Additive manufacturing of biomedical implants: A feasibility assessment via supply-chain cost analysis

Complexity has been one of the focal points of attention in the supply chain management domain, as it deteriorates the performance of the supply chain and makes controlling it problematic. The complexity of supply chains has been significantly increased over the past couple of decades. Meanwhile, Additive Manufacturing (AM) not only revolutionizes the way that the products are made, but also brings a paradigm shift to the whole production system. The influence of AM extends to product design and supply chain as well. The unique capabilities of AM suggest that this manufacturing method can significantly affect the supply chain complexity. More product complexity and demand heterogeneity, faster production cycles, higher levels of automation and shorter supply paths are among the features of additive manufacturing that can directly influence the supply chain complexity. Comparison of additive manufacturing supply chain complexity to its traditional counterpart requires a profound comprehension of the transformative effects of AM on the supply chain. This paper first extracts the possible effects of AM on the supply chain and then tries to connect these effects to the drivers of complexity under three main categories of 1) market, 2) manufacturing technology, and 3) supply, planning and infrastructure. Possible impacts of additive manufacturing adoption on the supply chain complexity have been studied using information theoretic measures. An Agent-based Simulation (ABS) model has been developed to study and compare two different supply chain configurations. The findings of this study suggest that the adoption of AM can decrease the supply chain complexity, particularly when product customization is considered.

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Risk and Cost Analysis in Supply Chain Structure with Simulation

2009 International Conference on Business Intelligence and Financial Engineering ◽

10.1109/bife.2009.94 ◽

2009 ◽

Author(s):

Min Li ◽

Kin Keung Lai

Keyword(s):

Supply Chain ◽

Cost Analysis ◽

Chain Structure ◽

Supply Chain Structure

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Episodic supply chains at times of disruption

Supply Chain Management An International Journal ◽

10.1108/scm-11-2020-0595 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Christina Öberg

Keyword(s):

Supply Chain ◽

Additive Manufacturing ◽

Supply Chains ◽

Design Methodology ◽

Secondary Data ◽

Transformational Change ◽

Content Type ◽

Metal Additive Manufacturing ◽

Contemporary Technology ◽

Metal Additive

Purpose Additive manufacturing has been described as converting supply chains into demand chains. By focusing on metal additive manufacturing as a contemporary technology causing ongoing disruption to the supply chain, the purpose of this paper is to describe and discuss how incumbent firms act during an ongoing, transformational disruption of their supply chain. Design/methodology/approach Interviews and secondary data, along with seminars attracting approximately 600 individuals operating in metal additive manufacturing, form the empirical basis for this paper. Findings The findings of this paper indicate how disruption occurs at multiple positions in the supply chain. Episodic positions as conceptualised in this paper refer to how parties challenged by disruption attempt to reach normality while speeding the transformational disruption. Originality/value This paper contributes to previous research by theorising about episodic positions in light of a supply chain disruption. The empirical data are unique in how they capture supply chain change at the time of disruption and illustrate disruptive, transformational change to supply chains. The paper interlinks research on disruption from the innovation and supply chain literature, with contributions to both.

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Modeling and analysis of the on-demand spare parts supply using additive manufacturing

Rapid Prototyping Journal ◽

10.1108/rpj-01-2018-0027 ◽

2019 ◽

Vol 25 (3) ◽

pp. 473-487 ◽

Cited By ~ 5

Author(s):

Yuan Zhang ◽

Stefan Jedeck ◽

Li Yang ◽

Lihui Bai

Keyword(s):

Supply Chain ◽

Additive Manufacturing ◽

Spare Parts ◽

Production Optimization ◽

Arrival Process ◽

Powder Bed Fusion ◽

Content Type ◽

Modeling And Analysis ◽

Powder Bed ◽

On Demand

PurposeDespite the widespread expectation that additive manufacturing (AM) will become a disruptive technology to transform the spare parts supply chain, very limited research has been devoted to the quantitative modeling and analysis on how AM could fulfill the on-demand spare parts supply. On the other hand, the choice of using AM as a spare parts supply strategy over traditional inventory is a rising decision faced by manufacturers and requires quantitative analysis for their AM-or-stock decisions. The purpose of this paper is to develop a quantitative performance model for a generic powder bed fusion AM system in a spare parts supply chain, thus providing insights into this less-explored area in the literature.Design/methodology/approachIn this study, analysis based on a discrete event simulation was carried out for the use of AM in replacement of traditional warehouse inventory for an on-demand spare parts supply system. Generic powder bed fusion AM system was used in the model, and the same modeling approach could be applied to other types of AM processes. Using this model, the impact of both spare parts demand characteristics (e.g. part size attributes, demand rates) and the AM operations characteristics (e.g. machine size and postpone strategy) on the performance of using AM to supply spare parts was studied.FindingsThe simulation results show that in many cases the AM operation is not as cost competitive compared to the traditional warehouse-based spare parts supply operation, and that the spare parts size characteristics could significantly affect the overall performance of the AM operations. For some scenarios of the arrival process of spare parts demand, the use of the batched AM production could potentially result in significant delay in parts delivery, which necessitates further investigations of production optimization strategies.Originality/valueThe findings demonstrate that the proposed simulation tool can not only provide insights on the performance characteristics of using AM in the spare parts supply chain, especially in comparison to the traditional warehousing system, but also can be used toward decision making for both the AM manufacturers and the spare parts service providers.

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Additive manufacturing in the spare parts supply chain: hub configuration and technology maturity

Rapid Prototyping Journal ◽

10.1108/rpj-03-2017-0052 ◽

2018 ◽

Vol 24 (7) ◽

pp. 1178-1192 ◽

Cited By ~ 13

Author(s):

Siavash H. Khajavi ◽

Jan Holmström ◽

Jouni Partanen

Keyword(s):

Supply Chain ◽

Additive Manufacturing ◽

Spare Parts ◽

Content Type ◽

Local Manufacturing ◽

Efficiency And Effectiveness ◽

Industrial Operations ◽

Production Configuration ◽

Part Production

PurposeInnovative startups have begun a trend using laser sintering (LS) technology patents expiration, namely, by introducing LS additive manufacturing (AM) machines that can overcome utilization barriers, such as the costliness of machines and productivity limitation. The recent rise of this trend has led the authors to investigate this new class of machines in novel settings, including hub configuration. There are various supply chain configurations to supply spare parts in industrial operations. This paper aims to explore the promise of a production configuration that combines the benefits of centralized production with the flexibility of local manufacturing without the huge costs related to it.Design/methodology/approachThis study quantitatively examines the feasibility of different AM-enabled spare parts supply chain configurations. Using cost data extracted from a case study, three scenarios per AM machine technology are modeled and compared.FindingsResults suggest that hub production configuration depending on the utilized AM machines can provide economic efficiency and effectiveness to reduce equipment downtime. While previous studies have suggested the need for AM machines with efficiency for single part production for a distributed supply chain, the findings in this research illustrate the positive relationship between multi-part production capability and the feasibility of a hub manufacturing configuration establishment.Originality/valueThis study explores the promise of a production configuration that combines the benefits of centralized production with the flexibility of local manufacturing without the huge costs related to it. Although the existing body of knowledge contains research on production decentralization, research on various levels of decentralization is lacking. Using a real-world case study, this study aims to compare the feasibility of different levels of decentralization for AM-enabled spare parts supply chains.

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Chain Reaction

Mechanical Engineering ◽

10.1115/1.2018-oct1 ◽

2018 ◽

Vol 140 (10) ◽

pp. 30-35 ◽

Cited By ~ 1

Author(s):

Alan S. Brown

Keyword(s):

Supply Chain ◽

Additive Manufacturing ◽

Supply Chains ◽

Medical Devices ◽

Business Models ◽

Rolling Stock ◽

Industrial Equipment ◽

Special Report ◽

Chain Reaction ◽

The U.S

For 30 years, additive manufacturing has made all sorts of promises. Yet machines remained slow, materials expensive, and printers too inconsistent for critical parts. And additive was costly. Today, however, the technology is turning that past on its head. While additive manufacturing is usually the most expensive way to make any part, it makes economic sense for supply chains. Which is why manufacturers of everything from aircraft and rolling stock to appliances, industrial equipment, and medical devices are looking at 3-D supply chain solutions—as are the U.S. Marines and UPS. This special report looks at how additive manufacturing is disrupting business models and transforming supply chains.

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Performance tradeoffs for spare parts supply chains with additive manufacturing capability servicing intermittent demand

Journal of Defense Analytics and Logistics ◽

10.1108/jdal-08-2020-0016 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Kyle C. McDermott ◽

Ryan D. Winz ◽

Thom J. Hodgson ◽

Michael G. Kay ◽

Russell E. King ◽

...

Keyword(s):

Supply Chain ◽

Additive Manufacturing ◽

Production Capacity ◽

Spare Part ◽

Spare Parts ◽

Mixed Integer ◽

Network Configuration ◽

Intermittent Demand ◽

Content Type ◽

Demand Patterns

PurposeThe study aims to investigate the impact of additive manufacturing (AM) on the performance of a spare parts supply chain with a particular focus on underlying spare part demand patterns.Design/methodology/approachThis work evaluates various AM-enabled supply chain configurations through Monte Carlo simulation. Historical demand simulation and intermittent demand forecasting are used in conjunction with a mixed integer linear program to determine optimal network nodal inventory policies. By varying demand characteristics and AM capacity this work assesses how to best employ AM capability within the network.FindingsThis research assesses the preferred AM-enabled supply chain configuration for varying levels of intermittent demand patterns and AM production capacity. The research shows that variation in demand patterns alone directly affects the preferred network configuration. The relationship between the demand volume and relative AM production capacity affects the regions of superior network configuration performance.Research limitations/implicationsThis research makes several simplifying assumptions regarding AM technical capabilities. AM production time is assumed to be deterministic and does not consider build failure probability, build chamber capacity, part size, part complexity and post-processing requirements.Originality/valueThis research is the first study to link realistic spare part demand characterization to AM supply chain design using quantitative modeling.

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