2.1 Industry 4.0
The Industry 4.0 is a well-known concept emerged during the Hannover fair in 2011 (Kagermann, H., 2011), originated from a project within the German government’s high-tech strategy focused on the computerisation of manufacturing. The major technical background and challenge (Raj, A., 2020) of Industry 4.0 is the introduction of three main internet technologies – i.e., Internet of Things (IoT), Big data, Cloud computing – into industries in combination with simulation techniques. Big data is a well-known term nowadays, it is used to describe data sets that are so large and complex which are difficult to be analysed using standard statistical software. Therefore, the management and evaluation of comprehensive data from numerous sources and Machine Learning technology, will be an essential part of the Industry 4.0 environment, to support decision-making (Ru¨ßmann, M., 2015). Then, Cloud computing is the essential enabler for data sharing across sites and companies, even across countries. With Industry 4.0, machine data and functionality will increasingly be deployed to the cloud, enabling more data-driven services for production systems. Even systems that monitor and control processes may become cloud based (Ru¨ßmann, M., 2015). Last but not least, the main enabler for the collection and integration of data from different sources is the IoT. IoT is the interconnection via the Internet of computing devices embedded in everyday objects, enabling them to send and receive data, and providing an Internet-based information architecture facilitating the exchange between physical objects and the virtual representation in information technology (IT) systems. IoT can be categorised as “consumer” IoT, that is human centred, and Industrial IoT (IIoT), that covers the domains of machine-to-machine (M2M) and industrial communication technologies with automation applications, connecting with the information systems and business processes (Boyes, H., 2018). Another important aspect to be defined in the Industry 4.0 environment, is how it changes the role of simulation of systems and processes. The role of simulation changes with the pressure due to the increasing product variety and customization, that require more flexible production systems modelling for a dynamic performance assessment and optimization. Therefore, simulation in the Industry 4.0 environment will leverage real-time data in order to mirror the physical world in a virtual model, allowing operators to test and optimize the machine settings, even in a systemic perspective. The major expression of this new simulation paradigm – run on line, synchronized with the physical system – is embodied by the Digital Twin (DT) concept. It represents the virtual and computerized counterpart of a physical system that can be used for various simulation purposes, exploiting real-time sensed data coming from the field, allowing prediction, and with the capability of being scaled from the asset to the system level (Khajavi, H., 2015).