Manufacturing Community Research Articles

Applying systems engineering principles to develop an open source laser based metal powder bed fusion system

Purpose Conventional powder bed fusion systems, with their high costs, proprietary nature and restrictive fees, limit research opportunities. This study aims to unveil an affordable, open-source hardware, open-source software laser-based metal powder bed fusion system. Recognizing the distinction between DIY and open-source hardware is crucial for widespread acceptance. Design/methodology/approach The authors present a comprehensive system architecture using object process methodology for functions and architecture, a design structure matrix to model system dependencies and classical technical drawing exploded views for select subsystems. Modularization enables high adaptability, fostering potential adoption. Findings The fully open system enables unrestricted research, mirroring common industrial metal laser-based powder bed fusion (L-PBF) systems. While “open” systems are available for purchase, they remain closed-source, lacking source code and technical drawings sharing, hindering contribution and co-development. The authors’ is the pioneering and sole open-source metal L-PBF system, boasting 1,500+ print hours. A series of industrial and academic adopters are currently implementing the system. Originality/value The open system, slicer software and controller offer unique process control, supporting multimaterial printing. The authors shared the design on the OpenAM GitHub page under the CERN-OHL-P v2 Open Source Hardware license. While it is functional for additive manufacturing (e.g. aluminum, tool steel, titanium and stainless steel), the entire process chain is actively evolving, ideal for co-development with the additive manufacturing community.

Alloying effects on the microstructure and properties of laser additively manufactured tungsten materials

A large body of literature within the additive manufacturing (AM) community has focused on successfully creating stable tungsten (W) microstructures due to significant interest in their application for extreme environments. However, cracking and additional embrittling features at grain boundaries have resulted in poorly performing materials, stymying the application of AM as a manufacturing technique for W. Several alloying strategies, such as ceramic particles and ductile elements, have emerged with the promise to eliminate cracking while simultaneously enhancing stability against recrystallization. In this work, we provide new insights regarding the defects and microstructural features that result from the introduction of ZrC for grain refinement and NiFe as a ductile reinforcement phase – in addition to the resulting thermophysical and mechanical properties. ZrC is shown to promote microstructural stability with increased hardness due to the formation of ZrO2 dispersoids. Conversely, NiFe forms into micron-scale FCC phase regions within a BCC W matrix, producing enhanced toughness relative to pure AM W. A combination of these effects is realized in the WNiFe + ZrC system and demonstrates that complex chemical environments coupled with the tuning of AM microstructures provides an effective pathway for enabling laser AM W materials with enhanced stability and performance.

Circular usage of waste cooking oil towards green electrical discharge machining process with lower carbon emissions

A global manufacturing community is dedicatedly striving to implement the concept of NetZero in precision cutting of difficult-to-machine materials, specifically, Inconel 617 (IN617) with due consideration to environmental protocols. The fast strain hardening issue of the said alloy during conventional processing rationalizes the application of electric discharge machining (EDM). However, EDM has been criticized for its high energy consumption and limited cutting efficiency. Moreover, conventional dielectric (kerosene) employed in EDM has drastic environmental and operator health concerns. To address the abovementioned issues, waste cooking oil (WCO) has been employed in this study which enhances the reusability of resources and minimizes the cost of the dielectric. Making the process sustainable is imperative along with continuously escalating scarcity of engineering resources. Therefore, the potential of shallow and deep cryogenically treated electrodes (SCT and DCT) has been comprehensively examined against nanofilled WCO to achieve the aforementioned objective. Three different concentrations of powder (Cp) and surfactant (Cs) to uplift the machining responses are investigated through a detailed parametric experimental design. Core machining factors such as material removal rate (MRR), surface roughness (SR), and specific energy consumption (SEC) are examined through optical and electron microscopy studies and 3D surface profilometry. Hereafter, machining factors are modelled using the artificial neural network (ANN) technique. An exceptional improvement of 80%, 25.3%, and 75.16% has been achieved in MRR, SR, and SEC respectively using nanopowder-mixed WCO against SCT brass compared to the responses’ values obtained against conventionally used kerosene. Furthermore, compared to kerosene, the maximum CO2 reduction of 79.97 ± 11.2% is achieved with WCO.

Effects of carbon content on precipitate evolution and crack susceptibility in additively manufactured IN738LC

Hot cracking is a major bottleneck preventing the additive manufacturing community from adopting precipitation-strengthened nickel-base superalloys, such as the IN738LC. Prior literature demonstrates the beneficial outcome of increasing the carbon content within IN738LC to alleviate its hot cracking problem. However, the effect of carbon content on the gamma prime precipitation and grain recrystallization was not fully addressed. Here, we fabricated five sample sets of IN738LC with different carbon contents and subjected these samples to two separate heat treatment processes. The precipitate and grain evolution were monitored under the backscattered electron imaging and electron backscattered diffraction studies. While the carbon addition could assist in addressing the hot cracking problem, horizontal delamination cracks were detected during the fabrication of large samples when the overall carbon content was above 0.4 wt.%, highlighting the need for care when introducing carbon for the purpose of resolving hot cracking.

Joint Special Issue: Advances in Design and Manufacturing for Sustainability

Abstract This special issue presents a collaborative initiative between the ASME Manufacturing Engineering Division (MED) and the Design Engineering Division (DED) to promote research in sustainability within the design and manufacturing communities. As the need grows for methodologies and tools capable of supporting sustainable systems, this compilation presents recent research trends exploring the integration of sustainability principles into and progression towards sustainability goals by the design and implementation of engineered systems.

Joint Special Section: Advances in Design and Manufacturing for Sustainability

Abstract This special issue presents a collaborative initiative between the ASME Manufacturing Engineering Division (MED) and the Design Engineering Division (DED) to promote research in sustainability within the design and manufacturing communities. As the need grows for methodologies and tools capable of supporting sustainable systems, this compilation presents recent research trends exploring the integration of sustainability principles into and progression towards sustainability goals by the design and implementation of engineered systems.

Development of Multi-Physical Simulation Models for Quasi-Static Load Analysis to Predict the Behavior of Li-Ion and Na-Ion Batteries Under Different Mechanical Abuse Loadings

There are lot of studies on understanding the short-circuit phenomena at cell component level and how to address the thermal management at module and pack level to avoid overheating. However, it is also very important, in terms of safety, to evaluate the response and failure of cells during abuse tests as this can promote the thermal runaway event. Safety of metal ion batteries under mechanical loadings is currently one of the most challenging and urgent issues face in the Electric Vehicle (EV) industry. In the battery manufacturing community, the property of strength and resistance of batteries to external loading has never been a design consideration. However, under local mechanical loading, batteries are prone to developing a internal short circuit (ISC), which may lead to the generation of smoke, fire, and possible explosion.This work is focused on the metal ion batteries safety studies (lithium and sodium) including the investigation of predictive models to determine the critical parameters that would lead to potential failure and provide critical insights to understand the mechanical and ISC behaviors of cells under mechanical abuse. Having a numerical model that correctly represents the cells and its response under different abuse tests could allow identifying main issues and helping on the cell design and chemistries to be used. To develop these models using LS-Dyna, it has been necessary to carry out studies of mechanical deformation on cell components and the complete cells. These studies have offered a better knowledge of the deformation of the inner components of the battery, being useful to identify the mechanism that initiate short circuits under mechanical misuse conditions. Building numerical models for batteries requires experimental work that provides not only the data for mechanical behavior of individual components (anode, cathode, separator, etc.), but also validation data for simulations of internal short circuit induced by mechanical abuse. Figure 1

World Practice of Applying State Support Measures for Organizations of the Military-Industrial Complex

The article is devoted to an analytical review of the best global practices in the implementation of measures of state support for organizations of the military-industrial complex (MIC). The purpose of the research was to study international experience in this area and determine its applicability in the context of the development of the Russian Federation’s MIC. The relevance of this work is determined by the need to ensure the solution of operational and strategic tasks of the Russian Federation’s military-industrial complex in the conditions of sanctions pressure from certain countries and the importance of assessing the available measures of state support for organizations of the complex. The study analyses the American Defense Manufacturing Community Support Program, which has been implemented in the United States since 2019. The program is based on the development of cooperation between public and private organizations, including enterprises of the military-industrial complex, scientific organizations, as well as local governments. The structure of the program provides for the formation of a community that brings together stakeholders to ensure sustainable development and competitiveness of the defense industrial complex. As part of the study of European experience, the activities of The European Defense Fund, established in the European Union in 2021 on the initiative of the Commission for the Support of Defense Cooperation of the European Union, were examined. The fund is focused on supporting and developing the European defense-industrial complex by financing innovative research, development and joint projects of international importance. The main objectives of the fund include increasing autonomy and competitiveness in the defense industry, as well as promoting integration and cooperation between the member states of the European Union. Within the framework of the article, each practice was analyzed, and conclusions have been drawn about what ideas from international practice could be applied in the development of the defense-industrial complex of the Russian Federation. The results of the study can be used by the Federal Assembly of the Russian Federation, the Government of the Russian Federation, the Ministry of Defense of the Russian Federation, the Foundation for Advanced Studies and other state structures and organizations that determine the policy in the field of defense industry regulation as proposals for further development of state support measures in the Russian Federation.

Predictability assessment of as-built hardness of Ti-6Al-4V alloy fabricated via laser powder bed fusion

Evaluating the predictability of selective laser melting (SLM) process has been a persistent endeavor in the manufacturing community since the technique’s inception. The ability to accurately predict the as-built hardness of fabricated parts is critical to judge its serviceability for specific applications. This investigation aims at achieving such predictability with as little as experimentation possible. In this research, reliable historical SLM data was mined on as-built Ti-6Al-4V alloy, from technical articles published over the past fifteen years. Three predictive models of Gaussian Process Regression (GPR), Neural Network (NN) and parametric Multiple Linear Regression (MLR) were built for as-fabricated bulk hardness of Ti-6Al-4V alloy manufactured via SLM. Ten-fold cross-validation training of the models involved a substantial 1,284 spatial datapoints of major SLM process parameters such as laser power, scanning speed, hatch spacing, layer thickness and volumetric energy density. Ultimate assessment of hardness predictability was performed by making predictions on ten cubic Ti-6Al-4V test coupons fabricated using a SLM machine. The GPR model stood out amongst other models, yielding a mean absolute prediction error of 6.12 HV over all samples. The overall predictability of these models came out to be in declining order of GPR > NN > MLR. Rudimentary characterization of test coupons revealed variation in observed hardness. Two tiers of robust validations, comprehensive dataset, statistical insights, actual experimental validation and material characterization make this study extremely unique for as-fabricated hardness of SLM-ed Ti-6Al-4V alloy.

Exploring the significant factors of reconfigurable manufacturing system adoption in manufacturing industries

PurposeA reconfigurable manufacturing system (RMS) can provide manufacturing flexibility, meet changing market demands and deliver high performance, among other benefits. However, adoption and performance improvement are critical activities in it. The current study aims to identify the important factors influencing RMS adoption and validate a conceptual model as well as develop a structural model for the identified factors.Design/methodology/approachAn extensive review of RMS articles was conducted to identify the eight factors and 47 sub-factors that are relevant to RMS adoption and performance improvement. For these factors, a conceptual framework was developed as well as research hypotheses were framed. A questionnaire was developed, and 117 responses from national and international domain experts were collected. To validate the developed framework and test the research hypothesis, structural equation modeling was used, with software tools SPSS and AMOS.FindingsThe findings support six hypotheses: “advanced technologies,” “quality and safety practice,” “strategy and policy practice,” “organizational practices,” “process management practices,” and “soft computing practices.” All of the supported hypotheses have a positive impact on RMS adoption. However, the two more positive hypotheses, namely, “sustainability practices” and “human resource policies,” were not supported in the analysis, highlighting the need for greater awareness of them in the manufacturing community.Research limitations/implicationsThe current study is limited to the 47 identified factors; however, these factors can be further explored and more sub-factors identified, which are not taken into account in this study.Practical implicationsManagers and practitioners can use the current work’s findings to develop effective RMS implementation strategies. The results can also be used to improve the manufacturing system’s performance and identify the source of poor performance.Originality/valueThis paper identifies critical RMS adoption factors and demonstrates an effective structural-based modeling method. This can be used in a variety of fields to assist policymakers and practitioners in selecting and implementing the best manufacturing system.Graphical abstract

Melt pool boundaries in additively manufactured AlSi10Mg: Correlating inhomogeneous deformation with local microstructure via in-situ microtensile tests

Microstructures in additively manufactured metals are often inhomogeneous and complex. Melt pool (MP) centers and boundaries can vary significantly, such as in AlSi10Mg, where MP boundaries reveal a coarsening and breakdown of the refined cellular network. However, bulk characterization techniques often lack the resolution to quantify the local deformation on the length scale of a melt pool boundary which ranges from 1 to 100 μm. Here, in-situ scanning electron microscopy (SEM) microtensile experiments on AlSi10Mg samples were used to compare the relative yield behavior and deformation uniformity throughout microstructural regions, particularly around the MP boundaries. Differences in the local mechanical response – deformation, strain hardening, and yield – are reported between the MP boundaries and centers. These differences in deformation are correlated to specific microstructural features like cell size, cell connectedness, cell eccentricity, and grain size. Quantitative correlations of local deformation with relevant microstructural features, as presented here, will aid modelers and the additive manufacturing (AM) community to more precisely predict and control AM AlSi10Mg part performance.

Machine Learning Techniques for Acoustic Data Processing in Additive Manufacturing In Situ Process Monitoring: A Review

There have been numerous efforts in the metrology, manufacturing, and nondestructive evaluation communities to investigate various methods for effective in situ monitoring of additive manufacturing processes. Researchers have investigated the use of a variety of techniques and sensors and found that each has its own unique capabilities as well as limitations. Among all measurement techniques, acoustic-based in situ measurements of additive manufacturing processes provide remarkable data and advantages for process and part quality assessment. Acoustic signals contain crucial information about the manufacturing processes and fabricated components with a sufficient sampling rate. Like any other measurement technique, acoustic-based methods have specific challenges regarding applications and data interpretation. The enormous size and complexity of the data structure are significant challenges when dealing with acoustic data for in situ process monitoring. To address this issue, researchers have explored and investigated various data and signal processing techniques empowered by artificial intelligence and machine learning methods to extract practical information from acoustic signals. This paper aims to survey recent and innovative machine learning techniques and approaches for acoustic data processing in additive manufacturing in situ monitoring.

Mechanism of material removal in tungsten carbide-cobalt alloy during chemistry enhanced shear thickening polishing

The use of cemented carbides is ubiquitous in many fields especially for mechanical toolings, dies, and mining equipment. Surface finishing of cemented carbide down to atomic level has been a long-standing quest in manufacturing and materials community. For application of complex-shaped cemented carbide components, this work proposes a novel ‘chemistry enhanced shear thickening polishing’ (C-STP) process using Fenton's reagent to obtain sub 10 nm finished polishing at a rate twice that of the conventional STP. This work offers quantitative insights into the influence of the concentration of Fenton's reagent on the polishing performance. While the material removal rate was seen to be sensitive to the concentration, the surface roughness (Sa) was found to be insensitive to the concentration of Fenton's reagent. The electrochemical experiments proved that Fenton's reagent could effectively reduce the corrosion resistance of tungsten carbide-cobalt alloy. The characterization of polished carbides using XPS and EDS revealed that the cobalt binder gets removed preferentially during C-STP, which explains why the material removal rate during this technique becomes twice that of conventional STP. This study provides a promising method for high efficiency polishing of tungsten carbide-cobalt alloy parts with complex-shaped such as micro-drill.

Influence of interface orientation and surface quality on structural and mechanical properties of SS316L/IN718 block produced using directed energy deposition

Functionally graded materials manufactured by additive manufacturing technologies reached high interest in additive manufacturing community over the last decades. High potential of additively manufactured multi-materials was demonstrated by many studies over the last 10 years. Most of the studies dealing with functionally graded materials had one common sign, which is the chemical composition gradient being controlled in the building direction of the final product. Hence, the multi-material interface is mostly situated in horizontal plane (XY) of the product. However, due to a complex geometry of the product, it is not always possible or desirable to achieve certain interface orientation and multi-material interface might incline from the ideal horizontal plane. Typically, corner zones, where interface orientation changes suddenly from horizontal to vertical orientation, are the most critical locations. Therefore, investigation of the interface orientation is important in order to establish the additive manufacturing limitation for certain applications. The current study revealed that the interface inclination has significant influence on the amount and distribution of formed defects at the materials interfaces. Furthermore, it was shown that the interface surface quality in terms of as-deposited surface or machined surface can significantly affects the defects formation. The effect of defects on the tensile specimen's elongation was significant, which based on the interface angle dropped over more than 70%.

Sticky Solutions

This article explores the agency of animal materiality, class, and context in shaping social values within wood research and manufacturing communities in mid-twentieth-century Japan, with a focus on animal glues (nikawa 膠) in relation to other adhesives. It relates the materiality and affordances of adhesives to their value within multiple technosocial contexts, in which glues made from mammalian skin, bones, and hooves remained the predominant adhesive within wood product manufacturing microenterprises but were being replaced by casein-, soybean-, and carbon-based adhesives in academic and corporate laboratories. Working primarily from research reports and consultation records compiled by industrial research institutes embedded within small-scale manufacturing communities, the article proposes that the materiality of animal glues and the larger assemblage of materials-energy-environment-tools-skill-knowledge present in, between, and around labs and workshops both rendered that materiality highly evident to human users and prompted them to value nikawa in highly divergent ways, depending on class and context. The affordances of animal-based glues, alongside those of plant- and carbon-based glues and other substances used with them in manufacturing, led different social groups to value them differently. The result was a bifurcation of value between adjacent but separate social groups, with workshop owners preferring to use animal glues, even as technical advisors labored to dissolve small workshop owners’ attachment or adherence to animal glues, and to prompt them to adopt newer, more “modern” adhesives as part of industrial rationalization and modernization. This paper is part of a special issue entitled “Making Animal Materials in Time,” edited by Laurence Douny and Lisa Onaga.

Investigation of Effect of Processing Parameters for Direct Energy Deposition Additive Manufacturing Technologies

In order to capitalize on the cost-effectiveness of additive manufacturing (AM), it is critical to understand how to build components with consistency and high quality. Directed energy deposition (DED) is an AM method for creating parts layer by layer through the use of a moving heat source and powder material inserted into the melt pool generated on the substrate. DED, like most AM processes, is highly complex due to the rapid thermal gradients experienced during processing. These thermal gradients are determined by a variety of processing parameters, which include laser power, powder feed rate, travel speed, layer height hatch spacing, etc. A lot of effort has been carried out in the additive manufacturing community to understand what these critical parameters are and how they influence the thermal gradients. Despite all these efforts, AM industries rely on a trial-and-error-based approach to find the right set of parameters to produce a quality part. This is time-consuming and not a cost-effective use of AM technology. The aim of our research is to reduce the amount of experimental data in combination with numerical analysis to optimize this relationship. Physics-based two-dimensional melt-pool modeling and experimental results from an OPTOMEC 850M LENS will be utilized to investigate the effects of processing parameters on melt-pool geometry, and the results from this study will provide key processing guidelines to achieve desirable clad geometry and powder efficiency for the DED method.

Defense Manufacturing Community Support Program (DOD)

Federal Grants & ContractsVolume 47, Issue 12 p. 3-4 Grants Alerts Defense Manufacturing Community Support Program (DOD) First published: 14 May 2023 https://doi.org/10.1002/fgc.33029Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL No abstract is available for this article. Volume47, Issue1218 May 2023Pages 3-4 RelatedInformation

Towards Data and Model Interoperability for Industrial Extended Reality in Manufacturing

Abstract Extended reality (XR) technologies have realized significant value for design, manufacturing, and sustainment processes. However, industrial XR, or XR implemented within industrial applications, suffers from scalability and flexibility challenges due to fundamental gaps with interoperability between data, models, and workflows. Though there has been a number of recent efforts to improve the interoperability of industrial XR technologies, progress has been hindered by an innate separation between the domain-specific models (e.g., manufacturing execution data, material specifications, and product manufacturing information) with XR (often-standard) processes (e.g., multiscale spatial representations and data formats optimized for run-time presentation). In this paper, we elaborate on promising research directions and opportunities around which the manufacturing and visualization academic community can rally. To establish such research directions, we (1) conducted a meta-review on well-established state-of-the-art review articles that have already presented in-depth surveys on application areas for industrial XR, such as maintenance, assembly, and inspection and (2) mapped those findings to publicly published priorities from across the US Department of Defense. We hope that our presented research agenda will spur interdisciplinary work across academic silos, i.e., manufacturing and visualization communities, and engages either community within work groups led by the other, e.g., within standards development organizations.

Comparing the flexural and morphological properties of dissimilar FFF-fabricated polymer composites

Additive manufacturing is becoming more and more significant for the production of engineering products. The global community of designers and manufacturers will undoubtedly benefit from identifying the process factors that could lead to superior mechanical behaviour. The incorporation of fibres and nanoparticles in polymer matrix is one of the most significant advancements in polymer fabrication. This study intends to investigate how the flexural behaviour of dissimilar polymer composites viz carbon fibre reinforced poly lactic acid (CF-PLA), carbon fibre reinforced poly ethylene terephthalate glycol (CF-PETG) and multi walled carbon nano tubes reinforced PLA (MWCNTs-PLA) are affected by process parameters viz nozzle diameter (0.2 mm, 0.4 mm, 0.6 mm), and infill pattern (triangular, honeycomb, rectilinear) through fused filament fabrication (FFF). Flexural testing was carried out on the fabricated specimens, and post to the testing, fractography has been carried out and statistical analysis of the observations is performed utilizing analysis of variance and Taguchi method. According to the observations, flexural strength of the polymer composite specimen increases with increase in nozzle diameter (ND). The flexural behaviour is also directly impacted with the variation of infill pattern (IP). Process parameter variations affect target factors differently depending on the fabricating material. For flexural behaviour, IP contributes 68.27% to CF-PLA, while ND contributes 88.96% to CF-PETG and 77.59% to MWCNTs-PLA. Overall, the highest flexural strength, 70.372 MPa, is exhibited by the specimen with ND 0.6 mm and rectilinear IP for MWCNTs-PLA as fabricating filament material. This study will aid researchers and designers in developing FFF-fabricated electrochemical energy storage devices with improved flexural behaviour of functional parts for a wide range of applications.

On the probabilistic prediction for extreme geometrical defects induced by laser-based powder bed fusion

Compared to traditional subtractive manufacturing processes, powder bed fusion (PBF) shows promise for making complex metal parts with design freedom, short development time, and environmental sustainability. However, there is a consensus within the additive manufacturing (AM) community that the random geometrical defects (e.g., porosity, lack-of-fusion) produced in PBF processes pose a great challenge to fabricating load-bearing parts, particularly under dynamic loading conditions. Therefore, it is imperative to quantify defect sizes and distributions to predict the critical, life-limiting defect size that significantly reduces fatigue life. This paper presents a comprehensive analysis of the defects induced by selective laser melting to quantify their sizes and statistical distributions. Then four cumulative distribution functions (i.e., Weibull, Gamma, Gumbel, and Lognormal CDFs) are leveraged and compared to predict the maximum defect size based on the principle of statistics of extremes. Both the peak over threshold (POT) approach and the block maxima (BM) approach are used for these predictions. The results show that the BM approach-based predictions for all CDFs to be much larger than the measured maxima while the POT approach-based predictions have less deviation. The Weibull and Gamma CDFs were best correlated to the data, measured by Pearson’s R correlation coefficient, while the Gumbel and Lognormal CDFs were also well correlated.