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A method for solving the problem of bend sequencing in sheet metal manufacturing is presented. The algorithm developed divides the part into basic shapes (channels and spirals) and determines the partial sequences associated with them. The complete bending sequences associated with the complete part were obtained from the combination of these partial sequences. To make this combination possible, several strategies were defined to reduce the number of solutions and, therefore, the searching time. All sequences (partial and complete) were checked considering possible part-tool collisions and tolerance constraints. The last stage was to order the sequences by taking into account the total process time. To attain the required process time accuracy, a robot was used for the handling operations. Finally, the sequence associated with the lower process time was selected as the optimal solution.

Industrial adoption of additive manufacturing (AM) processes demands improvement in the geometrical accuracy of manufactured parts. One key achievement would be to ensure that manufactured layer contours match the correspondent theoretical profiles, which would require integration of on-machine measurement devices capable of digitizing individual layers. Flatbed scanners should be considered as serious candidates, since they can achieve high scanning speeds at low prices. Nevertheless, image deformation phenomena reduce their suitability as two-dimensional verification devices. In this work, the possibilities of using flatbed scanners for AM contour verification are investigated. Image distortion errors are characterized and discussed and special attention is paid to the plication effect caused by contact imaging sensor (CIS) scanners. To compensate this phenomena, a new local distortion adjustment (LDA) method is proposed and its distortion correction capabilities are evaluated upon actual layer contours manufactured on a fused filament fabrication (FFF) machine. This proposed method is also compared to conventional global distortion adjustment (GDA). Results reveal quasi-systematic deformations of the images which could be minimized by means of distortion correction. Nevertheless, the irregular nature of such a distortion and the superposition of different errors penalize the use of GDA, to the point that it should not be used with CIS scanners. Conclusions indicate that LDA-based correction would enable the use of flatbed scanners in AM for on-machine verification tasks.Sensors 2020, 20, 1 2 of 24 following parts. Although this is the usual approach for quality assurance in AM it does not permit adoption of close-loop in-process improvements, and implies that optimization could not be done without previously manufacturing test specimens.Nevertheless, regarding the dimensional quality of manufactured parts, one key achievement would be to build layer contours that accurately follow theoretical profiles. This possibility would require on-machine integration of measurement devices to evaluate in-layer quality. The use of sensors capable of verifying each individual layer and checking the accuracy in contour tracing would allow for correction of the next layers. They would also make unnecessary previous testing of each particular geometry. Therefore, real-time, in-line metrology is commonly reported to be among the main challenges for AM development [9]. Contour verification could be carried out by means of different technologies, like structured light [7], conoscopic holography [10], coordinate measuring machine (CMM) optical probes [11] or ad hoc Charge-Couple Device (CCD) based instrumentation [12,13]. Nevertheless, computer vision based on flatbed scanner images should be considered as a serious candidate, since it can meet high scanning speeds at low prices.Flatbed scanners are optical devices commonly used to capture digital images of flat elements, such as sheets of paper or photographs. Nevertheless, image...

a b s t r a c tConoscopic holography (CH) is a non-contact interferometric technique used in surface digitizing. Like other laser techniques it is influenced by different factors such as surface reflectance, material, colour or even speckle noise caused by roughness. In this work, a CH system was used for analysing the influence of roughness on surface digitizing. For this purpose, several digitizing tests were performed on roughness specimens corresponding to EDM, face milling and flat grinding processes. Each roughness grade was digitized under different combinations of the sensor setting parameters (frequency F and power P) which satisfy that the signal acquired by the sensor lies within the quality values recommended by the manufacturer. The results were analysed by using two indicators that show quality of the points captured by the sensor regarding the surface geometrical reconstruction and its metrological reliability. Finally, the study provides a series of recommendations for adjusting the sensor in order to satisfy both indicators simultaneously.

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The current requirements for an efficient dimensional inspection of manufactured parts have lead to development of different in process and on-machine measurement (OMM) techniques. Touch trigger probes (TTP) are the most common technologies utilized, inspired on contact probes used on coordinate measuring machines (CMMs). The on-machine accuracy of TTPs depends upon precision of the tool-machine control as well as upon the procedure for TTP presetting. Taking this into account, a different OMM technique is considered in this work, which consists on a laser micrometer (LM) that is commonly used for in-process measurement of continuous products. The behaviour of TTP and LM is analysed and discussed in terms of repeatability and reproducibility. Results obtained by both techniques are compared each other by measuring a cylindrical workpiece and by checking the results with those obtained on a CMM.