# Design and Implementation of a Digital Twin System for Log Rotary Cutting Optimization
## 1 Introduction  
In the context of Industry 4.0's evolution, the sustained and deep integration of information technology into traditional manufacturing sectors has ushered the wood processing industry into the \"Intelligent Era\". At the historical intersection of a new round of technological revolution, industrial transformation, and China's accelerated high-quality development, and in the face of the new requirements of the \"dual-carbon\" strategy, digital twin technology has become an important means for further intelligent upgrading of China's wood processing industry [1]. Digital twins [2] are digital representations of real-world entities or systems, composed of physical objects and their virtual entities, twin data, and application services. Digital twins diverge from mere modeling and simulation, encompassing these methodologies as components of a more comprehensive technological ecosystem. Similar terminologies, however, denote distinct concepts, such as 'digital models', 'digital shadows', 'digital twins', and 'digital predictions'. A 'digital model' lacks real-time linkage with physical entities, akin to simulations and mathematical models; a 'digital shadow' plays a crucial role in real-time monitoring, where changes in the state of a physical entity instantaneously alter the state of its digital counterpart, constituting unidirectional real-time data communication from a physical to a digital space; a 'digital twin' involves bidirectional real-time data communication between physical and digital realms and utilizes methodologies such as big data and machine learning in cyberspace for further analysis and prediction; and a 'digital twin prediction' represents a digital replica of a physical entity, functioningthrough bidirectional real-time data communication in cyberspace [3]. Digital twins can be used to design and optimize products and processes more quickly and accurately, improve production efficiency, and reduce costs and risks. They have been widely used in various industries, including the manufacturing [4], automotive [5], medical [6], smart city [7], smart building [8], and other industries. Scholars have gradually attempted to apply digital twin technology to the wood processing industry. For example, [PERSON] proposed a simulation-based decision-making framework in 2017 to ensure order profitability, analyze required raw materials and equipment, and determine when to produce based on factory order volumes [9]. [PERSON] proposed using six characteristics of logs to train multiple machine learning models and applied them to MILP models to optimize log allocation for sawmills in 2020 [10]. [PERSON] et al. established a digital twin model of the wood side plate production process using VSM and FlexSim simulation models in 2022, effectively improving the production process and using computer vision methods to complete wood quality and thickness detection [11]. As discussed previously, the focus of most research papers is on issues related to wood processing scheduling and finished product inspection. However, the real challenge in the wood processing industry lies in the high heterogeneity of raw materials (logs) characterized by varying shapes and qualities of different logs [12]. This necessitates the adoption of distinct processing approaches for different logs to maximize resource utilization. Therefore, this paper applies digital twin technology in the wood processing workflow to achieve the aforementioned functionalities. The log rotary cutting process includes log centering, log debarking, and veneer peeling. The log is centered to find the optimal clamping point, and the outer waste material is removed by the log debarker. Finally, it is processed into veneers in the veneer peeling machine. The log debarker adopts a card-axis processing method, and the veneer peeling adopts a card-free axis processing method. The centering result is one of the important processes in the production process for card-axis processing.