## 1 Introduction  
Nowadays, the changing economic environment is characterized by a diverse and constantly evolving market, where responsiveness, flexibility, and innovation are the new criteria for success. In order to meet this need, business markets are looking for new manufacturing technologies to customize their products/services according to their customers' needs. Industry 4.0 is one of the concepts leading organizations to become more efficient, less wasteful, and much more productive. Industry 4.0 is an approach that aims to create an integrated and connected ecosystem to gain optimal results. It is mainly aimed at the manufacturing field, but can be applied to any other type of organization as shown in Reference [1]. In order to avail of the benefits of this paradigm, companies need to master their activities. To achieve this, they tend to use process automation, since it is one of the most effective methods for reaching this goal, according to Reference [2]. Several researchers have proposed methodologies for process automation. The initial goal was, and still is, to enhance and improve process modeling techniques by proposing tools and modeling languages to simplify the process and make it more accessible to all as shown in Reference [2]. The aim is to bridge the gap between business requirements and the technology used. That is why, over the last decade, <<model-driven>> engineering (MDE) approaches have emerged, considering models not just as documentation artifacts for communication purposes, but as central elements of the software engineering process in order to create a link between business requirements and IT requirements, as explained in Reference [3]. The methodology consists of smoothly describing a business need from a high level of abstraction to the concrete solution through model transformation. Even so, models provide solely a static presentation of the need. That is where the importance of visual computing comes in. Visual computing deals with everything related to computer visuals. It is a discipline that covers the visual representation of data through various techniques. It encompasses a number of fields including visual analytics, augmented reality, visual image processing, modeling, and simulation according to Reference [4]. Today, visual computing is considered a key enabling technology for Industry 4.0 and the industrial internet as explained in Reference [5]. This paper focused on the modeling and simulation (M&S) process. Once a model is established, simulation aims to add a dynamic component to the static model in order to increase its understandability and clarity, or to discover unknown issues, as explained in Reference [6]. Verification in traditional process automation usually occurs post-implementation, which leads to errors and inaccuracies in the expected results. By this stage, the off-target requirements are much more difficult and costly to fix. By detecting them during the earlier \"designing\" phase, simulation helps to reduce design errors and allow incorrect requirements to be fixed before they occur [6]. As such, the simulation tool is essential for evaluating the performance of the process in terms of its behavior and dynamicity. The main purpose of the simulation approach is to be able to bring to business users an early evaluation of the future process they want to set up. It aims to experimentally consider different solutions and to compare them in order to support decision-making. In this way, various case-study simulations could be performed before their implementation. Of course, experimenting with several alternatives within a real-life system is not feasible as it would be time- and money-consuming, risky (if the solution fails), and is generally not a proactive approach. Despite the wide availability of simulation methods, their application in the business processes field still remains a challenge, owing mainly to the fact that business analysts are searching for the easiest approaches by which to model and simulate their processes at the same time.