The economics of additive manufacturing: Towards a general cost model including process failure

Ding, Jin; Baumers, Martin; Clark, Elizabeth A.; Wildman, Ricky

doi:10.1016/j.ijpe.2021.108087

Cited by 36 publications

(11 citation statements)

References 49 publications

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“…These processes add to the overall lead time and can significantly reduce the productivity of the AM process, mainly when producing multiple parts (Strange & Zucchella, 2017). Consequently, adopting AM in production lines requires further development and consolidation (Ding et al, 2021;Strange & Zucchella, 2017).…”

Section: Low Printing/production Pace With Currently Available Additi...mentioning

confidence: 99%

The benefits and barriers of additive manufacturing for circular economy: A framework proposal

Tavares

Ganga

Filho

et al. 2023

Sustainable Production and Consumption

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Section: Low Printing/production Pace With Currently Available Additi...mentioning

confidence: 99%

The benefits and barriers of additive manufacturing for circular economy: A framework proposal

Tavares

Ganga

Filho

et al. 2023

Sustainable Production and Consumption

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“…As mentioned in the introduction, there are many potential benefits of AM technology. These are, however, not easy to achieve, as illustrated by the many challenges to AM adoption described in the literature [12,13,14,26,34,40]. It could, however, appear that such challenges can be countered by the acquisition of knowledge from networks.…”

Section: The Role Of Am Knowledge Networkmentioning

confidence: 99%

“…The implementation of AM also involves several potential challenges, such as cost issues, low technical understanding, lack of operator skills, and unclearness about strategies for AM use [13,14,26,33]. To overcome challenges related to inadequate AM knowledge, firms may acquire this from external parties, such as consultants, research institutions, suppliers, and network organizations [53].…”

Section: Introductionmentioning

confidence: 99%

Knowledge networks for adoption of additive manufacturing: The role of maturity

Haug¹,

Jensen²,

Arlbjørn³

et al. 2022

Proceedings of the Annual Hawaii International Conference on System Sciences

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Additive manufacturing (AM) has had a significant impact on manufacturing processes in many industries. The implementation of AM technology, however, involves several knowledge-related challenges, particularly for small and medium-sized enterprises (SMEs). We explore this topic by developing a theoretical model with the hypotheses that acquiring AM knowledge from networks is associated with competitive advantages from AM, and that this relationship can partly be explained by AM maturity. We test our model through a survey of Danish manufacturing SMEs. The findings show that AM knowledge acquisition from networks is positively associated with competitive advantages from AM, where around 40 percent of this relationship is explained by higher AM maturity. Furthermore, the findings suggest that different types of knowledge networks have different effects on AM maturity and competitive advantages from AM.

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“…The main issues in the industrialization of technology are productivity [4] and quality assurance [5], along with the relatively high cost of production. Further, post-processing and total production processes are topics of discussion due to the high costs [6] and, to some extent, failed builds of components with difficult printability [7].…”

Section: Introductionmentioning

confidence: 99%

Metal Laser-Based Powder Bed Fusion Process Development Using Optical Tomography

Björkstrand,

Akmal,

Salmi

2024

Materials

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In this study, a set of 316 L stainless steel test specimens was additively manufactured by laser-based Powder Bed Fusion. The process parameters were varied for each specimen in terms of laser scan speed and laser power. The objective was to use a narrow band of parameters well inside the process window, demonstrating detailed parameter engineering for specialized additive manufacturing cases. The process variation was monitored using Optical Tomography to capture light emissions from the layer surfaces. Process emission values were stored in a statistical form. Micrographs were prepared and analyzed for defects using optical microscopy and image manipulation. The results of two data sources were compared to find correlations between lack of fusion, porosity, and layer-based energy emissions. A data comparison of Optical Tomography data and micrograph analyses shows that Optical Tomography can partially be used independently to develop new process parameters. The data show that the number of critical defects increases when the average Optical Tomography grey value passes a certain threshold. This finding can contribute to accelerating manufacturing parameter development and help meet the industrial need for agile component-specific parameter development.

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The economics of additive manufacturing: Towards a general cost model including process failure

Cited by 36 publications

References 49 publications

The benefits and barriers of additive manufacturing for circular economy: A framework proposal

The benefits and barriers of additive manufacturing for circular economy: A framework proposal

Knowledge networks for adoption of additive manufacturing: The role of maturity

Metal Laser-Based Powder Bed Fusion Process Development Using Optical Tomography

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