EMERGING INDUSTRY 4.0 TECHNOLOGIES WITH REAL-WORLD EXAMPLES

 

What Is Industry 4.0 Technology?

Industry 4.0 which is often referred to by the name of Fourth Industrial Revolution, is focused on making business more efficient and more efficient. While prior to the Third Industrial Revolution focused on changing analog and mechanical methods to computer-controlled ones this Fourth Industrial Revolution focuses on expanding the reach of digital technology through making machines autonomous and able to “talk” to one another and analyze enormous quantities of information in ways humans cannot, all to achieve productivity and expansion. Industry 4.0 technology is a major change in how businesses run that is as important as the shift of steam-powered power into electric power in the Second Industrial Revolution.

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How is Industry 4.0 Technology Impacting the Manufacturing Industry?

In the manufacturing industry In the manufacturing industry, Industry 4.0 has wide-ranging implications. It’s used to boost efficiency in operations, enhance demand forecasting, eliminate data silos, implement predictive maintenance, provide workers a boost in safety, Virtual training. And much more. Industry 4.0 is part of a bigger concept called digital transformation encompasses manufacturing from planning to delivery using solutions for deep analytics including sensors for data on the floor smart warehouses, simulation of changes as well as asset and product tracking.

For manufacturing companies For manufacturers, Industry 4.0 technologies can help connect the processes that used to be separate to provide a more transparent and visual view of the whole enterprise, providing plenty of practical data.

10 real-world industry 4.0 Technologies and Examples

Here are the most popular digital transformation techniques brought through Industry 4.0. You can choose any one of them and jump to a specific section:

Big Data & Analytics

Autonomous Robots

Simulation/Digital Twins

Horizontal and Vertical Systems

Industrial IoT (IIoT)

Cyber-security Technology

The Cloud

Additive Manufacturing

Artificial Intelligence

Augmented Reality

Big Data & Analytics

Big Data is exactly what it is – massive quantities of data. The mountains of numbers and stats that are so massive that human beings and teams could be able to spend years searching through it manually, but not gain any real value. When machines are in the driving seat, it’s an entirely different scenario. Utilizing today’s modern computing capabilities, these massive streams of unadulterated, pure information can be transformed into precise, actionable information that drive decisions for manufacturers’ leaders. Data sources include everything from IoT sensors in factories and lighting systems, to sales data and supply chain variables like weather or the political climate.

Big data is the foundation of the other technologies of Industry 4.0. The more data that is utilized and the more effective it is, the better the level of efficiency.

Example of Big Data & Analytics in Manufacturing

Imagine this: A factory floor somewhere in Wisconsin with a small sensor (an industrial IoT sensor, which we’ll discuss in more detail later) connected to each machine in that factory. This sensor is always recording and analyzing data both on the sensor’s site and within the Cloud (which we’ll also discuss). The information from this small IoT sensor, as well as information about how frequently the machine is utilized, is gathered and processed by a machine learning algorithm.

The algorithm, also known as a formula, generates results about that machine’s maintenance schedule. It states, “This machine’s belt is likely to break in 2-3 weeks.” With this thought in mind, the maintenance should be scheduled for off times throughout the week, and the machine is able to function at all times of the day. It’s known as “predictive maintenance” and it would not be able to function without the use of big data. Big data can help this factory to take care of its assets, cut expenses, and reduce the possibility that downtime can cause.

Autonomous Robots

Autonomous robots are self-sufficient devices capable of managing their work effectively without the need of humans to operate them. They can quickly and efficiently complete routine tasks, even when they’re complicated, needing minimal or any downtime, excluding maintenance.

Example of Autonomous Robots in Manufacturing

Autonomous robots are utilized in manufacturing to support and move large items in a line of production. This prevents human injuries from welding and assembly as well as palletization. Autonomous robots also aid in order picking at the level of the warehouse because they are able to quickly assess and select the most efficient way to pick the items even when there are several orders. They are also able to be utilized to produce continuously, since they do not require breaks.

Simulation / Digital Twins

Digital twins, even though they may be appearing to be something straight from a sci-fi film it is actually the real technology behind the creation of a real-world object concept, or an area in an electronic space. It could include a 3D representation of all physical assets, operational systems , and structures in the entire facility. The possibilities for using digital twin systems are extremely vast.

Example of Simulation / Digital Twins in Manufacturing

With the help of industrial IoT sensors manufacturers is able to “see” their entire shop floor from a virtual perspective. They can see the exact location of each asset, their uptime and maintenance requirements (even those that haven’t yet been identified). They are able to even look inside machines that would be risky or expensive to access in real-world situations.

With this digital twin and machine learning, manufacturers can anticipate maintenance tasks and pinpoint the optimal times to make use of the equipment in order to minimize bottlenecks. Employees can be trained at the distance of a safe distance prior to introduction to non-simulated machines in the floor and evaluate concepts for changes to operations prior to spending time, money and effort to implement the ideas.

Horizontal and Vertical System Integration

Vertical and horizontal integration is often referred to as”the “backbone of Industry 4.0.” The basic idea behind vertical and horizontal system integration is connection and transparency. This can be within an organization, or externally working with partners from industry. Companies and machines are always communicating and sharing information which allows for greater analysis possibilities, more transparency, and improved efficiency for everyone.

Example of Horizontal and Vertical System Integration in Manufacturing

If a business has multiple manufacturing factories, horizontal integration is a way to provide seamless communication about information issues like delays and inventory levels. Vertical integration in manufacturing could involve breaking down the silos of interdepartmental departments in order to work together, from R&D through procurement manufacturing, to sales, and on and on. Everyone is sharing data Everyone benefits, and everyone is operating in a dynamic manner.

Industrial IoT (IIot)

Industrial IoT refers to the use of small sensors, often equipped with computers, that track and collect information in real-time across businesses. IoT sensors are able to be placed together with virtually anything from lighting to HVAC (Heating and ventilation), air-conditioning) to factory floor equipment. Industrial IoT is the underlying technology in Industry 4.0. The advantages associated with connected machines are immense because it gives information that can be used to make better decisions at all levels of an organization.

Example of Industrial IoT (IIoT) in Manufacturing

We’ve discussed the function that Industrial IoT in predictive maintenance. Another instance of IIoT in manufacturing is cutting down bottlenecks, resulting in huge increases in production.. If every machine on the production floor is equipped with an IoT device that is connected to it, which monitors the efficiency of production, utilization and uptime. The data could be used to aid an algorithm for machine learning. This will determine the machine that has the most important bottleneck and what steps to take to correct it. Do the machines require an upgrade? Do you think it is just a matter of needing to be used at a greater number of hours of the day?

Cybersecurity Technology

There is no way to have a lot of technology in each aspect of your business without having some form of protection put in place to prevent criminals and other evil agents from your systems. Cybersecurity technology safeguards your systems against threats from external and internal sources. Modern cybersecurity includes technologies such as blockchain and artificial intelligence that can defend modern technologies like industrial IoT devices.

Example of Cybersecurity Technology in Manufacturing

With digital, smart technology, businesses with inadequate security measures are vulnerable to the risk of theft of intellectual property, manufacturing equipment manipulated by saboteurs who create defective products including identity theft, ransomware and much more. But, they can reduce security risks by preparing plans in the event that they suffer a security breach, and can also put in place security measures to protect their equipment and data, including their IoT systems.

The Cloud

“The Cloud is a term that is not well-defined that refers to a wide range of connected systems that are on the internet. In general, it refers to an offsite server that is not connected to your company. “Cloud” refers to a server that is offsite from your business “Cloud” can be used for data and software stored online (e.g. the server of someone else) instead of being stored locally on a machine.

Example of The Cloud in Manufacturing

The Cloud provides a variety of advantages to manufacturers. It can store large amounts of sensor data safely with redundant backups built in. It is safe to hold customer information. It can also be used to compute. Computationally-intensive tasks such as risk modelling using machine learning can be done on the Cloud to reduce overhead costs for high-powered machinery. Recently it’s also been utilized for “cloud manufacturing” which can be used to refer to software or actual distributed manufacturing that spans multiple geographical areas.

Additive Manufacturing

Additive manufacturing is the process of creating products layer by layer, incorporating new materials instead of subtracting it. This is different from the previous method to manufacture (subtractive manufacturing) which includes tasks such as the cutting, carving and shaping of wood and so on.

Example of Additive Manufacturing in the Manufacturing Industry

3D printing is a type in additive production. The most popular adopters are Adidas who 3D print shoes and the patterns of which were based on massive data.

Artificial Intelligence and Machine Learning

Machine learning and artificial intelligence are machines that use algorithmic processes to analyze data and come up with conclusions that are not created by humans who developed them. Machines learn from data to create more accurate predictions.

Example of Artificial Intelligence in Manufacturing

Machine learning and artificial intelligence are used extensively in manufacturing to forecast demand as well as predictive maintenance. Because AI can analyze vast amounts of data gathered from sensors and other sources, it’s an ideal tool to predict complicated, volatile, and unpredictable situations in close to the moment in a way that humans are unable to. AI is able to anticipate and predict market trends for companies.

Augmented Reality

Augmented reality can be described as a sensory input, typically visual, that overlays onto the real world. Examples include Google Glass and the game Pokemon Go.

Example of Augmented Reality in Manufacturing

In the manufacturing industry, augmented reality can be utilized for worker training as well as maintenance. The new employees will be taught how to operate equipment that can be hazardous in a secure, virtual setting prior to going into manufacturing floor. AR is also beneficial in maintenance tasks, by providing tools, repair manuals, as well as other information that is immediately visible in the technician’s vision. Augmented reality can also allow technicians to look inside difficult and dangerous machinery before opening it to ensure they know what they’re looking at and what they should do prior to when they begin.

Brisklogic accelerates digital transformations in factories by offering an easy-to-use and flexible IoT platform that allows you to gather and transform data from any manufacturing equipment into highly effective practical applications.