Additive manufacturing, a key enabler of Industry 4.0, is revolutionizing the automatic landscape in manufacturing. The primary challenge in manufacturing innovation centers on the implementation of smart factories characterized by unmanned production facilities and automated management systems. To overcome this challenge, the adoption of 3D printing technologies, which offer significant advantages in standardizing production processes, is crucial. However, a major obstacle in complete automation of additive manufacturing is an inadequate placement of support structures at critical locations, which remains the leading cause of print failures. This study proposed a novel algorithm for accurate detection of island regions known to be critical areas requiring support structures. The algorithm can compare loops on two consecutive layers derived from STL files. In contrast to conventional GPU-based image comparison methods, our proposed CPU-based algorithm enables high-precision detection independent of image resolution. Experimental results demonstrated the algorithm's efficacy in enhancing the reliability of 3D printing processes and optimizing automated workflows. This research contributes to the advancement of smart manufacturing by addressing a critical challenge in the automation of additive manufacturing processes.

This paper presents the design and the control performance of a novel dynamic compliant-arm support with parallel elastic actuators that was developed to assist with the daily living activities of those whose arms are compromised by muscular disease or the aging process. The parallel elastic-arm support consists of a compliant mechanism with combined passive and active components for human interaction and to reach the user’s desired positions. The achievement of these tasks requires impedance control, which can change the virtual stiffness, damping coefficients, and equilibrium points of the system; however, the desired-position tracking by the impedance control is limited when the end-effector weight varies according to the equipping of diverse objects. A prompt algorithm regarding weight calibration and friction compensation is adopted to overcome this problem. A result comparison shows that, by accurately assessing the desired workspace, the proposed algorithm is more effective for the accomplishment of the desired activities.