## 1 Introduction  
Today, equipment maintenance has become crucial to increasing the overall performance of any manufacturing organization [1], especially in this increasingly competitive environment, where every company is seeking to maintain or even expand its market position. Actually, maintenance is no longer merely about correcting breakdowns [1, 2], but has become a crucial tool for optimizing processes, reducing downtime costs, and even improving quality [3]. As such, efficient maintenance management has a direct impact not only on equipment condition, but also on business productivity, flexibility, and competitiveness [4]. Meanwhile, the fourth industrial revolution, also known as Industry 4.0, is changing conventional production models [5]. Thus, this transformation goes beyond manufacturing processes and has a significant effect on how maintenance tasks are conceived and managed. Based on the integration of new and advanced technologies, such as the Internet of Things (IoT), Cyber-Physical Systems (CPSs), artificial intelligence (AI), real-time connectivity, cloud computing, and predictive analytics [6; 7], this new trend allows for better machine interconnection, automated decision-making, failure anticipation, and the continuous optimization of operations [8]. However, while these technologies offer substantial improvements in efficiency and productivity, they also create a reliance on interconnected systems, which can introduce vulnerabilities. Furthermore, the rapid pace of technological change may exceed an organization's capacity to adequately train its workforce, potentially resulting in a skills gap that obstructs the full utilization of these innovations [3; 5; 9]. In this new challenging environment, traditional approaches must also be improved and adapted to the context of Industry 4.0. When it comes to maintenance, we find that Total Productive Maintenance (TPM), which, since its emergence in the 1970s, has played a major role in the continuous improvement of industrial performance in companies [9; 10; 11]. Thanks to its principles of Continuous Improvement; Autonomous Maintenance; Preventive Maintenance; Quality Maintenance; Training and Education; and Safety, Health and the Environment, and the TPM office, companies that adopt it have been able to achieve high levels of reliability and availability [9]. However, in the current context, these principles must also be adapted to the new requirements and opportunities of the new industrial era [12]. This has given rise to a new term, TPM 4.0 or digital TPM [6; 12], in which new technologies are integrated into the development of traditional principles, enabling the continuous monitoring of equipment, shifting from preventive maintenance to data-driven predictive maintenance, while ensuring real-time management and better integration between production and maintenance [6]. Consequently, a central question stands out: _\"How does TPM evolve in the era of Industry 4.0, and what foundations can be used to build a digital implementation standard\"?_  
In order to effectively address this issue, this article proposes an in-depth analysis based on a systematic literature review (SLR) preceded by a bibliometric study, with a dual objective:  
* Firstly, to map scientific production on digital TPM by identifying trends, studies, publication sources, and dominant themes;
* Secondly, to structure the conceptual and technological contributions in order to propose the foundations of a standard for the implementation of TPM in the era of Industry 4.0. Consequently, the results of this study will allow us to establish a better understanding of the current dynamics of TPM 4.0 research, to clarify the technological facilitators identified in the literature, and to lay the foundations for a structured framework that can be used as a practical reference point for companies.