## 1 Introduction  
Until recently, digitization was seen as a strategic lever to innovate, stand out, and attract market attention [1]. Today, it has become a necessity for all companies [2], as evidenced by the value of the global digital transformation market, estimated at USD 731.13 billion in 2022, with a projected annual growth of 26.7 percent until 2030 [3]. It is no longer a choice, but a compulsory shift [4], accelerated by the COVID-19 pandemic that has driven every industry to adopt digital solutions [5]. To be competitive, companies must embrace digital transformation [6]. In manufacturing, this means integrating information systems, production environments, and operational technologies [7], aiming for more agile, flexible, and intelligent infrastructures capable of adapting to the changing market [8; 9]. In this context, digital transformation is one of the main outcomes of Industry 4.0 [10] and requires a profound overhaul of the entire business organization [11]. Integrating digital technologies into all processes is not easy, and many companies are not yet ready [12]. Reliable tools are needed to analyze system performance, manage complex changes, and support decision-making [13]. Indeed, moving to automation involves comparing different operational configurations before final adoption [14], evaluating options in terms of cost, flexibility, and throughput [15], as well as the optimal allocation of buffering resources in often constrained contexts [16]. In a resource-constrained scenario, it is critical to invest purposefully and use fast and accurate analytical tools [17; 18]. Among the enabling technologies, discrete event simulation (DES) offers key support for digital transformation [19]. In addition to digitizing processes, DES makes it possible to analyze, optimize, and test alternative scenarios in a virtual environment without operational impacts [20; 21]. This makes it a strategic tool in initial planning, helping companies understand the real impact of new technologies on their processes [22]. In this scenario, the present research proposes a case study in which DES is employed to guide and support the digital transformation process of an enterprise operating in the manufacturing sector. Specifically, WITNESS simulation software v 14.0 is used to digitally reconstruct the manufacturing process of an Italian company that produces aluminum cabinets for electric charging stations for automobiles. In a first phase, the simulation allowed for a detailed study and analysis of the process, identifying strengths and weaknesses [23; 24]. The results obtained were crucial for the next stage, in which several \"what-if\" analyses were conducted to evaluate the performance of various technological solutions to be implemented in the process, with the aim of optimizing it and initiating the development of smart manufacturing. The goal of this study is to propose a scientifically rigorous approach to support companies in their digital transition. DES is the tool used to guide business managers through such a radical and delicate change. An innovative approach is proposed using a framework and specific guidelines. In detail, it is intended to clarify the following:  
Q1: What is the evolutionary scenario and current status of DES becoming a Key Enabling Technology (KET) for Industry 4.0.? Q2: What are the distinguishing features of DES that offer significant benefits to manufacturing companies in terms of operational efficiency, cost reduction, and product quality improvement? Q3: How can DES effectively drive digital transformation in processes, facilitating the adoption of emerging technologies and optimizing the entire production chain? The proposed framework provides a clear and methodological approach for addressing digital transformation, offering companies a defined path. The practical guidelines, based on experience and empirical evidence, show how to apply the theoretical concepts of digital transformation in the real context of production processes.