What are the Industry 4.0 Technologies? Part 2 with Real Examples

8. Analytics and Big Data

In terms of data, it is important to use data analytics to convert data into information that provides actionable insights. Data visualization and machine learning models can help processes for data analysis. In general, machine learning techniques use powerful computational algorithms to process large-scale sets of information, whereas data viewing tools allow producers to understand the story that the data tells more easily. And then, companies can now find new ways to optimize the processes that affect their performance by taking previously isolated data sets, collecting and analyzing them.

Big Data refers to large and complex IoT device data sets. This information comes from a vast array of cloud and business apps, websites, computers, sensors, cameras, and much more—all in different formats and in different protocols. Data from production equipment equipped with MES, CRM, and ERP sensors and bases are many different types of data to take into account in the manufacturing industry. But how can manufacturers turn collected data into practical insights and tangible advantages? Through data Analysis.

9. Advanced Robotics (Technologies of Industry 4.0)

Throughout decades of uses of robotics, this technology rekindles by Industry 4.0. A new generation of advanced robotics is emerging with recent advances in technology that can perform difficult and sensitive tasks. They can recognize, analyze and act on the information that they receive from the environment, collaborate, and even learn from humans, using state-of-the-art software and sensors. Collaborative robot systems (“cobots”), designed to work safely around people and free workers from repetitive and dangerous tasks, are an important field of robotics.

An example is the collaborative Autonomous Mobile Robots (AMRs) that Fetch Robotics, based in California, has developed to find, track, and move inventories in warehouses and logistic facilities. Fetch AMRs are used for pick-up and placement by DHL in the Netherlands. At DHL, AMRs travel around the facility autonomously alongside the employees to learn and share the most efficient routes. This allows self-driving robots to reduce order cycle time by up to 50 percent and to achieve a productivity gain of up to twice, according to the company. As robots become autonomous, flexible, and cooperative, they are in a position to handle even more complex tasks, relieve employees of one-off tasks, and increase factory productivity.

10. Additive Manufacturing

One of the Technologies of Industry 4.0 is alongside robotics and intelligent systems, additive manufacturing, or 3D printing. Additional manufacturing works through the use of digital 3D models to produce parts that are layer by layer with a 3D printer. 3D printing is a valuable digital production technology in the context of Industry 4.0. AM offers today a wide range of manufacturing possibilities. From tooling to mass customization, in virtually every industry once just a fast prototyping technology. It enables components to be stored in virtual stocks as design files. So they can be produced on request and closer to the need — a model known as distributed production. Such a decentralized manufacturing approach can reduce transport distances. And thus costs and simplify inventory management through the stowage of digital files instead of physical parts.

Many examples are applied, but a fast radius can be an example. One of the nine best smart factories in the world was named by the World Economic Forum in 2018, the Chicago Fast Radius Facility. The contract producer focuses in Chicago, Singapore as well as at UPS Worldport on AM and also offers CNC-making and injection molding. This makes Fast Radius well positioned, with advanced manufacturing technology, to enhance the vision of fast-turning and solid product personalization. The proprietary technology platform is a key factor behind the agility and flexibility of Fast Radius.

The platform is capable of collecting information and information from any part design stored and produced in the Fast Radius virtual warehouse. The data helps teams to identify 3D printing applications and thus to assess the engineering challenges and economic challenges of manufacturing a component. In addition, through its virtual inventory, the company offers supply chain optimization. For example, for a heavy equipment manufacturer, Fast Radius created a virtual parts warehouse of 3,000 items. This approach is an innovative solution for the supply chain management with the high costs involved in the storage of rarely ordered parts.

11. Digital Twins

The digital double concept holds great promise for the optimization of industrial system performance and maintenance. Gartner, the global research firm, predicts that 50% of large industrial firms will use digital twins to monitor the assets and processes of these companies by 2021. A Digital Twin represents a digital representation that enables companies to understand, analyze, and optimize their processes better in real-time simulation. a real-world product, machine, process, or system.

Although digital twins can be confused with engineering simulation, much more is needed. A digital twin runs an online simulation based on data from sensors connected to a machine and other devices, unlike engineering simulation. When an IIoT device sends data in almost real-time, a digital twin can continually collect this data, keeping its reliability with the original throughout the product or system’s lifetime.

This allows the digital twin to predict possible problems in order to take preventative measures. For instance, a digital double operator can determine why a part works wrong or how long a product is running. This continuous stimulation contributes to improved product design and the operation of equipment. Digital twins have been a very important tool in aerospace, heavy machinery, and automotive applications for many years. The concept of digital twinning now extends in other industries by advances in computer science, machine learning, and sensors.

An Example:

Motor racing teams face extremely difficult product development demands, and Team Penske is no exception. US professional racing team is no exception. Team Penske partnered with Siemens last year to help speed up the race car development process by gaining access to sophisticated digital design and simulation solutions including digital twins.

Team Penske offers digital twins a virtual testbed for new parts to maximize performance of automotive before physical car ever comes into contact. A twin digital racecar relies on a real car sensor. The sensors collect data like pneumatic pressure, motor control, and wind speed and then convert to a virtual automotive model. This model enables engineers to check various design configurations and to make very rapid in design-driven by data.

This means for Team Penske that testing process is cheaper and more resource-efficient, and hopefully, an opportunity for quicker vehicles to develop.

12. Augmented reality

Despite the use of the technology in consumers’ applications. The manufacturing industry is just beginning to explore the benefits of increasing reality (AR). But, from montages to maintenance of production equipment, the technology has enormous underspent potential. Increased reality bridges the gap between digital and physical worlds by overlaying a virtual image or data physical object. For this purpose, the technology uses AR-enabled devices like smartphones, tablets, and smart lenses.

Take an example of a medical case –

A surgeon using AR glasses during surgery. The glasses could overlay and highlight color data from MRI and CT scans, like nerves, large blood vessels, and ducts. It helps the surgeon to find safest way to area, to minimize risk of complications, and to improve surgeon accuracy.

AR may enable workers to accelerate the assembly process and increase decision making in the field of manufacturing. AR glasses could, for instance, use for projects of real-world data. Such as layouts, assembly guidelines, locations with potential malfunctions, or a number of components, making work more easy and speedy.

Example: General Electric provides a picture of how production is possible with AR technology. The company now manages the use of AR glasses at its jet engine production plant in Cincinnati. Jet engine manufacturers often had to stop what they were doing before using these intelligent glazes to check their manuals and ensure that the work was done correctly.

With AR glasses, however, they can now get digital viewing instructions. They also can use voice commands to contact experts for immediate support or access training videos.

During the pilot, GE reports that workers using intelligent wearables have increased their productivity by up to 11 percent when compared with before. This approach could ultimately provide a tremendous potential to minimize errors, reduce costs and improve the quality of the product. Even with that example from GE, when it comes to AR implementation in production, we are still scratching the surface.

Riding the Wave of Digital Manufacturing

Manufacturing is now a thrilling time with the emergence of new digital technologies. The new technology wave offers companies the chance to increase flexibility, sustainability, and productivity. Industry 4.0 also provides people and machines with new ways of working together. Allowing enterprises to get more insight, reduce the risk of error and make better choices. Industry 4.0 will ultimately take root in the entire production ecosystem. But manufacturers will only stay at cutting edge of new digital era by understanding and harnessing driving Industry 4.0.

Practical examples of Industry 4.0

1.Construction

Meet Semi-Automated Mason or SAM, a robot that can take over the building industry very well on construction walls. The brick-filling robot, which was created in New York by Construction Robotics. It is supposed to maximize productivity while reducing total costs for labor.

Although building site productivity has stagnated over the past 20 to 30 years, automation and innovations have vastly improved manufacturing efficiency. SAM was developed to solve this problem by construction robotics. SAM needs a human companion to operate seamlessly but the bot is left to heavy elevation. At least three times as fast as human beings will be set up by the robot — which will never tire of or be incorrect.

2. Manufacturing

With the intelligent plant, Audi makes the production-ready for the future. Big technology –development and smart connection of vast quantities of data. In this factory of the future would make output data-driven, and therefore incredibly scalable and highly effective. The modulated assembly according to an entirely new, disruptive idea is a manufacturing process. In which Audi is no longer able to build its vehicles on an assembly line. Audi is undertaking many other interesting ventures, from application of augmented reality glasses to printing of metal 3D, as well as big project.

3. Public Transportation

Since, in 2008, the financial crisis struck the world. The word smart city has been seriously affected and a hit in recent years. A sustainable urban model and protecting quality of life of the people are key considerations in adoptive Smart City plan. Numerous economic, humanitarian, and legal elements must include in the smart city problem, not just as a technological discipline. The IoT architecture is used to develop so-called smart computers under Industry 4.0.

The commodity subcomponents have an intellect of their own. Adding information uses both during manufacture and subsequent processing of a product and for ongoing surveillance of product lifecycle.

What are the Connections Between Industry 4.0 and Lean Manufacturing

Lean production in the manufacturing world is generally understood and embraced. It is about strict human inclusion in the development chain and constantly enhances it and concentrates on adding value by waste management practices. However, the industrial sector recently established a new model dubbed Industry 4.0, or the fourth industry transition. It enables the development in the entire supply chain of an intelligent factory of an intelligent network of devices, goods, parts, characteristics, individuals, and ICT systems.

Their Main Connection With Industry 4.0: Operational Excellence

Manufacturers have been using lean concepts and tools for many decades to reduce organizational uncertainty and increase efficiency. The lean approach offers the basis for organizational success through standardization of procedures, a philosophy of quality development, and the empowerment of the staff on the field. Given the ever more dynamic activities, however, several businesses have realized that lean management alone does not solve their organizational problems.

Recently, a range of integrated digital technology called Industry 4.0 has evolved to include new approaches to complexity and efficiency enhancement. The right blend of Technologies of Industry 4.0 helps factories to improve speed, productivity, and teamwork and also encourage factory self-management. Both methods have the same purpose, namely organizational excellent results.