The Drivers of Manufacturing Industry 4.0

by Josh Hamlin

Since the dawn of industrialization, advances in technology have led to multiple industrial revolutions. The term Industry 4.0 refers to the 4th revolution that is upon us. During these past 2 centuries, mankind has witnessed three major revolutions that enabled them to advance the way no one could have ever imagined. The advent of steam engines, water power, and mechanization marked the first industrial revolution which occurred towards the end of the 17th century. The second revolution was brought on by the creation of assembly lines, almost a century ago. The third, taking place in the 1970s, involved the inclusion of computers and automation in many manufacturing processes. The 4th industrial revolution stems from this amalgamation of computers and industry. The name ‘Industry 4.0’ was first presented in 2011 at the Hannover fair and from that point onwards Industry 4.0 has turned into the focal point of consideration of the public authority in Germany and across numerous different nations.

The vision behind all this is to modernize and modularize manufacturing systems in such a way that products can control their own manufacturing processes. It defines a new level of organization in the overall life cycle of products and moving towards production specific to customer requirements. The main objective behind this revolution is to fulfill individual customer needs, which involves areas like order management, research and development, manufacturing, delivery and utilization, and recycling of materials. The fundamental difference between Industry 4.0 and previous advancements is the consideration of the role of humans in the production process. It promotes the idea of connecting physical devices like sensors to each other and to the internet. Currently, many researches are being performed and prototypes created, aiming to convert regular machines to self-learning and self-aware machines. This would lead to the creation of an industrial platform where machines interact with themselves as well as the products being manufactured.

The four main pillars of Industry 4.0 are Internet of things (IoT), Industrial Internet of things (IIoT), Cloud computing, and smart manufacturing which has digitized the manufacturing process.

The collection and evaluation of data on a large scale refers to Big Data. This data is collected from many different sources including production equipment and systems, enterprise, and customer care systems. This data then becomes the basis for the implementation of real-time decision making. Forrester defines Big Data as having four dimensions: Data volume, variety of data, data value, and the rate at which data is generated and analyzed. Analysis of data recovered from previous production methods can reveal threats and can be used to prevent accidents in the future. This influx of large amounts of data has enabled robots to become more autonomous, agile and easy to work with day by day. Researchers believe that at this rate it is certain that robots will one day interact with each other, and work alongside humans and learn from them. These intelligent and autonomous robots are used to perform methods that require unmatched precision and a limited amount of time.

Simulations are slowly being integrated into manufacturing plants. This helps convert real-time data from the physical world into a virtual model, which includes machines, products and humans thereby reducing the risk and extra cost during the experimentation stages. These virtual models are either 2D or 3D and can be used to assess cycle times, energy consumption and any irregularities in the procedures. They are also able to improve the decision making quality by working out easy and fast solutions using simulations.

The internet of things (IoT), comprises a worldwide network of interconnected objects that are addressed uniformly and communicate with each other via different protocols. This includes Internets of Service, Manufacturing services and people. Furthermore, it goes on to Integration of Information and Communication Technology (IICT) and embedded systems. The highlighting features of IoT are context, omnipresence, and optimization. Context refers to interaction between objects and the environment and responding immediately to any changes recorded, also known as context-aware. Omnipresence helps provide information regarding different locations and physical and atmospheric conditions of an object. Optimization refers to improvement and refinement of methods by integrating physical objects, human factors, autonomous machines, and smart sensors all across the factories of the future.

The increasing connectivity over the internet across these integrated systems, have also increased cyber threats dramatically. This makes the use of secure communication lines and controlled access to machinery very essential. Cyber Physical Systems are defined as systems with closely integrated natural and man-made systems with computation, communication, and control systems. CPS with proper sensors and other methods to acquire data can help recognize faults in machinery well before time, and preparations for fault repairs are automatically initiated. These systems also find the optimal utilization times of machines and other stations across the industry floor. Thus, it is very important for these systems to be well-protected against foreign access and decentralized, making any information provided by these systems credible.

Cloud computing is a fairly new concept encompassing advancements in hardware, virtualization, distributed computing, and service delivery over the internet. It aims to provide users and manufacturers with cloud-based computing power and different software applications all over the internet.

Augmented reality (AR) is currently being considered a highly promising technology with huge prospects for the future of industries. It allows viewing computer graphics in real life environments. It is mostly used in description, planning, and monitoring operations in real-time, diagnosing faults and recovery, and to provide training about industrial products and processes. Reports suggest that many manufacturers have implemented AR based systems to train their employees, quality management and product design among other implementations.

Additive manufacturing is the manufacturing technique in which different objects are constructed by melting thin layers onto other materials. This is usually done by melting thin layers of powder and adding one layer of material, plastic or metal, on top of another. This requires planning and highly sophisticated designs created using Computer-Aided Design (CAD) modules. 3D printing technology enables manufacturers to create miniature prototypes to study the designs. This ultimately speeds up the design and manufacturing process and the product ends up with little to no faults. The integration of additive manufacturing techniques has also enabled manufacturers to tend to the individual needs and requirements of each customer.

Manufacturing industry is widely adopting the Industry 4.0 features. Automated processes using artificial intelligence alongside machine sensors are being integrated into various manufacturing processes. Cold forging is a well known forming process under continuous development. It is employed to produce products with high levels of complexity. The products of cold forging have high tolerances and surface finish to a lack of expanding materials. Robotic installations in cold forging processes have been introduced recently at various facilities. These robots are flexible enough to handle the complete process. Also, simulations to study and improve crack propagation in forging dies are also an important advancement in manufacturing industries.

Industry 4.0 has enabled manufacturers to use smart, efficient, effective, and customized methods of production at reasonable costs. With the integration of faster computers, complex sensors and cheaper ways to store and transmit data, machines, and products are now smarter and are able to communicate, work with, and learn from each other. It also aims to provide for manufactures and end users in a sustainable way that protects the environment as well as tends to the customers’ specific needs.    

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