## 3 A Proposed Transferable DT for the Grinding Industry  
Due to its heavy dependence on non-systematic knowledge, which means that the process relies on extensive trial-and-error strategies, the grinding sector needs to advance towards a complete, transferable and ready-to-use digital twin (DT) through the integration of advanced models of the grinding process, original simulative mechanical tests, and state-of-the-art process sensors. Since at present grinding technology is linked to high-added value products and markets (e.g., the aerospace, automotive, and railway sectors), by achieving this goal grinding companies (machine-tool builders, wheel manufacturers and end-users of the process) will directly benefit from zero-defect production strategies and reduced setup times in a process that is highly dependent on trial-and-error experimental approaches. The present work proposes a down-top approach composed of different layers of the DT. The underlying hypothesis is based on the fact that process knowledge is distributed between very different agents (wheel manufacturer, machine-tool builders, end-users of the process, and fundamental research groups), and it is necessary to effectively share this knowledge. The aim is to produce a virtual mirror of the real process, integrating innovative monitoring systems (intelligent grinding wheel) and original theoretical and experimental approaches to grinding processes. The structure of the DT is composed of four layers, which integrate: (1) scientific knowledge of the process (advanced process modeling and numerical simulation); (2) characterization of materials through specialized mechanical testing; (3) advanced sensing techniques, to provide feedback for the process models; and (4) knowledge integration in a configurable open-source industrial tool. Each layer is described in detail in the following paragraphs, while Figure 1 illustrates the general concept underlying the DT. Figure 1: Structure and interaction between layers in the digital twin (DT) for the grinding industry. Layer 1: Numerical Modeling of Mechanical Behavior of the Grinding Wheel Using Advanced Process Simulation  
One of the main reasons for the lack of systematic knowledge about the behavior of the grinding process itself, and in particular, the behavior of the abrasive tool (the grinding wheel) lies in the fact that grinding wheels are manufactured by mixing abrasive and bonding agents along with certain other components. Since the specification is not fully standardized, and there are no standard mechanical tests for wheel characterization, the result is that it is very difficult to predict the behavior of a grinding wheel for a given part. Although general rules can be followed, the industrial practice of leading wheel manufacturers (Tyrolit, Saint-Gobain, etc.) for the optimum selection of a grinding wheel is absolutely dependent on each specific application. Due to this fact, wheel manufacturers are continuously developing new types of grinding wheels, mixing different grain shapes and sizes, inducing porosity in an artificial way or changing the bonding material properties in order to meet the requirements of new materials to be ground. The development of adequate grinding wheels is particularly important when profile wheels must be used. In this case, whilst it is possible to find not only an optimal material removal rate and good surface quality, it is also important to take into account minimum volumetric wear of the wheel in order to achieve optimal geometrical accuracy. Although this is one of the biggest challenges faced by the current industrial environment, very little information can be found in the scientific literature regarding the link between grinding wheel characteristics and performance. Consequently, in industrial practice, extensive trial-and-error experiments must be carried out in order to determine the optimum parameters for a given application. In order to meet this challenge, scientific process models can be considered as the deepest layer of a DT of the process.