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.
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.
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 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 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.
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
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.