# A Five-Step Approach to Planning Data-Driven Digital Twins for Discrete Manufacturing Systems
## 1 Introduction
The authors [PERSON] et al. [35] developed a framework for smart production management and production control based on the digital twin for an assembly shop-floor. Their work does not include steps for the user to develop a digital twin of the manufacturing system from the initial idea to the final implementation. To the best of our knowledge, no research exists that considers the multi-step approach with the instructions to users for the development of the digital twin and the visualization of the output data as a whole (from the initial idea to the final presentation of the results). Various research groups [19; 20; 21; 22; 23; 24; 31; 32; 33; 34; 35] focus on different segments of the digital twin planning process, but none of them suggest a comprehensive approach to planning and development of a data-driven digital twin. Hence, our paper defines the necessary data for modelling the digital model and presents the strategy to connect the digital model to a real manufacturing system to create a digital twin. The paper also addresses the presentation of the manufacturing system output data that improves the working environment for various users of the digital twin, in terms of easier planning and keeping up with the manufacturing schedule, detection of bottlenecks, etc. Therefore, we have proposed an approach that guides the user step-by-step from the development of the digital model, to the connection between the digital model and the real world through a feedback loop, to the control of a real system by the digital twin. Finally, the presentation of the output data for various participants is given. The approach is illustrated and validated in a case study of internal logistics (i.e., material flow) of a laboratory-scale discrete manufacturing system. Our study has several contributions regarding to the given literature. First, we proposed the classification of the building blocks of manufacturing systems into four groups, regardless of the type and size of the manufacturing system. Second, we develop and present a new approach for defining the parameters needed for planning the digital model for each building block. Third, we describe the innovative control of the real manufacturing system with its digital twin. For this purpose, the real manufacturing system is connected to its digital model bi-directionally, which defines the parameters that need to be exchanged. The overall contribution combines all partial contributions and results mentioned above into a new five-step approach, allowing to develop a digital twin of manufacturing system in a more streamlined way. The rest of this paper is organized as follows. The Materials and Methods section presents our five-step approach to developing the digital twin. Each step is described in detail in its subsection. In the first step, users get familiarized with the manufacturing system; in the second step with the sequence of the processes; in the third step with the parameters required to develop a digital model of the manufacturing system; in the fourth step with the connection of the digital model to the real manufacturing system and finally, in the fifth step with the benefits of using a digital twin. To illustrate the approach, a case study is presented in Section 3. The case study presents the real manufacturing system with its digital twin developed using our five-step approach. We demonstrate the manufacturing system supported with the digital twin, which has been tested and validated in terms of functionality and practical applicability. The Results and Discussion section shows all the steps with values and graphical representations for the case study. Finally, Conclusions highlights the main findings as well as future work.