## 2 Context and Problems  
The development of Industry 4.0 is meant to have an important impact on all levels of the supply chain: procurement, logistics, warehousing, production, and even fulfillment [8]. This development is closely related to the development of innovative technologies, both for the process itself and in the information and communication field. However, this development is not trivial to implement in industry. The introduction of RFID technology, for example [9], is associated with many difficulties (the authors identified 18, from top management to process operators), which make this evolution difficult in the field.  
Three main categories of technologies were identified by [3], namely digital mesh (device mesh, ambient user experience, 3D printing machines), smart machines (information of everything, advanced machine learning, autonomous agents and things) and a new IT reality (adaptive security architecture, mesh app and service architecture, IoT architecture and platforms). The most promising technologies were identified a few years ago when the authors of [10] identified the main technological pillars of Industry 4.0, which were later confirmed in [11; 12; 13; 14]. These technologies were classified as emerging technologies in [15] and are still currently envisioned in the Industry 4.0 trajectory [16; 17]. Recent reviews of their potential impacts on future industrial systems are provided below:  
* Big data and analytics [18];
* Autonomous machines [19];* Advanced simulation towards digital twins [20];
* Industrial IoT [21];
* Cloud manufacturing [22];
* Additive manufacturing [23];
* Augmented reality [24].  
By implementing all these technologies, greater assurances of safety, security, scalability, and reliability are expected, therefore exhibiting the need for open interfaces, modularity, interoperability, and verification [25]. All these notions are relatively new to end-users, which makes their adoption slower.  
In addition, the conclusions drawn from practitioners when implementing former Industry 3.0 innovative technologies (automation and robotics to name a few) still make sense: it is the case study that implies the success of new technology introduction, not the opposite. In the same way that the automatization of some manual manufacturing operations can be a disaster from many aspects (repeatability, quality, productivity among others), the same drawbacks are to be expected in terms of the application of an inappropriate technology in the field. Furthermore, the complexity that is naturally induced by the introduction of a new technology implies the need for continuous technological project management, aiming at the success of integration of all its aspects (technical, organizational, etc.). This critical success factor was identified in [26] as the need for a careful choice of the leader of Industry 4.0 technology implementation. This task, which was highlighted as a new potential Industry 4.0-oriented job profile by the authors of [27], and was denoted as a digital development specialist, will necessarily handle multiple skills and expertise.  
Based on these statements, it is clear that a generic methodology to assist this digital development specialist in the integration of new technology, independent from the targeted technology, is missing.