The C-Arm x-ray system (C-Arm) is a useful medical device commonly used in surgeries that require the use of x-ray images during operations. In some operations, surgeons rely heavily on the mobile C-Arm to effectively execute the surgery. In some cases, the success of the operation is directly correlated with the C-Arm and its ability to be repositioned to any desired position relative to the patient. In this paper, an integrated approach is provided for the automatic and accurate repositioning of a mobile C-Arm. The development of a C-Arm prototype is explained through the use of computer-aided design and manufacturing. To automatically reposition the C-Arm, a two-step integrated approach is introduced that uses motion capture systems and artificial intelligence-based repositioning. In the first step, the C-Arm is repositioned using Vicon motion capture along with a virtual platform and graphic user interface. In the second step, the accuracy of the repositioning of the C-Arm is further improved by incorporating a deep learning convolutional neural network with image processing and point feature matching. Key results indicate successful integration of the proposed method with the C-Arm prototype for the purpose of automatic and accurate repositioning.
To save time and resources, many are making the transition to developing their ideas virtually. Computer-aided gear production realization is becoming more and more desired in the industry. To produce gears with custom qualities, such as material, weight and shape, the trial and error approach has yielded the best results. However, trial and error is costly and time consuming. The computer-aided integrated design and manufacturing approach is intended to resolve these drawbacks. A simple one stage reduction spur gearbox is used as an example in a case study. First, the gear geometry is developed using computer aided design (CAD) modeling. Next, using MATLAB/Simulink, the gear assembly is connected virtually to other subsystems for system expectations and interaction analysis. Finally, using finite element analysis (FEA) tools such as ABAQUS, a dynamic FEA of the gear integration is completed to analyze the stress concentrations and gear tooth failures. Through this method of virtual gear design, customized dimensions and specifications of gears for satisfying system-level requirements can be developed, thereby saving time and manufacturing costs for any custom gear design request.
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