Maximizing design potential: investigating the effects of utilizing opportunistic and restrictive design for additive manufacturing in rapid response solutions

Prabhu, Rohan; Masia, Jordan S.; Berthel, Joseph; Meisel, Nicholas A.; Simpson, Timothy W.

doi:10.1108/rpj-11-2020-0297

Cited by 10 publications

(3 citation statements)

References 59 publications

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“…A feature of the design shown in Figure 9(C) in a cross-sectional cut through the blade is internal air-cooling channels. The ability to build internal structures into a component is hard to achieve by conventional metal processing but can be achieved by a realistic proposition with AM (Roca et al , 2016; Watkins et al , 2013; Prabhu et al , 2021). However, the as-built turbine blade [Figure 9(A)] demonstrates an important limitation of AM in relation to surface finish, as a rough surface finish introduces possible sites for crack initiation and propagation within the process [Figure 9(A)].…”

Section: Discussionmentioning

confidence: 99%

A review of Industry 4.0 and additive manufacturing synergy

Khorasani¹,

Loy

Ghasemi

et al. 2022

RPJ

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Purpose This paper reviews the synergy of Industry 4.0 and additive manufacturing (AM) and discusses the integration of data-driven manufacturing systems and product service systems as a key component of the Industry 4.0 revolution. This paper aims to highlight the potential effects of Industry 4.0 on AM via tools such as digitalisation, data transfer, tagging technology, information in Industry 4.0 and intelligent features. Design/methodology/approach In successive phases of industrialisation, there has been a rise in the use of, and dependence on, data in manufacturing. In this review of Industry 4.0 and AM, the five pillars of success that could see the Internet of Things (IoT), artificial intelligence, robotics and materials science enabling new levels of interactivity and interdependence between suppliers, producers and users are discussed. The unique effects of AM capabilities, in particular mass customisation and light-weighting, combined with the integration of data and IoT in Industry 4.0, are studied for their potential to support higher efficiencies, greater utility and more ecologically friendly production. This research also illustrates how the digitalisation of manufacturing for Industry 4.0, through the use of IoT and AM, enables new business models and production practices. Findings The discussion illustrates the potential of combining IoT and AM to provide an escape from the constraints and limitations of conventional mass production whilst achieving economic and ecological savings. It should also be noted that this extends to the agile design and fabrication of increasingly complex parts enabled by simulations of complex production processes and operating systems. This paper also discusses the relationship between Industry 4.0 and AM with respect to improving the quality and robustness of product outcomes, based on real-time data/feedback. Originality/value This research shows how a combined approach to research into IoT and AM can create a step change in practice that alters the production and supply paradigm, potentially reducing the ecological impact of industrial systems and product life cycle. This paper demonstrates how the integration of Industry 4.0 and AM could reshape the future of manufacturing and discusses the challenges involved.

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Section: Discussionmentioning

confidence: 99%

A review of Industry 4.0 and additive manufacturing synergy

Khorasani¹,

Loy

Ghasemi

et al. 2022

RPJ

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“…Sustainable supply chain emerges as a niche theme in this period and responsible innovation maintains its position in the emerging or disappearing themes. Thematic analysis revealed that the focus in the product development cluster is on additive manufacturing (AM), investigating AM adoption, and emphasizing inter-organizational collaboration (Luomaranta and Martinsuo, 2022), the need for balanced approaches to optimize creativity and efficiency (Blosch-Paidosh and Shea, 2021;Prabhu et al, 2021), and highlighting sustainability concerns related to environmental impacts (Gopal et al, 2023) and competitiveness (Turkcan et al, 2022). Such focus supports the shift towards a more specialized view of product development, positioning it in the more niche theme quadrant.…”

Section: Period 2021-2023mentioning

confidence: 99%

Scientometric exploration of responsible innovation: mapping the knowledge landscape

Fain,

Vukašinović,

Kastrin

2024

Proc. Des. Soc.

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While research into responsible innovation is not new, there have been recent calls to explore responsible product development, across different development stages and pillars of responsible innovation. In this paper, we use scientometric analysis to explore how the responsible innovation knowledge structure has evolved over the past 50 years. Our aim is to explore the relevance of the topic and propose future research orientations. Findings show that responsible innovation is an emerging topic warranting further investigation.

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“…A significant insight from Baumers et al (2017b) is that the expected impact of build failure is absent in most investigations on the cost of AM. The existing literature investigating build failure in AM is divided into four categories, including software-based simulation (Bresson et al, 2022;Chakraborty et al, 2022;Ge & Flynn, 2022), design optimization (Misiun et al, 2021;Prabhu et al, 2021;Xu et al, 2022), data-based estimation (Jirandehi et al, 2022;Wang et al, 2021), and mechanism exploration (Osswald et al, 2021;Roh et al, 2021). However, the impact of build failure on the environmental performance of AM, in terms of both process energy consumption and the energy embedded in the used raw materials, has not yet been investigated directly and in combination.…”

mentioning

confidence: 99%

The impact of the risk of build failure on energy consumption in additive manufacturing

Wang

Baumers

Basak

et al. 2022

J of Industrial Ecology

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Additive manufacturing (AM), also known as 3D printing, is associated with significant promise in the manufacturing sector. However, it has been shown that the risk of build failure has a substantial impact on the costs of AM and that this results from a relatively high level of process instability. Importantly, for such a promising technology, the effects of the risk of build failure on energy consumption have not yet been studied, which creates a significant gap in the knowledge of the real environmental performance of AM. This research addresses this gap by investigating the energy consumption of AM subject to the possibility of build failure. This is done by constructing a novel expected energy consumption model, integrating process energy consumption, the energy embedded in the raw material, and the probability of build failure as a function of the number of layers deposited. Model parameters are obtained from a series of build experiments conducted on the AM technology variant polymeric laser sintering, also known as laser powder bed fusion of polymers. The energy consumption model shows that the risk of build failure accounts for a substantial share of overall expected energy consumption, amounting to up to approximately 31% at full capacity utilization. Additionally, this paper uncovers a complex relationship between the risk of build failure and efficiency gains in per unit energy consumption resulting from increasing levels of capacity utilization (Supporting Information S1).

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Maximizing design potential: investigating the effects of utilizing opportunistic and restrictive design for additive manufacturing in rapid response solutions

Cited by 10 publications

References 59 publications

A review of Industry 4.0 and additive manufacturing synergy

A review of Industry 4.0 and additive manufacturing synergy

Scientometric exploration of responsible innovation: mapping the knowledge landscape

The impact of the risk of build failure on energy consumption in additive manufacturing

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