Inline measurement strategy for additive manufacturing

Abstract

Additive manufacturing (AM) takes a growing place in industry tanks to its ability to create free form parts with internal complex shape. Yet the final surfaces quality of the AM parts is still a challenge since it doesn't reach the required level for final use. To address this issue it is necessary to measure the form and dimensions deviation in order to plan post-process operations to be considerate. More over in a context of industry 4.0, this measurement step should be fully integrated into the manufacturing line as close as possible to the AM process and post-process. We introduce in this article an inline measurement solution based on a robot combined with a laser sensor. Robot allows reaching most of the orientation and positions necessary to digitize complex parts in a short time. The use of robot for digitizing is already addressed but not for metrological applications. Robots are perfectly design for velocity, ability and robustness but since now their poor positioning accuracy in not compatible with measuring requirements. The strategy adopted in this article is to provide an algorithm to generate path planning for digitizing AM parts at a given quality of the resulting cloud of points. After a discussion about the geometric and elastic model of the robot to identify the one that answers the quality requirements, the performances of the robot are evaluated. Thus several performances maps are introduced to characterize the behavior of the robot in its working volume. The qualification of the digitizing sensor is also performed to identify relation between digitizing parameters and the quality of final cloud of points. By using data resulting from the qualifications of sensor and robot and the part's CAD model the algorithm allows generating path planning to ensure the finale quality necessary to measure the shape deviation.

Application of total interpretive structural modeling for analyzing factors of additive manufacturing and industry 4.0 integration

“…The study revealed the possibility of decentralization by transferring the manufacturing load over the cloud and reduces sustainability issues, which is the key requirement of the current manufacturing scenario. Bordron et al (2019) studied I4.0 based solutions to tackle the challenges associated with AM. They reported the surface quality of the manufactured product as an important concern of the AM process.…”

“…They found no correlation between theoretical and experimental dimensional information. Thus, the need for I4.0 technologies in AM exists to track and improve the surface quality of the product (Bordron et al , 2019). Haleem and Javaid (2019) discussed AM applications in I4.0.…”

An automatic compensation method for improving forming precision of multi-layer multi-bead component

“…16 Through extensive research, WAAM technology has rapidly improved over the past decade. High forming accuracy has been achieved for thin-walled components (single-bead multi-layer components), 17,18 as well as high flatness of single-layer multi-bead weld surfaces, 19 and various paths planning algorithm have been proposed for different geometric shapes. 20 In contrast, the forming accuracy and surface flatness of multi-layer multi-bead (MLMB) components are generally low.…”

Development of a novel mobile robotic system for large-scale manufacturing

“…Commonly used three-dimensional measurement methods include fringe projection technology, 22 binocular vision, 23 and laser radar. 24 Compared to other methods, fringe projection technology has high resolution, real-time operability and robustness. 25 The measurement system can perform on-line measurement of the workpiece profile and measure the position and orientation of the robot and workpiece in relation to each other, which makes robotic machining more flexible.…”