Digital Twins for High-Tech Machining Applications—A Model-Based Analytics-Ready Approach

Abstract

This paper presents a brief introduction to competition-driven digital transformation in the machining sector. On this basis, the creation of a digital twin for machining processes is approached firstly using a basic digital twin structure. The latter is sub-grouped into information and data models, specific calculation and process models, all seen from an application-oriented perspective. Moreover, digital shadow and digital twin are embedded in this framework, being discussed in the context of a state-of-the-art literature review. The main part of this paper addresses models for machine and path inaccuracies, material removal and tool engagement, cutting force, process stability, thermal behavior, workpiece and surface properties. Furthermore, these models are superimposed towards an integral digital twin. In addition, the overall context is expanded towards an integral software architecture of a digital twin providing information system. The information system, in turn, ties in with existing forward-oriented planning from operational practice, leading to a significant expansion of the initially presented basic structure for a digital twin. Consequently, a time-stratified data layer platform is introduced to prepare for the resulting shadow-twin transformation loop. Finally, subtasks are defined to assure functional interfaces, model integrability and feedback measures.

Digitalized Automation Engineering of Industry 4.0 Production Systems and Their Tight Cooperation with Digital Twins

“…Traditionally, digital twins are defined in a domain-specific way that relies on a mathematical-physical description resulting from specific spatial shapes, materials, and physical phenomena/equations, see for example machining processes for high-tech/aerospace industry [15,16]. To simplify the design process of digital twins, generation of digital twins from 2D and 3D CAD plans/models is addressed in [17], by means of generating graphs from available plans/models that pose a basis for graph matchmaking.…”

A digital twin defined autonomous milling process towards the online optimal control of milling deformation for thin-walled parts

“…In recent years, the application of DT in machine tools has made achievements in many aspects. For the DT-driven machine tool framework, Hänel et al [15] introduced a competitiondriven digital transformation in the machining sector, in which the creation of a DT for machining processes is approached by using a basic DT structure; Zhao et al [16] proposed an advanced DT system framework for CNC machine tools and discussed the key factors that made the DT system more practical; Vishnu et al [17] proposed a digital twin framework for NC machining processes, which allows simulation, prediction, and optimization of key performance indicators using the historical and real-time machining data during process planning and machining phases, respectively. For thin-walled parts manufacturing, Zhu et al [18] presented a DT-driven thin-walled part manufacturing framework to allow the machine operator to manage the product changes, and make the start-up phases faster and more accurate.…”

Cloud-based process design in a digital twin framework with integrated and coupled technology models for blisk milling

“…Therefore, a well implemented DT framework should fulfill requirements regarding standardization, multidirectional communication, scalability, flexibility, modularity, traceability, real-time capability, and security (Boschert et al, 2016). The consistent usage of a standardized DT framework can help manufacturers to generate and manage common data and model collections, e.g., acquired process data from a machine tool consisting of position signals, motor drive currents or spindle speed (Hänel et al, 2020;Hänel et al, 2021).…”