A brief survey of sensing for metal-based powder bed fusion additive manufacturing
TL;DR: The cause of common defects in powder bed additive manufacturing is reviewed, sensing and control methods which have recently been investigated are surveyed, and recently-developed strategies to monitor part quality during the build process are summarized.
Abstract: Purpose ± Powder bed fusion additive manufacturing (PB F AM) of metal components has attracted much attention, but the inability to quickly and easily ensure quality has limited its industrial use. Since the technology is currently being investigated for critical engineered components and is largely considered uns uitable for high volume production , traditional statistical quality control methods cannot be readily applied . An alternative strategy for quality control is to monitor the build in real time with a variety of sensing methods and, when possible, to correct any defects as they occur. This article reviews the cause of common defects in powder bed additive manufactur ing , briefly surveys process monitoring strategies in the literature, and summarizes recently -developed strategies to monitor part quality during the build process. Design/methodology/approach ± Factors that affect part quality in powder bed additive manuf acturing are categorized as those influenced by machine variables and those affected by other build attributes. Within each category, multiple process monitoring methods are presented. Findings ± A multitude of factors contribute to the overall quality of a part built using PB F AM . Rather than limiting processing to a pre -defined build recipe and assuming complete repeatability , part quality will be ensured by monitoring the process as it occurs and , when possible, altering the process conditions or build plan in real -time . Recent work shows promise in this area and brings us closer to the goal of wide -spread adoption of additive manufacturing technology. Originality/value - This work serves to introduce and define the possible sources of defects and errors in metal -based PB F AM, and surveys sensing and control methods which have recently been investigated to increase overall part quality . E mphasis has been placed on novel developments in the field and their contribution to the understanding of the add itive manufacturing process. Keywords ± additive manufacturing, sensing and control, process quality, defects Article Classification - General review
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TL;DR: In this article, the authors identify, analyzes, and classifies the common defects and their contributing parameters reported in the literature, and define the relationship between the two and classify them under an umbrella of manufacturing features for monitoring and control purposes.
Abstract: The powder bed fusion additive manufacturing process enables fabrication of metal parts with complex geometry and elaborate internal features, the simplification of the assembly process, and the reduction of development time; however, its tremendous potential for widespread application in industry is hampered by the lack of consistent quality. This limits its ability as a viable manufacturing process particularly in the aerospace and medical industries where high quality and repeatability are critical. A variety of defects, which may be initiated during powder bed fusion additive manufacturing, compromise the repeatability, precision, and resulting mechanical properties of the final part. One approach that has been more recently proposed to try to control the process by detecting, avoiding, and/or eliminating defects is online monitoring. In order to support the design and implementation of effective monitoring and control strategies, this paper identifies, analyzes, and classifies the common defects and their contributing parameters reported in the literature, and defines the relationship between the two. Next, both defects and contributing parameters are categorized under an umbrella of manufacturing features for monitoring and control purposes. The quintuple set of manufacturing features presented here is meant to be employed for online monitoring and control in order to ultimately achieve a defect-free part. This categorization is established based on three criteria: (1) covering all the defects generated during the process, (2) including the essential contributing parameters for the majority of defects, and (3) the defects need to be detectable by existing monitoring approaches as well as controllable through standard process parameters. Finally, the monitoring of signatures instead of actual defects is presented as an alternative approach to controlling the process “indirectly.”
160 citations
TL;DR: In this article, a comprehensive real-time inspection method and a closed loop monitoring system are proposed to address the quality control for metal-based additive manufacturing processes, and possible inspection system configurations for improving the quality of AM printed parts are discussed.
Abstract: One of the most significant barriers to the broad adoption of additive manufacturing (AM) is the qualification of AM produced parts. With the high market competition, quality has become the market differentiator for products and services. To maintain or enhance the quality of the products, manufacturers use two techniques, quality assurance and control. In fact, many researchers characterize the quality assurance and control as the biggest challenge to widespread adoption of AM technologies for metals parts in aerospace industries. One approach to overcome this challenge is to implement in-situ process monitoring and inspection systems to enhance the quality of the printed parts and AM processes. This has been highlighted by numerous research efforts for the past decade and continues to be identified as a high priority research in the AM processes. In this paper, we review current process monitoring and control systems for metal AM in Powder Bed Fusion and Directed Energy Deposition systems. And then, possible inspection system configurations for improving the quality of AM printed parts are discussed based on the proposed framework and requirement. A comprehensive real-time inspection method and a closed loop monitoring system are proposed to address the quality control for metal-based AM processes
119 citations
01 Dec 2017
TL;DR: In this paper, various types of microstructural features or defects, their generation mechanisms, their effect on bulk properties and the capability of existing characterisation methodologies for powder-based AM parts are reviewed.
Abstract: Powder-based additive manufacturing (AM) technologies have been evaluated for use in different fields of application (aerospace, medical, etc.). Ideally, AM parts should be at least equivalent, or preferably better quality than conventionally produced parts. Manufacturing defects and their effects on the quality and performance of AM parts are a currently a major concern. It is essential to understand the defect types, their generation mechanisms, and the detection methodologies for mechanical properties evaluation and quality control. We consider the various types of microstructural features or defects, their generation mechanisms, their effect on bulk properties and the capability of existing characterisation methodologies for powder based AM parts in this work. Methods of in-situ non-destructive evaluation and the influence of defects on mechanical properties and design considerations are also reviewed. Together, these provide a framework to understand the relevant machine and material parameters, optimise the process and production, and select appropriate characterisation methods.
99 citations
TL;DR: A critical opinion on optimal design is delivered to show limits, benefits and ways of improvement in additive manufacturing and differences that may appear between virtual and real design are explored.
Abstract: Three-dimensional printing offers varied possibilities of design that can be bridged to optimisation tools. In this review paper, a critical opinion on optimal design is delivered to show limits, benefits and ways of improvement in additive manufacturing. This review emphasises on design constrains related to additive manufacturing and differences that may appear between virtual and real design. These differences are explored based on 3D imaging techniques that are intended to show defect related processing. Guidelines of safe use of the term “optimal design” are derived based on 3D structural information.
87 citations
References
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TL;DR: In this article, the authors discuss the principle and relevance of an in situ monitoring system for selective laser melting (SLM) which enables the operator to monitor the quality of the SLM job on-line and estimate the part accordingly.
Abstract: This paper discusses the principle and the relevance of an in situ monitoring system for selective laser melting (SLM). This system enables the operator to monitor the quality of the SLM job on-line and estimate the quality of the part accordingly. The monitoring system consists of two major developments in hardware and software. The first development, essential for a suitable monitoring system, is the design of a complete optical sensor set-up. This set-up is equipped with two commercially available optical sensors connected to a field-programmable gate array (FPGA) which communicates directly with the machine control unit. While the sensors ensure a high-quality measurement of the melt pool, the FPGA’s main task is to transfer the images from the sensors into relevant values at high sample rates (above 10 kHz). The second development is the data analysis system to translate and visualize measured sensor values in the format of interpretable process quality images. The visualization is mainly done by a “mapping algorithm,” which transfers the measurements from a time-domain into a position-domain representation. Further off-line experiments illustrate an excellent compatibility between the in situ monitoring and the actual quality of the products. The resulting images coming out of this model illustrate melt pool variations which can be linked to pores that are present in the parts.
339 citations
TL;DR: Monitoring of laser processes has been researched actively since the 1980's in several institutes around the world and has been commercially applied to even the newest laser processes, e.g. additive manufacturing.
206 citations
DOI•
01 Aug 2011TL;DR: The development of a framework for online quality control of Selective Laser Melting is the subject of this paper and consists of two complementary systems: a system for visual inspection of powder deposition and aSystem for online and real-time monitoring of the melt pool.
Abstract: Selective Laser Melting (SLM) is an Additive Manufacturing technique which allows producing three-dimensional metallic parts from powder material, using a layerby-layer fashion. Typical applications of this technology are parts with high geometrical complexity or internal features such as biomedical implants or casting molds with conformal cooling channels. In order to break through in industries with very high quality standards (such as aerospace industries), an important issue to be addressed is quality monitoring and control during the actual building process. Online quality control can significantly increase the robustness of the process by enabling to check the quality of the building process in the earliest possible stage, such that eventually corrective actions can be taken during the process. This is in contrast with on-line and a posteriori quality control which does not allow taking corrective measures if the quality of the part does not meet the desired quality standard. The development of a framework for online quality control of Selective Laser Melting is the subject of this paper. The framework consists of two complementary systems: a system for visual inspection of powder deposition and a system for online and real-time monitoring of the melt pool. A combination of these two systems enables to guarantee the quality of SLM parts with high confidence.
133 citations
01 Jan 2013
TL;DR: High-power laser and their material processing applications can be classified into three main classes: laser-assisted micro-fabrication, laser assisted welding, and laser-induced periodic surface structures as mentioned in this paper.
Abstract: High-power lasers and their material processing applications.- An overview.- Laser-assisted machining of materials.- Current status and future scope of application.- Laser-assisted micro-fabrication.- Laser-assisted welding of materials.- Direct laser cladding.- Laser surface engineering.- Laser-induced periodic surface structures.- Optical monitoring in laser processing.- Diode laser-assisted materials processing.- Laser-assisted surface processing for biomedical applications.
72 citations
18 Feb 2014
TL;DR: In this article, an ultrasonic sensor was developed for detecting changes in porosity in metal parts during fabrication on a metal powder bed fusion system, for use as a process monitor.
Abstract: Some metal additive manufacturing processes can produce parts with internal porosity, either intentionally (with careful selection of the process parameters) or unintentionally (if the process is not well-controlled.) Material porosity is undesirable for aerospace parts - since porosity could lead to premature failure - and desirable for some biomedical implants, since surface-breaking pores allow for better integration with biological tissue. Changes in a part's porosity during an additive manufacturing build may also be an indication of an undesired change in the process. We are developing an ultrasonic sensor for detecting changes in porosity in metal parts during fabrication on a metal powder bed fusion system, for use as a process monitor. This paper will describe our work to develop an ultrasonic-based sensor for monitoring part porosity during an additive build, including background theory, the development and detailed characterization of reference additive porosity samples, and a potential design for in-situ implementation.
37 citations