## 1 Introduction  
Ergonomic issues represent one of the main factors characterizing the manufacturing working environment. Indeed, in addition to designing a production system according to an ergonomic approach, the working activities need to be continuously monitored, especially when the volume of production varies, causing changes in cycle time and, consequently, changes in working tasks and workload. Going more into detail, biomechanical overload represents one of the main risk factors in a manufacturing environment and is a possible source of Musculo-Skeletal Disorders (MSDs). MSDs consist in lesions or alterations of muscles, nerves, tendons and joints and, as demonstrated by numerous studies in literature and international standards, they are caused by prolonged exposure to awkward working postures, exerted forces, Material Manual Handling (MMH) and repetitive actions [1, 2]. Over the years, the high incidence of the MSDs related to biomechanical overload led to the development of numerous risk assessment methods, principally observation-based, as collected by [PERSON] et al. [3]. The application of risk assessment methods is mandatory during normal production to monitor working activities whenever changes are made to production volume or to working tasks. However, since the methods are observational, mostly based on the compilation of specific check-lists, the evaluation procedure is time-consuming and, additionally, strictly subjective, so it does not guarantee the repeatability of measurements. For these reasons, in the era of Industry 4.0, the need to develop numerical methodologies and measurement devices has become a priority for companies wishing to have efficient and safe production systems. In particular, among the enabling technologies, the integrated use of Industrial Internet of Things (IIoT) and simulation tools allows for monitoring working performance, enhancingthe control of the process and a near-real time management of the whole production line, in terms of balancing and ergonomics [4; 5]. However, the literature dealing with the use of Industry 4.0 concept and tools for Ergonomics is poor, as also pointed out by [PERSON] et al. [6] in a deep review. Most researches are documented in conference proceedings, although the topic is very actual with wide application possibilities. This research was born with the aim of creating tools that can support experts in ergonomic screening, ensuring accuracy and repeatability of measurements. From this point of view, the DT, based on the integration of IIoT and simulation, can represent the best solution as it allows exploiting the computational capability by using numerical models in which real data are implemented. IIoT includes objects or devices (sensors, actuators, mobiles, etc.) that are able to interact and communicate between them, via internet protocols, and, thanks to the implementation of specific algorithms, they are able to carry out measurements and make decisions autonomously in order to manage machines and production systems [7]. Among these technologies, for ergonomics purposes, wearable devices are crucial since they can be provided with sensors capable to measure parameters related to humans (postures, forces, muscular activity, etc.). Widespread in recent years, wearable motion tracking devices have seen a massive introduction in the factory environment. Thanks to their good accuracy and low invasiveness, they allow acquiring motion data during normal working activities and analyzing them in order to evaluate ergonomics indexes related to the biomechanical load due to working postures [8; 9; 10]. In addition to IIoT, a manufacturing scenario can be fully reproduced in a 3D environment, giving the possibility to simulate the operations of a real working process [11]. This makes feasible, since the design phase, choosing the correct solutions, knowing in advance the performance of the line. The implementation of real data, collected by IIoT devices, in a simulation scenario realizes the so-called Digital Twin (DT).