Currently digital transformation has a huge impact on human lives. Digital transformation does not just mean a transformation of a (non-) physical element to a digitally identifiable element. It focuses on the utilization of digital technology for transforming (improving) procedures or routines of business and operation. The manufacturing industry has been adopting the most recent digital technology, and lots of digital data are being created. To utilize the stored data, data analysis is essential. Because the manufacturing data is created in a different format at every manufacturing step, the integration of the data is always the bottleneck of the data analysis. Querying of the right data at the proper time is fundamental for high-level data analysis. The digital thread is introduced to provide the inter-reference of digital data based on a context. This paper proposes a digital thread framework for the machining process. The context of the proposed framework consists of the questions of how the product will be machined, how it is (was) being produced, and how it was made. A prototype software was developed to verify the proposed framework by implementing the creating, storing, and querying modules for simulation, monitoring, and inspection data.

With the advent of the 4th industrial revolution, advanced digital manufacturing technologies are actively developed to strengthen manufacturing competitiveness. Smart factories require a real-time digital twin including a Cyber-Physical System (CPS) of machines and processes and intelligent technologies based on the CPS. To predict machining quality and optimize machines and processes, it is necessary to analyze the cutting force during machining. Therefore, for real-time digital twin, a fast cutting force simulation model that receives information such as the positions of the feed axes in short time intervals from the CNC and calculates the cutting force until the next information is input is required. This paper proposes a voxel-based fast cutting force simulation in NC milling for real-time digital twin. The proposed simulation model quickly calculates the cutting force by using only information of voxel elements removed by each tool edge without complicated Cutter-Workpiece Engagement (CWE) and chip thickness calculations in previous studies. To verify the performance of the developed simulation, experimental machining was performed and the measured cutting force and simulated cutting force were compared. It was demonstrated that the proposed model can successfully predict the cutting force 3.5 times faster than the actual process.