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Monitoring and Control in Additive Manufacturing Processes

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A special issue of Materials (ISSN 1996-1944). This special issue belongs to the section "Manufacturing Processes and Systems".

Deadline for manuscript submissions: closed (10 December 2022) | Viewed by 18797

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Dr. Brian T. Gibson

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Guest Editor

Oak Ridge National Laboratory, Knoxville, TN 37932, USA
Interests: additive manufacturing; control; robotics; sensors
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Additive manufacturing (AM) has the potential to be disruptive in numerous industry sectors, both in the direct manufacture of parts and in the manufacture of production tooling. High costs and long lead times associated with parts manufactured via traditional methods have, for years, driven the increasing interest in AM. AM also affords the opportunity for rapid design and production cycles, low-volume manufacture, and site-specific control of part properties. While significant progress has been made in terms of process development and control over the last decade, new generations of machines, larger build volumes, additional degrees-of-freedom, multiple points of deposition, new slicing techniques, novel sensors systems, and closed-loop control all present opportunities for AM to reach new applications, achieve greater part quality, and accelerate adoption by industry.

It is my pleasure to invite authors to submit original research articles and review articles that will contribute to the broad area of monitoring and control in additive manufacturing processes, including metal-, polymer-, concrete-, and other material-based systems. Potential topics include, but are not limited to:

Directed energy deposition
Metal powder bed fusion
Extrusion-based processes
Novel AM processes and machine configurations
Tool path or scan path generation
Novel sensor systems and imaging techniques
Closed-loop process control
Data analytics and machine learning

Dr. Brian T. Gibson
Guest Editor

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Keywords

Additive manufacturing
Sensors
Feedback
Closed-loop control
Slicing
Machine control

Published Papers (7 papers)

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Research

18 pages, 9736 KiB

Open AccessArticle

Modeling and Control of Layer Height in Laser Wire Additive Manufacturing

by Natago Guilé Mbodj, Mohammad Abuabiah, Peter Plapper, Maxime El Kandaoui and Slah Yaacoubi

Materials 2022, 15(13), 4479; https://0-doi-org.brum.beds.ac.uk/10.3390/ma15134479 - 25 Jun 2022

Cited by 6 | Viewed by 2152

Abstract

Laser Wire Additive Manufacturing (LWAM) is a flexible and fast manufacturing method used to produce variants of high metal geometric complexity. In this work, a physics-based model of the bead geometry including process parameters and material properties was developed for the LWAM process of large-scale products. The developed model aimed to include critical process parameters, material properties and thermal history to describe the relationship between the layer height with different process inputs (i.e., the power, the standoff distance, the temperature, the wire-feed rate, and the travel speed). Then, a Model Predictive Controller (MPC) was designed to keep the layer height trajectory constant taking into consideration the constraints faced in the LWAM technology. Experimental validation results were performed to check the accuracy of the proposed model and the results revealed that the developed model matches the experimental data. Finally, the designed MPC controller was able to track a predefined layer height reference signal by controlling the temperature input of the system. Full article

(This article belongs to the Special Issue Monitoring and Control in Additive Manufacturing Processes)

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11 pages, 3224 KiB

Open AccessCommunication

Automated Process Planning for Embossing and Functionally Grading Materials via Site-Specific Control in Large-Format Metal-Based Additive Manufacturing

by Michael Borish, Brian T. Gibson, Cameron Adkins and Paritosh Mhatre

Materials 2022, 15(12), 4152; https://0-doi-org.brum.beds.ac.uk/10.3390/ma15124152 - 11 Jun 2022

Cited by 1 | Viewed by 1475

Abstract

The potential for site-specific, process-parameter control is an attribute of additive manufacturing (AM) that makes it highly attractive as a manufacturing process. The research interest in the functionally grading material properties of numerous AM processes has been high for years. However, one of the issues that slows developmental progress in this area is process planning. It is not uncommon for manual programming methods and bespoke solutions to be utilized for site-specific control efforts. This article presents the development of slicing software that contains a fully automated process planning approach for enabling through-thickness, process-parameter control for a range of AM processes. The technique includes the use of parent and child geometries for controlling the locations of site-specific parameters, which are overlayed onto unmodified toolpaths, i.e., a vector-based planning approach is used in which additional information, such as melt pool size for large-scale metal AM processes, is assigned to the vectors. This technique has the potential for macro- and micro-structural modifications to printed objects. A proof-of-principle experiment is highlighted in which this technique was used to generate dynamic bead geometries that were deposited to induce a novel surface embossing effect, and additional software examples are presented that highlight software support for more complex objects. Full article

(This article belongs to the Special Issue Monitoring and Control in Additive Manufacturing Processes)

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13 pages, 1089 KiB

Open AccessArticle

Methodology to Determine Melt Pool Anomalies in Powder Bed Fusion of Metals Using a Laser Beam by Means of Process Monitoring and Sensor Data Fusion

by Jana Harbig, David L. Wenzler, Siegfried Baehr, Michael K. Kick, Holger Merschroth, Andreas Wimmer, Matthias Weigold and Michael F. Zaeh

Materials 2022, 15(3), 1265; https://0-doi-org.brum.beds.ac.uk/10.3390/ma15031265 - 08 Feb 2022

Cited by 14 | Viewed by 2673

Abstract

Additive manufacturing, in particular the powder bed fusion of metals using a laser beam, has a wide range of possible technical applications. Especially for safety-critical applications, a quality assurance of the components is indispensable. However, time-consuming and costly quality assurance measures, such as computer tomography, represent a barrier for further industrial spreading. For this reason, alternative methods for process anomaly detection using process monitoring systems have been developed. However, the defect detection quality of current methods is limited, as single monitoring systems only detect specific process anomalies. Therefore, a new methodology to evaluate the data of multiple monitoring systems is derived using sensor data fusion. Focus was placed on the causes and the appearance of defects in different monitoring systems (photodiodes, on- and off-axis high-speed cameras, and thermography). Based on this, indicators representing characteristics of the process were developed to reduce the data. Finally, deterministic models for the data fusion within a monitoring system and between the monitoring systems were developed. The result was a defect detection of up to 92% of the melt track defects. The methodology was thus able to determine process anomalies and to evaluate the suitability of a specific process monitoring system for the defect detection. Full article

(This article belongs to the Special Issue Monitoring and Control in Additive Manufacturing Processes)

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20 pages, 39379 KiB

Open AccessArticle

Real-Time Sensing of Output Polymer Flow Temperature and Volumetric Flowrate in Fused Filament Fabrication Process

by Rakshith Badarinath and Vittaldas Prabhu

Materials 2022, 15(2), 618; https://0-doi-org.brum.beds.ac.uk/10.3390/ma15020618 - 14 Jan 2022

Cited by 7 | Viewed by 3015

Abstract

In this paper we addressed key challenges in engineering an instrumentation system for sensing and signal processing for real-time estimation of two main process variables in the Fused-Filament-Fabrication process: (i) temperature of the polymer melt exiting the nozzle using a thermocouple; and (ii) polymer flowrate using extrusion width measurements in real-time, in-situ, using a microscope camera. We used a design of experiments approach to develop response surface models for two materials that enable accurate estimation of the polymer exit temperature as a function of polymer flowrate and liquefier temperature with a fit of

R^{2} = 99.96 % and 99.39 %

. The live video stream of the deposition process was used to compute the flowrate based on a road geometry model. Specifically, a robust extrusion width recognizer

(REXR)

algorithm was developed to identify edges of the deposited road and for real-time computation of extrusion width, which was found to be robust to filament colors and materials. The extrusion width measurement was found to be within 0.08 mm of caliper measurements with an

R^{2}

value of 99.91% and was found to closely track the requested flowrate from the slicer. This opens new avenues for advancing the engineering science for process monitoring and control of FFF. Full article

(This article belongs to the Special Issue Monitoring and Control in Additive Manufacturing Processes)

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17 pages, 6295 KiB

Open AccessArticle

Influence of Laser Energy Input and Shielding Gas Flow on Evaporation Fume during Laser Powder Bed Fusion of Zn Metal

by Yu Qin, Jinge Liu, Yanzhe Chen, Peng Wen, Yufeng Zheng, Yun Tian, Maximilian Voshage and Johannes Henrich Schleifenbaum

Materials 2021, 14(10), 2677; https://0-doi-org.brum.beds.ac.uk/10.3390/ma14102677 - 20 May 2021

Cited by 11 | Viewed by 2987

Abstract

Laser powder bed fusion (LPBF) of Zn-based metals exhibits prominent advantages to produce customized biodegradable implants. However, massive evaporation occurs during laser melting of Zn so that it becomes a critical issue to modulate laser energy input and gas shielding conditions to eliminate the negative effect of evaporation fume during the LPBF process. In this research, two numerical models were established to simulate the interaction between the scanning laser and Zn metal as well as the interaction between the shielding gas flow and the evaporation fume, respectively. The first model predicted the evaporation rate under different laser energy input by taking the effect of evaporation on the conservation of energy, momentum, and mass into consideration. With the evaporation rate as the input, the second model predicted the elimination effect of evaporation fume under different conditions of shielding gas flow by taking the effect of the gas circulation system including geometrical design and flow rate. In the case involving an adequate laser energy input and an optimized shielding gas flow, the evaporation fume was efficiently removed from the processing chamber during the LPBF process. Furthermore, the influence of evaporation on surface quality densification was discussed by comparing LPBF of pure Zn and a Titanium alloy. The established numerical analysis not only helps to find the adequate laser energy input and the optimized shielding gas flow for the LPBF of Zn based metal, but is also beneficial to understand the influence of evaporation on the LPBF process. Full article

(This article belongs to the Special Issue Monitoring and Control in Additive Manufacturing Processes)

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12 pages, 6348 KiB

Open AccessArticle

OICP: An Online Fast Registration Algorithm Based on Rigid Translation Applied to Wire Arc Additive Manufacturing of Mold Repair

by Ruibing Wu, Ziping Yu, Donghong Ding, Qinghua Lu, Zengxi Pan and Huijun Li

Materials 2021, 14(6), 1563; https://0-doi-org.brum.beds.ac.uk/10.3390/ma14061563 - 22 Mar 2021

Cited by 7 | Viewed by 2245

Abstract

As promising technology with low requirements and high depositing efficiency, Wire Arc Additive Manufacturing (WAAM) can significantly reduce the repair cost and improve the formation quality of molds. To further improve the accuracy of WAAM in repairing molds, the point cloud model that expresses the spatial distribution and surface characteristics of the mold is proposed. Since the mold has a large size, it is necessary to be scanned multiple times, resulting in multiple point cloud models. The point cloud registration, such as the Iterative Closest Point (ICP) algorithm, then plays the role of merging multiple point cloud models to reconstruct a complete data model. However, using the ICP algorithm to merge large point clouds with a low-overlap area is inefficient, time-consuming, and unsatisfactory. Therefore, this paper provides the improved Offset Iterative Closest Point (OICP) algorithm, which is an online fast registration algorithm suitable for intelligent WAAM mold repair technology. The practicality and reliability of the algorithm are illustrated by the comparison results with the standard ICP algorithm and the three-coordinate measuring instrument in the Experimental Setup Section. The results are that the OICP algorithm is feasible for registrations with low overlap rates. For an overlap rate lower than 60% in our experiments, the traditional ICP algorithm failed, while the Root Mean Square (RMS) error reached 0.1 mm, and the rotation error was within 0.5 degrees, indicating the improvement of the proposed OICP algorithm. Full article

(This article belongs to the Special Issue Monitoring and Control in Additive Manufacturing Processes)

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20 pages, 5378 KiB

Open AccessArticle

Model-Based Feedforward Control of Part Height in Directed Energy Deposition

by Qian Wang, Jianyi Li, Abdalla R. Nassar, Edward W. Reutzel and Wesley F. Mitchell

Materials 2021, 14(2), 337; https://0-doi-org.brum.beds.ac.uk/10.3390/ma14020337 - 11 Jan 2021

Cited by 13 | Viewed by 2458

Abstract

Control of the geometric accuracy of a metal deposit is critical in the repair and fabrication of complex components through Directed Energy Deposition (DED). This paper developed and experimentally evaluated a model-based feedforward control of laser power with the objective of achieving the targeted part height in DED. Specifically, based on the dynamic model of melt-pool geometry derived from our prior work, a nonlinear inverse-dynamics controller was derived in a hatch-by-hatch, layer-by-layer manner to modulate the laser power such that the melt-pool height was regulated during the simulated build process. Then, the laser power trajectory from the simulated closed-loop control under the nonlinear inverse-dynamics controller was implemented as a feedforward control in an Optomec Laser-Engineered Net Shape (LENS) MR-7 system. This paper considered the deposition of L-shaped structures of Ti-6AL-4V as a case study to illustrate the proposed model-based controller. Experimental validation showed that by applying the proposed model-based feed-forward control for laser power, the resulting build had 24–42% reduction in the average build height error with respect to the target build height compared to applying a constant laser power through the entire build or applying a hatch-dependent laser power strategy, for which the laser power values were obtained from experimental trial and error. Full article

(This article belongs to the Special Issue Monitoring and Control in Additive Manufacturing Processes)

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