With the 3rd industrial revolution, businesses started making use of Information Technology extensively. In the recent years, data has become a driving force for businesses that offer deeper insights and reduces risks. It's time now for the 4th industrial revolution.
Industry 4.0 introduces the Internet, Artificial Intelligence and other emerging technologies to industrial manufacturing. It takes factory automation, which is already accomplished, to another level. Industry 4.0 aims to add the Intelligence factor to Industrial Manufacturing, making industries more safe, autonomous and productive. It uses Big Data Analytics to come up with predictions for the machines to take decisions and act accordingly on their own. This lets the businesses employ its human resources where emotional, creative, and analytical thinking matters more.
The term Industry 4.0 was coined in 2011, at the Hannover Fair. In 2012, a working group on Industry 4.0 laid down a set of deployment endorsements to the German Federal Government. This working group is considered as the founders and driving force behind Industry 4.0. In April 2013, the final reports of Industry 4.0 were presented at the Hannover Fair.
The internet has been a major influencer in the current developments happening across the world. Industry 4.0 is also driven by the Internet. Though factories are being influenced by the digital technology, it has so far been at a managerial level. Industry 4.0 intends to bring the digital technology at the operational level and to imbibe the element of intelligence into manufacturing. This will imply the use of robots that can autonomously take decisions and perform optimally under the given conditions. This will also imply seamless flow of real-time information within the organization that is used by the intelligent systems to make such decisions. This will revolutionize industrial manufacturing wherein the manufacturing pattern will assimilate the market information and adjust the levels and quality on its own. There's scope for customized manufacturing with minimal changes in the input which will reduce the risks and costs of manufacturing. There's predictive maintenance which reduces the downtime significantly thereby increasing the productivity.
The term industry 4.0 is a collective term embracing a number of contemporary automation, data exchange and manufacturing technologies, which draws together cyber world and physical systems or machines, the internet of things and internet of services. Industry 4.0 revolution will be driven by an ensemble of evolving technologies such as Big Data Analytics, Artificial Intelligence, IIoT, Advanced Robotics, and Predictive Maintenance. More technologies such as Cloud Computing, Digital Transformation and Additive Manufacturing are also a part of Industry 4.0.
Materials and Manufacturing Processes deals with issues that result in better utilization of raw materials and energy. This conference address issues on traditional topics such as casting, machining, forming and joining to latest topics such as fabrication of nanomaterials. Materials form the basis for vehicles and production processes. The functions of materials optimize component performance, design, convenience and customer safety.
Let's have a detailed look into the technologies that drive Industry 4.0 forward:
Everything is going smart these days. Smartphones have become an essential. Smart devices have become very common. Smart factories will revolutionize manufacturing. Smart factories vouch for customization, personalization, and demand-based manufacturing in a cost-effective way. It uses the latest technologies, thereby optimizing industrial manufacturing, offering what is in demand.
The technologies that add up to making smart factories are the Internet, Big Data Analytics, IoT, 3D Printing, Artificial Intelligence, Advanced Robotics, and Cloud Computing.
When manufacturing meets the internet and digitization, it improves the efficiency and productivity. Cyber-Physical Manufacturing Systems are based on the 5 core principles of configuration, cognition, cyber, conversion and connection. It works by allotting digital twins that works on the cloud assimilating the real-time data from a physical system and offering cognition from the processed information while staying connected over the internet. This ensures better data management.
Surveys reveal that by 2020, connected physical assets will produce more than 44 ZB of data. Cyber-Physical Manufacturing system takes control of the CPS at machine level, fleet level and enterprise level.
Robots are already being used in factories and warehouses. But they are controlled by the humans as of now. When AI starts controlling the robots and they become autonomous, it will change industrial manufacturing.
Autonomous robots help to make the factories a much safer place. When they take over the mundane and redundant jobs, the human resources can be engaged in more creative works that require cognitive thinking. Robots eradicate human errors. Robot has become a feasible option, especially when they can operate alongside humans making manufacturing more efficient, precise and safe.
With IIoT, AI and Cloud Computing, autonomous robots and vehicles offer a much brighter future to industrial manufacturing.
Businesses that leverage data are bound to be successful. Real-time data analytics along with the KPIs offer some serious insights into the business' performance versus time. This information is also used up by AI to make predictions. Machine Learning and AI use the information that's generated and collected by businesses to analyze various patterns for cognitive decision-making. Robotics and smart systems rely largely upon this information.
Real-time analytics help AI and autonomous machines to assimilate the data and make intelligent decisions.
Data in its raw form may not be easy to interpret. The workers and operators who are skilled in machine operations may not be able to make sense of the vast information presented before them as graphs and reports. Virtual and Augmented reality helps visualize this data and make better sense for the end-users of Industrial manufacturing. VR and AR will play an important role in the Industry 4.0 era, offering consumable insights to the users. These technologies can offer visualization of digital instructions to the operators for easy understanding. Personalized training, gamification and simulation training, are possible through VR and AR. Effective training through AR and VR will play a vital role in reducing costs in any environment.
3D modelling and simulations are already quite popular in manufacturing and industrial manufacturing. In Industry 4.0, 3D modelling gains a higher ground with the help of 3D printing. Simulations and gamifications are being widely used for corporate training and in academics. They prepare the end-users or operators for adapting the industrial digital transformation much faster and more efficiently. Simulations train the end-users of the virtual environment. Simulation also supports experimentation in software and generates the data needed to meet experimental objectives.
Additive Manufacturing is a method that builds 3D objects by adding layers, one over the other. RP (Rapid Prototyping), DDM (Direct Digital Manufacturing), additive fabrication, and layered manufacturing are the major technologies used in Additive Manufacturing.
RP is used for visualizing the prototypes. Three-dimensional CAD drawings are printed, layerby-layer using 3D printer. These layers could be same or different materials depending upon the requirements.
Integration is essential to achieve business goals. When it comes to manufacturing and industrial production, horizontal and vertical integration are equally essential. Horizontal integration helps to assimilate the data across the various departments and production units, while vertical integration helps to assimilate what's happening from the operator level to how it is aligned to the organizational goals.
All this information will be stored in a centralized server, in the cloud, which will be available across the organization offering insights and inputs for the integrated systems.
The Internet-of-Things connect smart devices to a central repository which is connected to the internet. IoT offers a vast amount of data to the consumer durables manufacturer, which he uses for understanding user-behavior patterns to improve the product placing and its quality. Industrial IoT offers the manufacturers such critical information about the machine usage, its productivity and downtime. The manufacturers can use this information for analysis and predictive maintenance. It will also help them to remotely operate the machines which makes production safer and more effective.
Artificial Intelligence involves cognitive decision-making. When the computers are able to utilize vast volumes of information to understand the patterns and use them for taking autonomous decisions, they become intelligent. The two commonly used applications of AI are in personalization and recommendation that we see in the websites. In industrial production, AI plays an important role in developing autonomous robots and vehicles.
While AI works primarily on real-time data, distributed intelligence requires both historical and real-time data to take cognitive decisions. Learning on the cloud is increasingly being used by Business Intelligence systems that help the management. With Distributed Intelligence, this learning is done on the manufacturing level.
As everything gets connected to data and the internet, cybersecurity becomes a major challenge for businesses. The hackers are already challenging the cyber world every day with hacking, security breaches, phishing and other data threats. As manufacturing gets digitized, the threat gets larger as many classified combinations or manufacturing secrets will have to be fed into the machines that run autonomously. To avoid data breach, technologies such as blockchain, cloud and cyber-security are helpful.
Blockchain has proven its encryption and privacy features already which is used for cryptocurrency trading and transactions. The fact that they breaching the blockchain security is extremely difficult and near to impossible makes it an essential technology for Industry 4.0. Cloud computing is also extremely secure and lets you share information safely to different stakeholders. Cybersecurity is an ever-growing market since digitization became an industry standard. With industrial digitization, cybersecurity will also evolve exponentially.
Predictive maintenance is when your machines know when they are due for maintenance, in terms of dates as well as wear and tear and then they analyze the situation and request for maintenance autonomously. This reduces the downtime significantly. If the issues with the machines can be identified in the earlier stages, the repair will be much more effective. This can be achieved through IIoT, AI and Cloud Computing.