## 1 Introduction  
Industry 4.0 (14.0) is a term introduced by the German government to label the convergence of technologies such as the Internet of Things Things (IoT), Cyberphysical Systems (CPS), and Cloud Computing in the new generation of industrial systems [1]. In the manufacturing environment envisioned by the concept of 14.0, the vast amount of data that is collected from the shop floor can be transported and analyzed to provide information that is then used to monitor and control operations. The ultimate goal is to develop Smart Manufacturing (SM) capabilities to produce finished goods of optimal quality, on time, with the minimum waste of energy and resources [2]. Initially intended as a strategy for the manufacturing sector, it has been adopted by other industries such as energy and transportation, where reliability and safety are of paramount importance [3]. The infrastructure that has been developed to support the (IoT) is the means to handle and process the data. The new Information and Communication Technologies that will provide a platform for the deployment of I4.0 have been an important topic of research [1]. Specifically, the network that allows manipulating and managing big data, from the telecommunication operators to the cloud administration and computing services, facilitates the introduction of I4.0. Communication and data transfer protocols have been developed to enable data transfer from sensors and machine controls to other equipment or the Cloud, and eventually, back to the shop floor. Delays in the process of handling and analyzing the data have an impact on the quality of the services that can be provided [4]. For this reason, data commonly goes through filtering and preprocessing procedures before it is sent to the Cloud [5]. During this procedure, data are also analyzed, and decisions are made by controls of different hierarchies based on the information that is gained from the analysis. Digital Twins (DT) and Cyberphysical Systems (CPS) are the core tools of I4.0. They merge the physical world. i.e., intelligent machines and the data from sensors and part measurements, with the virtual models designed to represent reality. The purpose of CPS and DT is to monitor and forecast the behavior of a system, with the ultimate goal of controlling their processes. In particular, computer simulation is a key element of CPS for monitoring and forecasting. Simulation models can be used for contrasting a system's behavior with expected conditions, predicting future states, diagnosing sources of problems, and preventing inefficient or hazardous conditions. The connection of the field data with these models is an important research topic [6; 7]. [PERSON] et al. [8] stressed the importance of acquiring accurate and reliable data from the shop floor to develop CPS. [PERSON] [9] described how DT are critical components of CPS, and pointed out that connectivity is a key element to achieve smart manufacturing capabilities. [PERSON] [10] stated that fast, reliable communications between machines and improved intelligence at the machine level are also features of smart factories. Machine tools are invaluable sources of information in smart factories, a perspective that needs to be assimilated at the design stage. Several studies have tried to incorporate I4.0 principles and technologies at the machine tool level. For example, current machine design trends such as sustainability, can benefit from I4.0 tools and cloud computing ([PERSON] [11]), ([PERSON] [12]). [PERSON] et al. [13] argued that smart tools are a key element for machine tools and smart processes within an I4.0 ecosystem. [PERSON] et al. [1] stated that smart devices are key elements for resilient smart factories, and both are important topics of research. To make the best use of the capabilities of the habilitating technologies in sensors, communications, and data analysis, machine architectures and design paradigms must evolve. Multiple studies have been made about the architectures that can make the best used of IoT at the system level.