Since traditional systems are incapable of meeting flexible customer requirements, manufacturing processes must be modularised and assembled for individual processes depending on the situation. This entails the integration of various technologies into a Smart Factory: automation technology, sensors, RFID and information technology.
Integrated Industry or Industry 4.0 is the transformation of today’s factories into Smart Factories, where the orchestration of services represents the definitive solution for fully modularised automation. Production is controlled by components (machines, robots, conveyor systems, loading equipment and products), and in a largely decentralised and autonomous manner. Via sensors, objects detect the state of their surroundings, they can be uniquely identifies, possess built-in object memory and exchange information with other objects. Through the addition of embedded systems, objects become Cyber-Physical systems (CPS). Industry 4.0 facilitates the vision and execution of a Smart Factory, creating a virtual copy of the physical world and make decentralised decisions.
Industry 4.0 or the Fourth Industrial Revolution is a collective term embracing a number of contemporary automation, data exchange and manufacturing technologies. It had been defined as “a collective term for technologies and concepts of value chain organization”, which draws together Cyber-Physical Systems, the Internet of Things and the Internet of Services.
Over the Internet of Things, Cyber-Physical systems communicate and cooperate with each other and with humans in real time, and via the Internet of Services, both internal and cross-organizational, services are offered and utilized by participants of the value chain. All the information in the entire network will become available. Once the product quality does not meet the requirements, the collected data can serve as a clue to find the root-cause.
Industry 4.0 gives us a vision of a more flexible and efficient future. To turn this vision into reality, we need the combined efforts of industry and science. To turn vision into products, we need collaboration between innovative companies from a variety of product areas, all working together to make this implementation a reality.
How are you going to manage this challenge?
There are six design principles in Industry 4.0 which support companies in identifying and implementing Industry 4.0 scenarios:
1. Interoperability: the ability of cyber-physical systems (i.e. workpiece carriers, assembly stations and products), humans and Smart Factories to connect and communicate with each other via the Internet of Things and the Internet of Services
2. Virtualization: a virtual copy of the Smart Factory which is created by linking sensor data (from monitoring physical processes) with virtual plant models and simulation model
3. Decentralization: the ability of cyber-physical systems within Smart Factories to make decisions on their own
4. Real-Time capability: the capability to collect and analyse data and provide the derived insights immediately
5. Service Orientation: offering of service (of cyber-physical systems, humans or Smart Factories) via the Internet of Services
6. Modularity: flexible adaption of Smart Factories to changing requirements by replacing or expanding individual modules
Characteristic for industrial production in an Industry 4.0 environment are the strong customization of products under the conditions of high flexibilised mass-production. The required automation technology is improved by the introduction of methods of self-optimization, self-configuration, self-diagnosis, cognition and intelligent support of workers in their increasingly complex work.
Industry 4.0 has triggered a new industrial revolution or phenomenon. The basic principle of Industry 4.0 is that by connecting machines, work pieces and systems, businesses are creating intelligent networks along the entire value chain that can control each other autonomously.
Some examples for Industry 4.0 are machines which can predict failures and trigger maintenance processes autonomously or self-organized logistics which react to unexpected changes in production, a networked until everything is interlinked with everything else. It means that the complexity of production and supplier networks will grow enormously. Networks and processes have so far been limited to one factory. But in an Industry 4.0 scenario, these boundaries of individual factories will most likely no longer exist. Instead, they will be lifted in order to interconnect multiple factories or even geographical regions.
There are differences between a typical traditional factory and an Industry 4.0 factory. In the current industry environment, providing high-end quality service or product with the least cost is the key to success and industrial factories are trying to achieve as much performance as possible to increase their profit as well as their reputation. In this way, various data sources are available to provide meaningful information about different aspects of the factory. In this stage, the utilization of data for understanding current operating conditions and detecting faults and failures is an important topic to research. E.g. in production, there are various commercial tools available to provide Overall Equipment Effectiveness (OEE) information to factory management in order to highlight the root causes of problems and possible faults in the system. In contrast, in an Industry 4.0 factory, in addition to condition monitoring and fault diagnosis, components and systems are able to gain self-awareness and self-predictiveness, which will provide management with more insight on the status of the factory.
Furthermore, peer-to-peer comparison and fusion of health information from various components provides a precise health prediction in component and system levels and force factory management to trigger required maintenance at the best possible time to reach just-in time maintenance and gain near zero downtime.
Challenges which have been identified include:
• Lack of adequate skill-sets to expedite the march towards fourth industrial revolution
• Threat of redundancy of the corporate IT department
• General reluctance to change by stakeholders
Modern information and communication technologies like Cyber-Physical Systems, Big Data or Cloud Computing will help predict the possibility to increase productivity, quality and flexibility within the manufacturing industry and this to understand advantages within the competition.
Big Data Analytics consist of 6Cs in the integrated Industry 4.0 and Cyber Physical Systems environment: Connection (sensor and networks), Cloud (computing and data on demand), Cyber /model & memory), Content/context (meaning and correlation), Community (sharing & collaboration), and Customization (personalization and value). In this scenario and in order to provide useful insight to the factory management and gain correct content, data has to be processed with advance tools (analytics and algorithms) to generate meaningful information. Considering the presence of visible and invisible issues in an industrial factory, the information generation algorithm has to be capable of detecting and addressing invisible issues such as machine degradation, component wear, etc. in the factory floor.
The fourth industrial revolution will affect many areas. Five key impact areas emerge:
1. Machine safety
2. Industry value chain
3. Workers
4. Socio-economic
5. Industry demonstration: To help industry understand the impact of Industry 4.0
Now, the time has come to transform “Industry 4.0” into a reality inside factories.
Dave Food