With the development of intelligent manufacturing and computer science, the system of equipment in the workshop has become more and more complex. In the intricate environment, the state of device changes constantly, which could affect the accuracy of methods since they cannot adapt the changing context. Recently, Digital Twin (DT) has received great focus among academic world and industrial world, which provides a new normal form for solving problems. In this paper, the structure of DT is discussed and a DT and Stacked Auto Encoder (SAE) Based Model is proposed to monitor the product quality. Based on the classical structure of DT, the digital model of DT is further divided into two parts, a task-achieved part and a self-update part. The former that comprises an encoder network that is a part of SAE and an Artificial Neural Network (ANN)-based classifier could check whether products are qualified. And a decoder network, another part of SAE, and a parameters-update rule make up the self-update part that could detect the accuracy of the task-achieved part and retrain the neural networks as the accuracy is poor. Furthermore, a new loss function is put forward as a training criterion in order to magnify the tiny difference between input data and result. In order to emulate the changing environment, the experimental data are collected at two different points in time. The data are then input to the proposed model and two other traditional methods to test the ability of accuracy and the adaptability for changing context. The comparisons show that the proposed method has got improvements, especially in where the effect of working environment is significant.

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In this study, a Back Propagation (BP) neural network algorithm based on Genetic Algorithm (GA) optimization is proposed to plan and optimize the trajectory of a redundant robotic arm for the upper limb rehabilitation of patients. The feasibility of the trajectory was verified by numerical simulations. First, the collected dataset was used to train the BP neural network optimized by the GA. Subsequently, the critical points designated by the rehabilitation physician for the upper limb rehabilitation were used as interpolation points for cubic B−spline interpolation to plan the motion trajectory. The GA optimized the planned trajectory with the goal of time minimization, and the feasibility of the optimized trajectory was analyzed with MATLAB simulations. The planned trajectory was smooth and continuous. There was no abrupt change in location or speed. Finally, simulations revealed that the optimized trajectory reduced the motion time and increased the motion speed between two adjacent critical points which improved the rehabilitation effect and can be applied to patients with different needs, which has high application value.

Soft-PLC with open architecture is the direction of development in industrial automation. This paper discusses the method of communication between the interface functions of LinSERCANS under RTLinux and the external library of Soft-PLC under Windows. Based on the API HOOK theory, the communication between the interface functions of LinSERCANS and the external libraries of Soft-PLC is set up and it solves the calling functions of dynamic link libraries in different operation systems. It is able to combine LinSERCANS with the Soft-PLC, and a run-time system is developed based on the interface technology of the serial real-time communication system (SERCOS) and technology of soft-PLC. This runtime system has been used in all electronic injection molding machines and works very well.