**1. Introduction**

Future manufacturing systems will differ significantly from those of today. The changes will not only result in the pressure of customers on the variant of new products but also revolutionary changes in the impact of technological innovation. The most significant factor that affects the existing manufacturing environment is the customer. The factory must be able to produce the required product in the shortest possible time and at a reasonable cost. Future manufacturing will provide products that will be tailored to the requirements of a particular customer, highly sophisticated, complex, and capable of offering new functionality; therefore, it will require an entirely new manufacturing environment.

The customisation and personalisation of products are a complex problem that researchers are trying to tackle today. On the one hand, researchers have used the appropriate construction of new products, also known as modular, reconfigurable products. On the other hand, they have also tried to increase the flexibility of the manufacturing system, which we now refer to as reconfigurable manufacturing. However, future manufacturing systems will use completely new principles in their operation. Researchers have sought to develop and exploit new methods and approaches to product design and production due to the growing complexity of both products and manufacturing systems [1].

Industry 4.0 is a digital revolution being witnessed in the present generation, whereby the aim is to digitise the entire manufacturing process with minimal human or manual intervention [2]. We are in a time where every major breakthrough in technology changes the face of manufacturing industries. At present, we are in the era of Industry 4.0, which is hailed as the age of cyber-physical systems (CPSs) that has taken manufacturing and associated industry processes to an unforeseen level with flexible production, including manufacturing, supply chain, delivery, and maintenance [3]. The development of the Industry 4.0 concept was needed to develop new competitive business models. These business models need to be based on cooperation and better use of the available resources [4]. Industry 4.0 is based on digitalisation and application of exponential technologies. Digitisation and application of exponential technologies are directly linked to CPSs. CPSs presaturate physical devices with built-in tools for digital data collection, processing, and distribution, and, through the internet, are connected to each other online. CPSs form the basis for technology such as the Internet of Things and, in combination with the Internet of Services, form the base for Industry 4.0.

New factories, or their manufacturing systems, will have unique features that enable them to respond quickly and efficiently to frequently changing customer demands. These manufacturing systems will be designed as modular, reconfigurable, and intelligent holonic systems capable of rapidly changing their functions and capacities based on the auto diagnostic. The dynamism of complex manufacturing systems will no longer be possible to study using today's modelling and simulation techniques. The future dynamic manufacturing environment will require robust modelling and simulation tools that will be able to simulate complex phenomena and processes. New simulation systems must function as part of complex control systems, working in real-time and must be used to support decision-making and the creation of new knowledge. In this case, real-time work is seen as a rapid response to emerging events and time deterministic calculation of the trajectories of the development of future manufacturing system conditions [5].

Simulation has become the most essential tool for dynamic analysis of complex systems in recent decades. A high level of development has mainly seen a discreet simulation using the principles of the event orientation. The latest simulation tools have thus simplified the process of creating simulation models that today are being waived from the use of more straightforward analytical methods [6]. Today, artificial intelligence or virtual reality is the usual supportive technique used in simulations. The importance of simulation grows mainly with the increasing complexity of systems. They are mainly used where an erroneous decision can mean inefficient investment, long-term economic losses, and a weakening of its competitiveness.

In the growth of systems complexity and deployment of smart devices that decide on actions in factories of the future, it is, therefore, necessary to determine the outcome of the actions for management needs in a high emergence of processes. [7]. The requirement of frequent changes to the production base requires the rapid commissioning systems of automated manufacturing systems (Ramp Up), which will require new simulation tools. In the case of control, emulating technologies that are tied to the simulation may be used. One of the advantages of the emulation environment is that it can monitor the technical system (such as production, assembly, logistics) in real-time to evaluate the data collected and to update the model in question on a real-system basis and to carry out experiments on the simulation model simultaneously. In Industry 4.0, the introduction of the digital twinning of objects and processes is equally important [8].

The orientation of research into new manufacturing approaches is directed towards the area of intelligent manufacturing systems, using reconfigurable manufacturing systems, adaptive logistics, and the concept of competence islands. New simulation systems must also be adapted to this new requirement. They must possess the ability to simulate agent systems and model large networks. Modelling and simulation will, therefore, be an integral part of the planning and control of the processes of factories of the future.

Research on the principles of modelling and simulation and the development of factories of the future have been the long-term areas of research at the Department of Industrial Engineering, University of Žilina. The issue addressed is consistent with the strategy of Industry 4.0. Just by defining the characteristics of the systems used in factories of the future and their properties can be evaluated, as such systems can be modelled and simulated. The article, in its periphery, deals with the description of the manufacturing concepts that are potentially highly applicable for use in factories of the future, and the core descriptions of the use of modelling and simulation, mainly metamodeling, in the processes control of factories of the future. An example of using this approach is described in the processes control of laboratory ZIMS (Zilina Intelligent Manufacturing System).
