Industry 4.0

Industry 4.0

Industry 4.0  is a vision that evolved from an initiative to make the German manufacturing industry more competitive.  Industry 4.0 is being presented as an overall change by digitalization and automation of every part of the company, as well as the manufacturing process. This goal becomes possible by introducing self-optimization, self-cognition, and self-customization into the industry. 

From practical point of view Industry 4.0 enables the manufacturing sector to become digitalized with built-in sensing devices virtually in all manufacturing components, products and equipment. The analyzing of related data within a ubiquitous system with the fusion of digital data and physical objects has the ability to transform every industrial sector evolve much faster and with greater impact than previous industrial approaches. Easy exchange of information and the integrated control of manufacturing products and machines acting simultaneously and smartly in interoperability, results in significant increase in the efficiency and decrease of the production cost.

Components of Industry 4.0:

horizontal integration: It brings the concept of a new type of worldwide value chain networks. 

vertical integration: The concept is to achieve hierarchical subsystems at the production line to produce an easy to configure and high flexibility production line. 

Engineering integration: This concept acts  along the whole value chain from the beginning to the end to assist in the customization of products. 

Generally nine characteristics for industry 4.0 are defined including:

Cyber-Physical System (CPS) : Each production system of CPS has sensors installed in the entire physical aspects in order to connect the physical things with virtual models. 

Internet of things (IoT): IoT can provide advanced connectivity of systems, services, physical objects, enables object-to-object communication and data sharing. IoT can be achieved through the control and automation of aspects like heating, lighting, machining and remote monitoring in various industries 

Internet of Services (IoS) : The Internet of Services (IoS) acts as “service vendors” to provide services through the internet according to the types of digitalization services. 

Big Data and Analytics: Huge amounts of information produced and obtained daily where current processing and analysis is unable to cope using traditional methods. Big data and analytics is beneficial for predictive manufacturing and is an important direction for industrial technology development through the rapid development of the Internet. 

Augmented Reality: This technology can bring huge support for maintenance works in business by utilizing predictive maintenance to prevent any unplanned reactive maintenance. This will reduce time and the potential errors in maintenance works , thus, costs associated with doing too much preventive maintenance is reduced.

Autonomous Robots 

Highly flexible robots with capabilities to interact with each other and collaborate actively with humans under the guidance of handlers is a characteristic of Industry 4.0.

Additive Manufacturing (3D Printing) : The implementation of new manufacturing skills for the purpose of integrating information technologies plays a crucial role in the competitiveness of the economy. Need for high quality parts with complex geometry through completely automated manufacturing techniques is only achievable through adopting the additive manufacturing approach.

Cloud Computing: Cloud computing is a relatively new system logic that provides a huge space of storage for the user. The functionality of machine data will be stored into the cloud storage system, allowing production systems to be more data-driven. 

Simulation: Simulation modelling is a way of running a real or virtual process or a system to find out or guess the output of the modelled system or process using real-time data to represent the real world in a simulation model. Therefore, operators are able to optimize the machine settings in a virtual simulated situation before implementing in the physical world. Advanced artificial intelligence (cognitive) on process control, including autonomous adjustments to the operation systems (self- organization) can also be done through simulations.