaboration.

Cyber security

Cyber security ensures secure communication between machines, devices and industrial systems, especially in systems that are being networked for the first time. A high level of cyber security is essential to maintain confidentiality and data protection. Cyber security prevents data breaches that could endanger the entire plant.

Horizontal and vertical system integration

This is about the complete integration of all data from all departments, teams, functions, production and components and that across the entire value chain. Complete integration is essential for end-to-end monitoring and for building a reliable database (SSOT-Single Source of Truth). This database serves as the basis for decision-making, the allocation of resources and the organization of cooperation in order to enable lean manufacturing. This is also one of the greatest challenges of Industry 4.0.

Simulation / digital twin

A digital twin is a virtual copy of a real process with real data. Before a decision is made, simulation tools are used to test and optimize processes. In this way, error rates can be reduced, costs lowered and processes optimized.


Sensors connected to machines enable performance, system and environmental characteristics to be recorded. Manufacturing companies can use sensors to collect data from production. This data can be used for monitoring purposes, for predictive maintenance, to optimize processes and improve machine availability, or in general for data analysis.

AI (Artificial Intelligence)

AI enables the optimization of tools, technologies and processes through intelligent machine algorithms. In principle, AI technologies can always be used to improve Industry 4.0 solutions, for example, to improve monitoring, maintenance, robotics or operational management.

11. ML (machine learning)

With machine learning, a branch of AI, manufacturing processes can be optimized on the basis of recorded and collected data. This also includes calculation models and algorithms from the field of operational excellence.

12. Industrial Internet of Things (IIoT)

This means the digitization of all devices and machines used in industry. Older machines without their own control can also be digitized. The IIoT enables collaboration, data acquisition and optimization in real-time. The industrial Internet of Things forms the basis for generating data for most other Industry 4.0 technologies.

Advantages of Industry 4.0 for manufacturing companies

Industry 4.0 is useful in many ways for manufacturers in a wide variety of industries, from food production to automotive suppliers. The following benefits are mentioned as examples:

Productivity and efficiency

The main benefit of Industry 4.0 and smart factories is that the respective industries can increase their productivity and improve their efficiency. How does it work? With Industry 4.0 technologies, production companies can collect data and use the analysis of this data to improve their key business figures. The new processes ensure data-based and therefore more intelligent decision-making. Bottlenecks can be identified and resource allocation optimized. Barriers are removed and, as a result, machine availability is increased, so that performance and production quality increase.

Cost reductions

As a result of improved productivity and efficiency, costs decrease and profits increase. The costs also decrease thanks to improved resource allocation, shorter production times and fewer downtimes, thanks to improved quality and less waste or rejection. In addition, so-called predictive and preventive maintenance enable optimized machine maintenance. Wear and tear are reduced and depreciation is increased. Although Industry 4.0 naturally requires a certain initial investment in new technologies, the return on investment (ROI) is still significant.

Traceability and transparency

The networking of all machines and systems enables data to be collected. This information can be used to transparently track the performance and output of the machines. This enables managers to better monitor and control operational processes. This enables the optimization of production processes and the improvement of product quality. Key figures can be set and monitored. In addition, the data can also be used to comply with legal regulations more easily.

Agility & Innovation

Industry 4.0 enables deeper insights into production. You will then better understand where the bottlenecks are, introduce scalable technologies and work together better on processes. Production companies are thus given the flexibility and agility they need to reorganize the allocation of their resources, introduce new processes and implement ideas.


Many manufacturers are still competitive due to lower costs and increasing product quality, even without cuts in wages or even outsourcing to low-wage countries.

Industry 4.0 challenges

Even if Industry 4.0 brings many advantages, there are also some challenges

Initial investments

Industry 4.0 offers a very advantageous return on investment (ROI), but also requires a certain investment that not all companies may be able to shoulder. This includes, for example, investments in new technologies, training courses and machines. Adjusting business models can also result in costs.

Data protection and security risks

When communicating between devices (D2D – Device to Device) and machines (M2M – Machine to Machine), personal data can also be exchanged. Data breaches in the company’s own production facility or at third-party providers could make this data accessible to attackers and endanger data protection with regard to PII (Personal Identifiable Information). Furthermore, there are fundamentally new attack surfaces and weak points from networking via IoT. These two topics require appropriate government regulations and also new cybersecurity technologies.

Training of the workforce

Operating a conventional machine requires different skills than operating a conventional machine connected to a computer. Managing traditional industrial production is different from managing data-driven, automated production. Industry 4.0 brings new technologies and functions that require a change in the mindset of employees and other skills. For this reason, companies have to train their employees and also ensure a new corporate culture. This takes time, effort and resources.

Dependence on technology

Industry 4.0 technologies can “free” older processes, but companies are still restricted by existing technologies and their operating personnel. For example, networked devices and machines require IT teams in the factories. Companies have to analyze large amounts of data and are therefore dependent on AI algorithms and computer scientists. While Industry 4.0 is gradually gaining ground, many of these technologies are still in development. Therefore, not all challenges of today’s modern factory can be answered by Industry 4.0.


The connection of different systems and machines to a common business process requires standardization and technologies that are not always available.

An entry into Industry 4.0

Switching to Industry 4.0 is not always easy. In the beginning, an initial investment is always required and you have to find the right technological solutions for yourself. Employees have to be trained and given confidence in the process of collecting and evaluating data.
A simple way to get started with Industry 4.0 is to implement a universal, non-invasive technology.
3d Signals offers an IoT solution that can be set up easily and non-invasively on your machines (without interfering with the machines). You can use it to collect data and gain usable insights immediately. Increase the availability and productivity of your machines right from the start. View data from your machines in real-time, optimize your production processes and increase productivity.

Six major themes in industrial automation

With the buzz around Smart Industry, the industrial automation market is focusing on themes such as cybersecurity, big data and connectivity. Mechatronics&Machinebouw discusses the most important trends with experts from B&R and Rockwell.

Digital engineering

Digital engineering
Digital engineering

One of the key trends in industrial automation is digital engineering. OEMs, end-users, and system integrators are all looking for tools that enable them to pre-engineer and test in a fully virtual world. Of course, there have been plenty of mechanical and electrical design packages on the market for years, but the industry is ready for the next step. ‘These mechanical and electrical CAD tools produce all kinds of beautiful models. Developers now want to merge them into one platform,” says Patrick Blommaert, business manager Architecture & Software at Rockwell Automation. ‘From the combined data, they can generate a prototype of the machine, a 3D model or even a digital twin, with which they can easily show how the design is progressing and where it is going. With the ever-growing computing power, these models are becoming more and more realistic. That simplifies the consultation with the client considerably.

End customers increasingly need data so that they can better optimize their processes.
Connecting tools from different suppliers together seems an impossible task, especially because the packages come from other worlds and therefore speak a completely different language. But according to Blommaert, things are going very well these days. ‘There are standards for data exchange between all those systems. For example, you can make a direct link between Eplan’s electrical models and Rockwell’s 3D simulation tools. And you can link the data from Matlab to that. Those export and import functionalities work excellently.’

Simple software development

Simple software development
Simple software development

Bas Michielsen, sales manager for the Netherlands at B&R Industrial Automation, sees a change in software development for automation. ‘The IEC standard for PLC programming languages ​​has been around since the 1990s. Since then, the development method has hardly changed. However you control PLCs, via Structured Text, C++ or G-Code, it’s all relatively old. In the industry, you now see more and more companies that offer functionalities in pre-programmed software blocks. Think of recipe processing, motion or safety. These are things that come back with every new machine. In B&R’s Mapp technology, those functions are contained in building blocks that you mainly need to configure. The days of code knocking are largely over.’
With hardware programming becoming easier and easier, there’s more time for the heart of the matter. ‘The focus can increasingly shift to how to implement the most important functionality of the machine as efficiently and quickly as possible,’ says Michielsen. ‘More and more software platforms are available on which you can simulate extensively. Because you can do the different development processes in parallel, the available design time for software designers is stretched a long way. In theory, the software can be ready before the hardware is physically delivered. That is of course very interesting in mechanical engineering.’

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Image It is now possible to combine data from mechanical and electrical design tools. Those export and import options work fine. Image: Rockwell
The next step is fully automatic code generation, Michielsen thinks. ‘To some extent, this is already possible with Matlab/Simulink, for example. You put your model in such a system, press a button and your software rolls out automatically. That also works for PLC controls.’

In the cloud

In industrial systems today there are many levels where you can perform tasks: on the controller, on an edge device, in the factory or in the cloud. ‘Of course, there are tasks that you want to keep close to the controller. You really don’t put the controller’s CPU in the cloud’, says Blommaert. ‘But that would be possible in an edge device. You can also filter data there. It is the first layer where you can run advanced process control or other optimizations with artificial intelligence. At the factory level, you can install an IoT platform that takes advantage of the massive computing power in the cloud. In that layer, you can give more people in your organization access to the data, so that you can not only analyze the data from one factory but also compare different sites.’
It gets complicated when there are systems in a factory without an Ethernet connection. ‘I still see regularly – especially at older factories – that data is recorded on paper and later copied into a spreadsheet,’ says Michielsen. ‘On the basis of that input, try to implement an efficiency improvement. B&R has a solution for this so that you can still connect older machines to the internet and read the data. This way you can still optimize any factory – brownfield, greenfield or a mix. And then it may suddenly turn out that the old factory does indeed need to be replaced because the performance really lags behind.’

Call for data

The term has been coined: the internet of things. ‘End customers increasingly want to be fed with data,’ observes Michielsen. ‘On the basis of that, you can come up with all kinds of great algorithms to achieve efficiency gains in your process. Ideally, you have a self-learning factory that automatically optimizes production lines. We’re not there yet, of course, but technology is growing in that direction.’
The difficulty is that it is often not entirely clear exactly what data such an end customer needs. ‘Does he want to increase the overall equipment effectiveness of his machinery, is it about the quality of his end product or is it all about productivity?’, Michielsen sums up. ‘In all cases, the requirement is that the machine must generate more data. Everyone is saying that their machines must be ready for Industry 4.0, but it is much more important to first have a clear idea of ​​what exactly is needed. That is why we often sit down with the machine builder and the end customer to get everything up and running.’

Cyber ​​Security

What are the biggest challenges in the industrial automation market? ‘Not in the field of technology’, answers Blommaert. ‘Good controllers have been around for years. Of course, they could be even faster, but I see sufficient progress there. The ultimate goal of much automation is to get all the information through all ranks of the organization as quickly as possible. That means that you link all kinds of things together, that it and to converge. And then cybersecurity is a risk.’
Michielsen: ‘We notice that end customers, in particular, are very careful about connecting their machines to the internet. There is still a lot of fear that factories will be hacked. In part that is right. After all, it happens regularly that the most advanced banks and tech companies fall victim to cybercriminals. OEMs often tell us that their customers simply don’t accept plugging an Ethernet cable into the machines. As a result, they cannot save on service via remote support.’

Cyber ​​Security
Cyber ​​Security

There is still a lot of fear among plant managers that their factories will be hacked. They are therefore very careful about pinning their machine to the internet.
No one can give a 100 per cent guarantee against hackers. After all, professional cybercriminals will always find a back door, no matter how strict the security is. ‘But if you build it up in a good way, you can considerably limit the risks,’ says Blommaert. ‘You have to be aware that the risk is never completely gone, but with the right steps and the right tools, you can go a long way. You often see the strategy of working in the field with as few PCs as possible. You then put everything in an IT centre and work with zero or thin clients. This way you can distribute the content to different users and you only have one point that you have to secure properly.’
Michielsen: ‘At B&R we have a solution to gain safe access to a machine anywhere in the world. We do this via encrypted VPN tunnels that are extra secured with certificates. This is often a complex matter that usually lies outside the scope of our discussion partners. IT technology is a completely different sport than PLC control or the control of machines. We often take our IT specialists with us to the customer to explain everything properly.’

Staff shortage

Another tricky issue is the labour market. ‘That is a real concern,’ says Michielsen. ‘The industry is growing fast and to achieve all this, we need a lot of people. Unfortunately, there is a shortage of technicians. We all have to show what great jobs there are in automation.’
Part of the solution is to make the tools more intuitive. ‘That way more people can use them’, explains Blommaert. ‘Think of augmented reality. An operator scans a tag with his tablet and gets a wealth of information back, exactly when he needs it and projected at the right locations. He can also receive real-time feedback during a complicated step-by-step plan that he has to go through. It has really become a collaboration tool.

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