Additive manufacturing : determinants of adoption and effects on global value chain participation. A country-level analysis

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Supervisor:

Lucia Piscitello

Co-Supervisor:

Giulia Felice

School of Industrial and Information Engineering Master of Science Degree in Management Engineering

Academic Year 2016-2017

ADDITIVE MANUFACTURING:

DETERMINATS OF ADOPTION AND EFFECTS ON

GLOBAL VALUE CHAINS PARTICIPATION.

A COUNTRY-LEVEL ANALYSIS.

Alessandro Cavedagna - 858644

Fabio Lamperti - 853123

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List of Figures

Chapter 1

Figure 1.1. Hype Cycle curve for 3DP ... 23

Figure 1.2. Geographic distribution of worldwide total AM capacity ... 24

Figure 1.3. Changes in industry adoption between 2014 and 2017 ... 25

Figure 1.4. The 3DP process ... 27

Figure 1.5. Digital model creation steps ... 28

Figure 1.6. The SLA process. ... 33

Figure 1.7. The DLP process. ... 34

Figure 1.8. The CLIP process. ... 35

Figure 1.9. The SLS, SLM and DMLS processes. ... 37

Figure 1.10. The FDM and FFF processes. ... 39

Figure 1.11. The MJM and PJM processes. ... 40

Figure 1.12. The Inkjet Z Corporation process. ... 42

Figure 1.13. The LOM process. ... 43

Figure 1.14. The LMD and LENS processes. ... 45

Figure 1.15. Final applications of AM systems ... 46

Chapter 2 Figure 2.1. Porter’s Value Chain ... 50

Figure 2.2. Conceptual framework of the Smile Curve ... 68

Figure 2.3. Current state of ideal GVC restructuring following each unbundling ... 74

Chapter 3 Figure 3.1. Summary of the works, and related authors, presented in Chapter 3. ... 79

Figure 3.2. Accounting of Gross Exports: Concepts ... 92

Figure 3.3. Decomposition of GDP by industry ... 96

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Figure 3.5. Index system for production length ... 105 Figure 3.6. Number of border crossing and the GVC production length index system .... 107 Figure 3.7. Value chains for Chinese exports of electrical and optical equipment ... 113 Figure 3.8. Participation mode, value generation and supply chains in the EU ... 116 Chapter 4

Figure 4.1. Comparison between granted patents and patent applications on AM, from 1984 to 2017. ... 125 Figure 4.2. Granted patents on AM, by country, from 1984 to 2017... 127 Figure 4.3. Comparison between AM-related patents produced in the US and the sum of AM patents data from all the other inventor countries, from 1984 to 2017. ... 128 Figure 4.4. Number of patents on AM produced in the six most active countries excluding the US, from 1984 to 2017. ... 129

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List of Tables

Chapter 1

Table 1.1. AM material and technology combinations ... 30

Chapter 3 Table 3.1. Schematic outline of Input-Output Tables ... 84

Table 3.2. World Input-Output Table (WIOD), three regions example ... 86

Chapter 4 Table 4.1. Summary of research queries on USPTO Database. ... 124

Table 4.2. Number of AM-related granted patents, by country (up to date: 2017, October 15th). ... 126

Table 4.3. Regression results on the main determinants of AM adoption. ... 133

Table 4.4. Descriptive statistics of AM adoption proxy and its main determinants. ... 134

Table 4.5. Correlation coefficients of AM adoption proxy and its main determinants. ... 137

Chapter 5 Table 5.1. Descriptive statistics of the variables used to assess the impact of AM technologies on GVC participation. ... 153

Table 5.2. Regression results on potential determinants of GVC participation (Share of Re-Exported Inputs on Total Imported Inputs)... 154

Table 5.3. Regression results on potential determinants of GVC participation (Domestic Value Added in Exports as a Share of a Country’s Exports). ... 155

Table 5.4. Results from regression model to test the impact of AM adoption on GVC participation (Domestic Value Added in Exports as a Share of a Country’s Exports). ... 158

Table 5.5. Results from regression model to test the impact of AM adoption on GVC participation (Share of Re-Exported Inputs on Total Imported Inputs). ... 160

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Table 5.6. Correlation coefficients of GVC participation indicators, their determinants and AM adoption proxy. ... 161 Appendix 1

Table A.1.1. Regression results on the main determinants of AM adoption (Random Effects Negative Binomial). ... 165 Table A.1.2. Regression results on the main determinants of AM adoption (Random Effects Probit). ... 166 Appendix 2

Table A.2.1. Industry breakdown for the 2016 Trade in Value Added (TiVA) indicators. .... 167 Appendix 3

Table A.3.1. Comparison between average country score for CTOTAL in Domestic Value Added in Exports as a Share of a Country’s Exports and Share of Re-Exported Inputs on Total Imported Inputs, over period 2000 – 2011. Comparison index in Columns IV and VIII are calculated using the formula (100 – EXGR_DVASH – IMGRINT_REII). ... 168 Table A.3.2. Average country score for CTOTAL, C28, C29 and C34 in Domestic Value Added in Exports as a Share of a Country’s Exports, over period 2000 – 2011. ... 169 Table A.3.3. Average country score for CTOTAL, C28, C29 and C34 in Share of Re-Exported Inputs on Total Imported Inputs, over period 2000 – 2011. ... 170

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Abstract (English Version)

Additive Manufacturing (AM) has the potential to revolutionise the organisation of all the activities carried out by firms. The growing diffusion of this technologies is increasingly challenging small and medium firms, as well as Multinational Enterprises (MNEs), to reinvent their business models. Since AM is forecasted to go mainstream within few years, many scholars argue on its effect on Global Value Chains (GVCs) too. Even if it has already disrupted industries like Aerospace, Automotive and Life Sciences, the lack of available data on the real worldwide diffusion of this technologies has precluded the possibility to study this phenomenon from an empirical standpoint, so far.

This study investigates the AM technologies and their potential role within the current conversation in the International Business field, with a particular focus on its possible impact on GVCs. The first section of the work encompasses a rigorous review of the existing literature on both AM technologies, GVCs and the existing literature on the relationship between them. In order to test our theoretical hypothesis and to overcome the lack of diffusion data, the second part identifies a reliable proxy of AM adoption – i.e. patenting activity - and its country-level determinants. The third section of the dissertation develops an econometric model to examine the role of AM in influencing countries’ participation to GVCs. To do this, we rely on two measures of GVC participation: i) Domestic Value Added in Exports

as a Share of a Country’s Exports; and ii) Share of Re-Exported Inputs on Total Imported Inputs; both tested using our AM adoption proxy and a set of GVC

determinants. Our country-level analysis is focused on 3 specific industries, in 62 countries for the period 2000 – 2011.

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Our results contribute to the strand of literature supporting that AM fosters a country’s decreasing participation in GVCs. The empirical evidence suggests that this phenomenon is caused by a decreasing reliance on intermediates processed abroad, hence an increasing importance of domestic goods, manufactured via AM.

Key Words: Additive Manufacturing, 3D Printing, Global Value Chains, GVC

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Abstract (Italian Version)

La Manifattura Additiva (MA) ha il potere di rivoluzionare l'organizzazione di tutte le attività svolte dalle imprese. La crescente diffusione di questo insieme di tecnologie sta spingendo sempre di più le piccole e medie imprese e le aziende multinazionali a reinventare i propri modelli di business. Dal momento che la MA diventerà una delle tecnologie di riferimento negli anni a venire, il suo impatto è destinato a ripercuotersi sulle Catene Globali del Valore (CGV). Anche se queste tecnologie hanno già profondamente cambiato settori come l'aerospaziale, l'automobilistico e le scienze sanitarie, la mancanza di dati disponibili sulla loro reale diffusione a livello mondiale ha fino ad ora precluso la possibilità di studiare questo fenomeno da un punto di vista empirico.

Questo studio analizza le tecnologie additive e il loro ruolo all'interno dell'attuale dibattito nel campo dell’International Business e, in particolare, la loro influenza sulle CGV. La prima parte del lavoro comprende una rigorosa revisione della letteratura sia sulla tematica delle tecnologie additive, che su quella delle CGV. Al fine di far fronte alla mancanza di dati riguardanti la diffusione, la seconda parte identifica la produzione di brevetti come una proxy affidabile di adozione della MA, e individua le sue determinanti di paese. La terza parte di questo lavoro descrive un modello per analizzare l’influenza della MA sul livello di partecipazione dei paesi alle CGV. A questo scopo, vengono proposte due misure di partecipazione CGV: i)

il valore-aggiunto nazionale nelle esportazioni come quota delle esportazioni di un paese; e ii) la quota di input riesportati sul totale degli input importati; entrambe

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CGV. L’ analisi si concentra su 3 settori specifici, in 62 paesi, per il periodo 2000 – 2011.

I nostri risultati contribuiscono al filone della letteratura a sostegno dell’ipotesi secondo cui la MA favorisca la diminuzione della partecipazione di un paese alle CGV. Le evidenze empiriche suggeriscono che questo fenomeno è causato da una diminuzione della dipendenza da prodotti intermedi esteri, quindi da un crescente utilizzo di beni domestici, fabbricati tramite MA.

Parole Chiave: Manifattura Additiva, Stampa 3D, Catene Globali del Valore,

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Executive Summary

This dissertation focuses on the disruptive potential of Additive Manufacturing (AM) technologies. Thanks to its flexibility, high customisation potential and cost savings, AM is believed to revolutionize the way production of goods is performed. However, along with several new opportunities, the adoption of these technologies brings also a wide set of challenges for adopters in every country and industry. According to some scholars, this change has already started, and it is going to reshape the organization of firms and Multinational Enterprises, hence their role in Global Value Chains (GVCs). Some other academics are more conservative on the possible impact that AM could have, given the adoption hurdles these technologies imply. These contrasting opinions are fostering the actual debate around the International Business’ implications of AM.

This work wants to shed a first light on which of the above-cited opinions is going to prevail in the future, addressing the question: how will AM technologies

impact Global Value Chains?

To provide an answer, after a rigorous review of the literature, we structured this study in two sections. The first one provides an in-depth investigation of the determinants of AM adoption, assessing which are the country-specific factors favouring this phenomenon. The second one explores the relationship between AM adoption and country participation to GVCs.

Chapter 1 of this thesis addresses the description of the AM, both in the

hardware and software dimensions. It is noteworthy that this innovation is compatible with a wide range of materials and it efficiently carry out complex shapes (e.g. hollow objects). Furthermore, allowing to produce any Computer Aided Design (CAD) model with a single device, and enabling to economically unbundle

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production locations, AM makes economies of scale irrelevant for a wide range of goods. This disruptive potential induced many economists to claim that “economies of scale are dead”. However, there are technical barriers (e.g. long lead times, rough surface finishing) which still remain to be addressed. Furthermore, the typical AM production costs for standard consumer goods are still not comparable with those associated to production in series. Thus, AM is suitable for those products for which personalization is a competitive factor.

In Chapter 2, we analyse the present and future effects that this technology has on firms’ operations. While current applications of AM are mainly in the R&D, this technology can potentially affect the different activities that are described in the Porters’ Value Chain. We especially focus on logistics and production due to the potentially high impact that AM can have on these two stages. Specifically, production can be affected in terms of location choices (e.g. re-shoring), logistics in terms of reduction in the flow of goods (i.e. sharing of file rather than physical goods). For this reason, adopting this kind of technology can lead to changes in inter-country trade relationships led by Multinational Enterprises. The framework used to explore this phenomenon is the GVC as represented by the “Smile of the Value Chain” (Shih, 1992). According to its traditional conceptualization, the activities providing the higher value-added are those positioned at the extremes of the Value Chain (i.e. upstream activities: design and R&D; downstream activities: marketing and sales) which are also those located in high income countries. AM can potentially undermine this view.

Chapter 3 presents a literature review on GVCs, and the history of metrics of

country participation in them. Empirical studies on GVCs have been gathering an increasing attention in the world of International Business stimulating contributions on both the fields of data analysis (e.g. Timmer et al., 2014; Stehrer, 2012) and metrics formulation (e.g. Koopman et al., 2014; Johnson & Noguera, 2012; Antràs et al., 2012; Dietzenbacher et al., 2005; Hummels et al., 2001). Through this review, we

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aim to highlight strengths this section aims to highlight strengths and weaknesses of these models proposed to analyse this complex phenomenon.

In Chapter 4 we rely upon the methodology suggested by Abeliansky, Martinez-Zarzoso and Prettner (2016) to build an indicator of country-level AM diffusion, which refers to the innovation activity, as measured by patent data.

This part of the research concerns the country-level determinants of the innovative ferment around AM. Specifically, drawing from the relevant literature (Furman, Porter & Stern, 2002; Ginarte & Park, 1997), we derive that potential country-level determinants of AM technology adoption – as measured by patenting activity, are: the level of connectivity, the level of property-rights protection, the cumulated stock of R&D investments, the export share of hi-tech products.

These hypotheses are tested through a regression model on a panel database including 214 countries from 1996 to 2015. Starting from the specificities of data gathering, we describe the observations and explain the rationale which lead us to use specific regression models. In order to deal with count data, we select the Negative Binomial regression model with year dummies, clustering for country-specific errors.

Our results, confirm the afore-mentioned set of determinants to be significant and robust factors influencing AM adoption.

In Chapter 5, we investigate the topic of GVC participation in terms of main determinants and the impact of AM. Namely, in this chapter we test the validity of our research hypothesis:

“Additive Manufacturing influences country-level participation in a Global Value Chain by fostering vertical integration and disembodying adopters from trade in intermediate goods.”

First, relying on the literature described in Chapter 3, we select two historical measures of GVC participation: Domestic Value Added in Exports as a Share of a

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taken from the OECD-World Bank Trade in Value Added (TiVA) database. Afterwards, we identify a basic set of potential country-level determinants of GVC participation following the work by Taglioni and Winkler (2015). The significance of these factors is tested using a Fixed Effect regression model with year dummies. In particular, we deploy a panel encompassing 62 countries over 12 years, from 2000 to 2011. We run the model for the whole economy and for three specific sectors separately – i.e. fabricated metal products, machinery and equipment and motor vehicles, trailers and semitrailers. These sectors are chosen because they are particularly subject to AM technology (Laplume, Petersen & Pearce, 2016).

The outcomes of these regressions suggest that variables affecting GVC participation are: Investments in logistic infrastructures, School enrolment in tertiary

education and Connectivity index.

Finally, we included our AM adoption proxy – i.e. patenting activity, in the afore-described model in order to probe the relationship between this technology and GVC participation.

Our results suggest that, for the three cited sectors, a greater AM presence is correlated with a lower level of GVC participation. These findings provide some preliminary evidence on the disruptive potential that AM may have in reshaping trade relationships among countries, and certainly open the way to future investigations.

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CHAPTER 1: Introduction to Additive Manufacturing

Additive Manufacturing (AM) is rapidly emerging as a new and disruptive manufacturing technology that has major implications for companies and industries. As a hyper-flexible production technique providing highly customized and personalized products it has an enormous potential, although it also implies important and necessary changes in the business model of companies (i.e. in the logic of creating and capturing value). These changes bring a new set of opportunities and challenges not only for the top management of firms which decide to adopt this new technology, but also for all the other players in the economic world. In the following chapter, we try to depict a complete picture of what AM is, presenting the evolution of the technology, a precise description of the production methods developed so far and the related applications.

1.1. What is Additive Manufacturing

AM technology is defined as “the process of joining materials to make objects from 3D model data, usually layer upon layer, as opposed to subtractive manufacturing methodologies, such as traditional machining” (ASTM International, 2012). The term “3D Printing” (3DP) is commonly used as a synonym for AM, but it is somewhat inexact: the former is commonly adopted to define not only the technology itself, but also specific printing technologies, such as the “Fused Deposition Modelling”. The latter, on the other hand, is broader since it refers to any professional production technique which clearly distinguishes itself from conventional manufacturing methods, based on subtractive processes in which the

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unnecessary material is milled away until the final shape is obtained (Laplume, Petersen & Pearce, 2016). Simply said, the functioning of a standard 3D printer is quite similar to that of a traditional 2D inkjet printer, as both involve information to be printed from a digital file. While classic printers apply ink to paper, 3DP devices operate a transformation on materials in order to build a three-dimensional solid object. In this way, AM is used to directly produce finished products and parts, or in indirect processes in combination with traditional manufacturing techniques.

Even if AM is impressively gaining momentum, it is however neither a new technology nor a commonly adopted one. It first appeared in 1983, when an engineer named Chuck Hall printed a cup using a system where light was shone into a vat of photopolymer – a material which changes from liquid to plastic-like solid when light shines on it – and traces the shape of one level of the object. Subsequent layers are then printed until it is completed (Hickey, 2014). The system was patented three years later and improvements in technology led to the development of 3DP devices, coming into commercial use in 1988. Starting from the early 1990s, AM technologies began to be used to quickly manufacture prototypes. In fact, the capability of making physical objects in a short time directly from virtual Computer Aided Design (CAD) data helps to cut down the production development step. Nowadays, the fabrication of conceptual, as well as functional, prototypes in a wide variety of materials, is widespread in many industries; however, during all this time – and coming to early 2000s, 3DP has evolved within the boundaries of the R&D departments of a small oligopoly of firms (e.g., 3D Systems, zCorp, Stratasys, and Objet Geometries), leading to some variations in terms of resolution, colour availability, and time required for printing (Laplume, Petersen & Pearce, 2016). All this started to change in 2005, when Adrian Bowyer, a professor of mechanical engineering at University of Bath (UK), launched an open-source 3D printer project called the “RepRap” (self-replicating rapid prototyper) (Bowyer, 2014; de Jong & de Bruijn, 2013; Jones et al., 2011; Sells, Bailard, Smith & Bowyer, 2010). The process used in RepRap 3D printers is called “Fused Filament Fabrication”, just to avoid trademark

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infringement towards the Fused Deposition Modelling process. The goal of the RepRap project was to create a 3D printer capable not only of printing various products but also of replicating itself. Recent versions of the RepRap can print approximately 50% of their own parts, dramatically reducing costs (Pearce, 2015). Bowyer made the design of his creation available for free under the GNU General Public License1_{. As soon as this device was freely accessible, adoption started to take}

off and a research community made of 3DP users, based on the “Open Innovation” paradigm, started to flourish. When the core patent for the technology used in the RepRap expired in 2009, hundreds of derivative innovations created by individuals and companies started to flourish all over the world. Dozens of new companies offering open-source printers appeared, and many of them gathered funding from crowdsourcing platforms, such as Kickstarter and Indiegogo. Moreover, between 2009 and 2013, the RepRap printers and similar ones drove down the market cost of 3D printers to USD 1,000 and even less. Such a price was lower than one tenth of the cost of other 3D printers offered by incumbents, at the time. This forced major firms to offer lower-cost 3D printers, printing in plastic materials in a limited fashion, in order to compete in RepRap’s market segment. However, many of the AM technologies needed to build better and less expensive machines are still being protected by patents. For example, laser patents owned by incumbents of the 3DP industry make it difficult for engineers and researchers to experiment on technologies other to the RepRap one’s.

While waiting for other key patents for AM technologies – especially for those able to print metals – to expire, 3DP is becoming increasingly used in a large number of sectors. The technology is sky-rocketing due to recent advances in printing speed, capabilities and lower prices of printers, the latter being partly driven

1_{GNU General Public License (GNU GPL or GPL) is a free software license. It is widely used since it}

guarantees end users the freedom to run, study, share and modify the software (Free Software Foundation , 2016).

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by the expiration of a number of patents. In 2014, the global 3DP market for hardware, supplies, and services was valued at USD 4.5 billion, but is predicted to increase to USD 17.2 billion by 2020 (A.T. Kearney, 2015). The consultancy firm McKinsey estimates 3DP market to grow up to USD 490 billion by 2025. Having a look at the news, industry analyses and reports from consultants, hundreds of different forecasts and projections about the future size of the AM market are presented. In this scenario of expectations and ferment, it is somehow difficult to assess which are the most accurate ones. For this reason, only few estimates are reported, in order to give a sense of the potential sought in the technology by different actors.

Briefly addressing the issue of technology evolution, the well-known IT advisory company, Gartner, believes that enterprise AM technologies are ready to achieve a widespread adoption. As illustrated in the 2015 Gartner’s annual “Hype

Cycle” of emerging technologies, Enterprise 3DP is increasingly accelerating to

maturity. Over the past five years, it has successfully moved from being a nascent technology to reaching the cusp of the “Plateau of Productivity”, signalling that mainstream adoption is starting to take off. In contrast, Consumer 3DP is still at the “Peak of Inflated Expectations” and will require more time before it reaches mass adoption (DHL, 2016). Figure 1.1 reports a complete view of the different application fields for AM, as well as their positioning on the curve by Gartner. As one can notice, a whole set of other crucial applications of 3DP is still experiencing early phases of the Hype Cycle: IPR in 3DP, Industrial 3DP and 3DP in Supply Chain – nowadays considered among the most relevant in terms of potential future impact on the global economic system – are climbing the Peak of Inflated Expectations, meaning that, right now, they are gathering much attention from the academic and business world. Anyway, the real impact that all these promising applications of AM technologies are going to have will be likely assessed in the years to come.

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Figure 1.1. Hype Cycle curve for 3DP. Source: Gartner (2015).

Evidently, the technology is developing and spreading at a fast pace, and more and more companies are starting, or at least considering to, use the technology (Magnus, 2016). As shown in the annual survey by the US based consulting firm Wohlers Associates, Inc. – which has a 30-year experience in the world of AM – this proliferation trend has already begun almost a decade ago and it is continuously gaining strength on each of the relevant dimensions of “geography”, “industries” of adoption and “applications” of the technology. In 2014’s Wohlers annual survey respondents included 29 manufacturers of professional-grade, industrial AM systems (those that sell for USD 5,000 or more) and 82 service providers worldwide (Wohlers Associates, Inc., 2014). Starting from the data provided in the survey, Wohlers Report presents estimates on cumulative totals of AM systems installed by country from 1998 to the end of 2013, excluding data related to used system sales (so that machines are not counted two or more times).

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percentage. The United States, being the place in which the technology was initially developed, lead the global distribution of players in the industry.

Figure 1.2. Geographic distribution of worldwide total AM capacity. Source: Wohlers Associates, Inc. (2014).

The survey also asked each company to indicate which industries they serve and the approximate revenues (as a percentage) that they receive (Wohlers Associates, Inc., 2014). Since more data were publicly available with respect to industry adoption, comparative observation can be carried out with respect to evolution trends between 2014 and 2017. As it can be seen from Figure 1.3, in latest years the overall distribution of industry adoption changed: Aerospace sector has experienced a strong increase, whereas other industries, like Motor vehicles and Consumer products/electronics, fell in percentage. Nevertheless, it is worth observing that, as the AM industry developed much in the last years, the share of revenues coming from these industries increased in absolute terms, even if the percentage weight has decreased. Data presented in the 2014 and 2017’s releases of the report confirm what just presented, reporting a jump from the USD 3.07 billion of revenues at the end of 2013, to the USD 6.06 billion registered in the year ended on December 31, 2016 (Wohlers Associates, Inc., 2017; Wohlers Associates, Inc., 2014).

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Figure 1.3. Changes in industry adoption between 2014 and 2017. Source: Wohlers Associates, Inc. (2017, 2014).

Survey’s results regarding the applications of the AM technology are reported in Section 1.3, also providing a deeper focus on main industrial applications. In recent years, 3DP has been capturing the imagination of everyone from entrepreneurs to hobbyists. Most engineers and even executives are starting to realize that this technology is moving well beyond the immediate prototyping application: there is growing hype and excitement that 3DP can potentially revolutionize the manufacturing world. Already today, leading companies eager to be first-mover winners in an AM future have begun to leverage on this technology, demonstrating inspiring applications across a range of industries (DHL, 2016). By committing to big investments, some players are already betting on the future success of AM technologies for their businesses. In 2016, Mercedes-Benz Truck announced its first 3D-printed spare parts service, HP launched its first 3D printers’ product line, and GE, BMW and Nikon made a multimillion dollar investment in the 3DP start-up Carbon (Vanian, 2016). The implications of this potentially disruptive technology have been recognised not only by the academic and industrial worlds, but even by governments. In the past few years, institutions from all over the world started to realise the impact that AM can have on the economic system if used as a “weapon” in the hands of policy makers. In June 2011, President Obama launched the Advanced Manufacturing Partnership (AMP), a plan to bring together industry, universities, and the US federal government to invest in emerging technologies, including 3DP. Initially, a budget of USD 500 million was set to jumpstart the

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government’s plan (The White House: Office of the Press Secretary, 2011). Again, in the US, in 2013, the America Makes program – a public-private partnership – was lunched with USD 90 million in funding: USD 30 million from the federal government and the rest from the business and non-profit sectors (Ford, 2014). In the rest of the industrialized world economies, China, Singapore, and some countries in the European Union have committed hundreds of millions of USD to develop and commercialize 3DP systems. China, for example, has been investing in AM since the early 1990s, and the Chinese government, in 2013, has pledged 1.5 billion yuan (USD 245 million) to a seven-year project to advance in technology development (Ford, 2014). In Europe, Germany is leading the game on AM and other emerging industrial technologies with the government’s investment program “INDUSTRIE 4.0” started in 2010 and providing EUR 200 million (European Parliament, 2015). Moreover, in 2014 the EU lunched the six-years “Horizon 2020 Research Programme”, providing almost EUR 80 billion for research and innovation, including support to the development of key enabling technologies (European Parliament, 2015).

The observed rise in AM investments and adoption is a signal that a growing number of firms are beginning to realize the major economic advantages of 3DP technologies compared to conventional manufacturing techniques. These advantages open up to the possibility for new business models and services based on 3DP. For example, the US hearing aid industry converted to 100% to AM in less than 500 days, and not one company that stuck to traditional manufacturing methods survived (D'Aveni, 2015). With reports of such a disruptive change, it can be easily said that 3DP has moved beyond its early success, and the results of an acceleration in the innovation cycle for the technology is now being applied in the manufacture of a wide array of products.

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1.2. Technology Review

In this section, we analyse how AM technology works in practice. To do this, firstly we describe each of the basic components necessary to create a 3D printed object. Secondly, a detailed description of the different production techniques classified as AM is presented.

The three basic ingredients, for the 3D “creation” of a product, are: 1. A digital model: the digital representation of an object.

2. Feed material: the material used to manufacture the final object.

3. A 3D printer: the hardware used to create the solid object out of the digital model and feed material.

Figure 1.4. The 3DP process. Source: DHL (2016).

1.2.1. The Digital Model

Any AM device or 3D printer starts the “building” process from a digital design of the part to be produced. The 3D model is usually created using a Computer Aided Design (CAD) software that measures thousands of cross-sections of the object, precisely determining how each layer is to be constructed. Nowadays, CAD model can be created using a 3D scanner to make a three-dimensional digital copy of the selected object. These scanners can leverage on different technologies to generate the 3D model needed. Some examples are: spatially modulated structured light, volumetric scanning and time-of-flight sensors. Recently, companies like Microsoft and Google enabled their hardware to perform 3D

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scanning, for example Microsoft’s Kinect. In the near future, digitising real objects into 3D models is expected to become mainstream. CAD software solutions were born during the Computer Numerical Control (CNC) revolution of the 1980s but, as of today, there is not a comprehensive and completely dedicated software package for AM machines yet. Nevertheless, 3DP devices of any kind can seamlessly integrate both with commercial programs by, for example, SolidWorks, SolidEdge, Autodesk, and with free-to-use design tools such as Blender, Tinkercad and Google SketchUp. Till some years ago, at the end of the object design process, the resulting file needed to be uploaded into a specialized software in order to slice this model into cross-sectional layers, creating an STL (Surface Tessellation Language, an industry-standard format) or similar type of file. Nowadays, instead, designers’ work can be saved in the STL format directly using a traditional CAD software. When the 3D model is sliced, it is ready to be fed into the 3D printer. This can be done via USB, SD or Wi-Fi, it depends on the specific brand and type of device used. When a file is uploaded in an AM machine, the object is ready for production: the device reads every slice – every 2D image – and creates a three-dimensional object.

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1.2.2. Feed Material

Materials available for AM production processes are just a little fraction of the whole range of materials used in traditional manufacturing techniques (e.g., polymers, metals, and ceramics). This represent one of the biggest challenges to a widespread adoption of AM. Nevertheless, every year new materials are advanced in AM, resulting in better microstructures, and enhanced material tolerability (Aliakbari, 2012). As of today, the major categories of AM materials are:

• Polymers: the most widely used material in AM. Nylon is the most widely

used polymer because it melts and bonds better than other polymers (Guo & Leu, 2013);

• Composites: combinations of two or more materials, either naturally (in

nature) or engineered. Composites can be mixed uniformly or non-uniformly to make different compounds (Guo & Leu, 2013);

• Metal products: they can be formed in a “direct” way – by melting metal

particles together or an “indirect” way – by bonding the metal with post-processing. There are many ways and AM methods to form metals through the indirect or direct way (Guo & Leu, 2013);

• Functionally graded materials: one example is a pulley that contains more

carbide near the hub and rim to make it harder and more wear resistant, and less carbide in other areas to increase compliance (Guo & Leu, 2013);

• Ceramics: because of their chemical structures and resistance to high

temperatures. Unfortunately, these materials can be brittle, making them difficult to manufacture especially if complex geometries are involved. Examples of ceramics include, alumina, silica and zirconia. Ceramics can be produced through indirect or direct process (Guo & Leu, 2013).

Combinations between different materials available and usage in each 3DP technology are summarised in Table 1.1.

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Table 1.1. AM material and technology combinations. Source: Wohlers Associates, Inc. (2014).

Although there have been increases in the variety and application of AM material inputs and feed stocks, they are still expensive relative to traditional manufacturing materials. For example, powder metals can be 200 times as costly as sheet metal (McKinsey & Company, 2012), and photopolymers cost between USD 750 and USD 1,000 per gallon compared to injection moulding material, which costs USD 1 per pound (Gordon, 2008). While some producers enjoy savings when using AM for custom products and low production runs, the high prices of available materials continue to be an impediment for many potential producers (Ford, 2014).

1.2.3. 3D Printer Technologies

The 3DP market offers a huge variety of choices, and not all devices use the same technology2_{. In fact, there are several ways to print and all those available are}

additive, differing mainly in the way layers are built to create the final object (3DPrinting.com, 2017).

In order to understand these differences, a detailed state of the art analysis of all AM sub-technologies is presented. The analysis aims at describing in detail the

2_{In this work, for the sake of simplicity, we refer to AM as he family of technologies. Hence, we use the}

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process chain involved in each sub-technology currently available for direct fabrication of parts. In general terms, the process chain for AM is simply characterized by direct production of objects based on a STL file. Intermediate stages, such as tool manufacturing, are unnecessary. As reported in the ISO 17296-2:2015(E) Directive for General Principles on AM, there are basically two different categories:

1. Single-step Processes: parts are fabricated in a single operation where the basic geometric shape and basic material properties of the intended product are achieved simultaneously;

2. Multi-step Processes: parts are fabricated in two or more operations where the first typically provides the basic geometric shape and the following consolidates the part to the intended basic material properties.

Note that according to the final application for the product, all processes may require different post-process treatments in order to reach the needed properties. Subsequently, the analysis explores the different AM technologies' the requirements for specific feedstock-process combinations – such as information on fundamental properties of the feedstock (material used in the process), requirements on feedstock (pre-conditioning) and dimensional accuracy – and the specific machine types.

To be more precise: since 2010, the ASTM F42 developed a set of standards that classify the AM processes into seven different categories according to Standard Terminology for AM Technologies. These are:

• Vat photopolymerization; • Powder bed fusion; • Material extrusion; • Material jetting; • Binder jetting; • Sheet lamination;

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Hereafter, all these processes are analysed following the yet cited methodology.

Vat photopolymerization

The definition of Vat photopolymerization according to ISO 17296-1 is: “AM process in which liquid photopolymer in a vat is selectively cured by light-activated polymerization”. Most photopolymers react to radiation in the ultraviolet (UV) range of wavelengths, but other visible light systems are used, too. When irradiation occurs, the liquid material undergoes a chemical reaction to become solid. Key features of the process are:

• Feedstock: liquid or paste: photoreactive resin with or without filler. • Binding mechanism: chemical reaction bonding.

• Source of activation: typically, UV radiation from lasers or lamps.

• Secondary processing: cleaning, support material removal, post-curing by further UV exposure.

The Vat photopolymerization process is applied to three types of technologies, the first and the most commonly used is Stereolithography (SLA). SLA (sometimes referred to as SL) utilise a UV laser to build the object, one layer at a time. For each layer, the laser beam traces a cross-section of the part pattern on the surface of the UV curable liquid resin, and to a degree of depth inside the resin, forcing it to solidify when exposed to the UV light, thus joining it to the layer below. After the section’s tracing is complete, the SLA’s elevator platform on which the object is being built descends by a distance equal to the thickness of a single layer and the process can restart with the following section. Materials used in SLA are either transparent or white and cannot be coloured during the process but with use of a post-process (grey colours are possible on some platforms) (Bogers, Hadar & Bilberg, 2016). One of the main suppliers of SLA machines is 3D Systems. 3D Systems has a wide range of SLA machines used for production from the iPro series. 3D Systems machines can achieve a layer thickness of between 0.05 and 0.15 mm and due to the liquid characteristic of its resin, it can achieve down to a micron level accuracy. The iPro

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machines operate with a dual laser spot size capability for faster building rate, with a beam size of 0.13 mm in diameter for borders and 0.76 mm for filling (3D Systems, 2013; Melchels, Feijen & Grijpma, 2010; Pham & Gault, 1998).

Figure 1.6. The SLA process.

Another type of machine available on the market is the Digital Light Processing (DLP). It is very similar to SLA, the key difference is the light source: instead of using a laser beam, a traditional light source, like an arc lamp, projects images onto the polymer surface. Contrary to SLA, in which the platforms moved downwards as patterns are projected on it, DLP's light projector is located under the platform and patterns are projected onto a clear tray containing the resin, curing the resin from beneath. The platform holding the part will then move up and a new layer of resin will be applied on the tray (Bogers, Hadar & Bilberg, 2016). Due to its light projecting technology that project a 2D image and not a single point laser, lead time can be significantly reduced and numerous parts can be built simultaneously (Gibson, Rosen & Stucker, 2010; Melchels, Feijen & Grijpma, 2010).

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One of the main suppliers of DLP technologies is EnvisionTEC. In its machines, print resolution can reach 0.05 mm and the building rate can arrive to 25 mm/h. Layer thickness can vary between 0.025 to 0.15 mm, while materials used in the DLP technology are essentially the same as are used in SLA. Here, materials are mostly transparent or have a yellow/red colour (EnvisionTEC, 2013).

Figure 1.7. The DLP process.

The last and also the newest machine type which applies the Vat photopolymerization process is the Continuous Liquid Interface Production (CLIP). The technology has been developed in recent years by the US company Carbon. Its machines offer a speed from 25 to 100 times faster than currently available commercial SLA machines. This new CLIP process has some similarities with DLP and SLA but uses additional lens like oxygen permeable layer in the resin vat that enables changing pulses of UV light and oxygen to build the object in fast continuous flow (3DPrinting.com, 2017). As regard resolution and precision of the process, CLIP technology offers breakthrough performances, since there are almost no layers and there is a sharp increase in print quality, final object precision and smoothness (Carbon, 2017).

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Figure 1.8. The CLIP process.

Powder bed fusion

ISO 17296-1 defines powder bed fusion as: “AM process in which thermal energy selectively fuses regions of a powder bed”. This process utilizes a container filled with material’s powder, that is processed using an energy source, commonly a scanning laser or electron beam. Key features of the process are:

• Feedstock: various powders such as thermoplastic polymers, pure metals or metal alloys, structural or industrial ceramics.

• Binding mechanism: thermal reaction bonding.

• Source of activation: thermal energy, typically transferred from laser, electron beam, and/or infrared lamps.

• Secondary processing: removal of loose powder and, if applicable, support material, and post-process operations to improve surface finish, dimensional accuracy and material properties.

Powder bed fusion processes were among the first commercialized AM processes. The most commonly used technologies are Selective Laser Sintering (SLS) and Selective Laser Melting (SLM) or Direct Metal Laser Sintering (DMLS). The difference

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between names mainly refers to the type of powder used in the process (thermoplastics, ceramics and metals). In fact, SLS is used to produce aesthetics prototypes and plastic parts, whereas SLM/DMLS finds its application in the creation of metal parts with severe undercuts. Since both technologies work in the same way, only SLS is described in detail to give a deeper sense of how the production process takes place.

SLS was developed and patented by Dr. Carl Deckard (University of Texas) in the 1980s. During SLS process thin layers of powder are being distributed in the building chamber and fused together with the use of a laser deflection system (mirrors deflect the laser beam to a desired location) to create the desired three-dimensional shape. The laser will create a path in the polymer's layer that will consolidate the layers. After the binding of a layer takes place, the powder bed is lowered by one-layer thickness, and a new layer is dispensed. The process will repeat itself until a shape is created (Kruth, Mercelis, Van Vaerenbergh, Froyen & Rombouts, 2005; Kruth, Wang, Laoui & Froyen, 2003). SLS machines do not use support materials as the un-bound powder left in the chamber is used as a support structure for the coming layers. This restricts the possible dimensions and geometries with SLS technology (Gibson, Rosen & Stucker, 2010). One of the main suppliers of SLS machines is EOS GmbH, a German producer of industrial AM machines. The main difference between different platforms is the size of the building chamber. Layer thickness can reach dimensions between 0.06 and 0.18 mm, depending on the size of the laser and production parameters, and the building speed can be as fast as 30 mm/h. Going down in layer and beam size will increase the details and the accuracy of the part but will reduce the speed of the process. The majority of materials used in SLS are white although some materials are offered in black as well. Colouring is only possible with the use of post-processes (EOS, 2013). Also, 3D Systems offers a series of SLS machines able to reach a layer thickness between 0.08 and 0.15 mm and a building speed between 1 and 5 L/h (3D Systems, 2013).

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Figure 1.9. The SLS, SLM and DMLS processes.

Material extrusion

Material extrusion, according to ISO 17296-1, is an “AM process in which material is selectively dispensed through a nozzle or orifice”. The key features of this process are:

• Feedstock: Filament or paste, typically thermoplastics and structural ceramics.

• Binding mechanism: thermal or chemical reaction bonding.

• Source of activation: heat, ultrasound or a chemical reaction between components.

• Secondary processing: removal of support structure.

In high-end devices, a second nozzle is needed to dispense support material used to create geometries that would otherwise collapse during the building process. The final object is then obtained by dissolving the support material with a specific chemical treatment.

The most commonly used technology in this process is Fused Deposition Modelling (FDM), but the technology is also referred to as Fused Filament Fabrication (FFF). The two terms are exactly equivalent: the first refers to the invention by Scott Crump in the late 80’s. After patenting the FDM technology, he started the company

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Stratasys in 1988. FFF was latterly coined by the members of the RepRap project to provide a definition that would allow a legal and unconstrained use.

In FDM based machines, a filament of material (usually a string of plastic) is fed to a heating element (the nozzle) and is semi-molten in order to be able to dispense the plastic as desired. Since the material dispensed from the nozzle is in a semi-molten state, it binds with the layer beneath it to create a solid object (Bogers, Hadar & Bilberg, 2016). The printing head often moves in the X and Y directions while the platform itself moves in the Z, although in some machines the print head is capable of moving in all three directions (Gibson, Rosen & Stucker, 2010; Ahn, Montero, Dan, Roundy & Wright, 2002). In most cases, FDM is used with two plastic filament material types: Polylactic acid (PLA) and Acrylonitrile Butadiene Styrene (ABS). Nevertheless, many other materials have been tested in time and are now available, ranging from flexible materials to conductive ones, and even wood fill. The above-mentioned US company Stratasys is one of the main actors on this technology, and its industrial machines differ by the size of the chamber, tip sizes for production, production speed, and other variants. The smallest layer thickness available in FDM is 0.127 mm. The tip size chosen also has a great influence on the accuracy of the part. There are several tip sizes available, such as T16 (0.4 mm in diameter), T12 and T10 (0.3 mm and 0.25 mm in diameter, respectively) (Stratasys, 2013). Normally, technological development aims at reaching smaller tip size and thicker layers to increase accuracy and better surface properties, but in the case of FDM technology researcher must seek a compromise: the mechanical property of the part worsen as less material is applied. Less binding surface imply worse mechanical integrity.

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Figure 1.10. The FDM and FFF processes.

Material jetting

According to ISO 17296-1, material jetting is an “AM process in which droplets of build material are selectively deposited”. The process is pretty similar to the way a traditional 2D inkjet paper printer works, but it is applied layer-by-layer to a build support creating a 3D part and then hardened using a UV light. Key features are:

• Feedstock: liquid photopolymer or melted wax, with or without filler.

• Binding mechanism: chemical reaction bonding or adhesion by solidification of melted material.

• Source of activation: radiation light source for chemical reaction bonding. • Secondary processing: support material removal, post-curing by further

radiation light exposure.

In addition to the building material applied by the print head, a wax based support material is applied in order to expand the range of geometries achievable by the machine. The support material can be removed using pressurized water (Vaupotič,

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Brezočnik & Balič, 2006; Brajlih, Drstvensek, Kovacic & Balic, 2006). The most common technology associated to material jetting process is Multi-Jet Modelling (MJM), also referred to as Polyjet Matrix (PJM).

Currently, PJM is one of the youngest 3DP technologies available on the market. It is one of the fastest and more accurate 3DP technologies. The speed of the process is attributed to two characteristics of the technology. The first is the multiple ejection of material from the print head and the second is the dual UV light system in both sides of the print head. Both attributes enable the production of multiple parts simultaneously and a faster curing process (Melchels, Feijen & Grijpma, 2010). PJM was first commercialized by the company Objet, which then merged with Stratasys in 2013, and is now part of Stratasys products’ catalogue. Layer thickness is specified as 0.016 mm with accuracy of about 0.085 mm, depending on geometries and materials and materials vary from ABS and PP like materials to rubber materials. Several platforms are able to combine soft and hard materials, create different hardness to the finished products and print in the full CMYK (Cyan, Magenta, Yellow, Key black) colour range (Stratasys, 2015).

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Binder jetting

The definition of binder jetting reported in the ISO 17296-1 directive is: “AM process in which a liquid bonding agent is selectively deposited to join powder materials”. In contrast with the other processes analysed, in the binder jetting two materials are used, both needed for the creation of the final object: powder base material and a liquid binder. Key features of the process are:

• Feedstock: powders, powder blends or particulate materials, and a liquid adhesive/bonding agent.

• Binding mechanism: chemical and/or thermal reaction bonding.

• Source of activation: depending on the bonding agent, chemical reaction. • Secondary processing: removal of loose powder, impregnation or infiltration

of suitable liquid material depending on the powder material and intended application.

Epoxies, waxes and other adhesives are used for polymer materials, ceramics and metals are bonded by infiltration with melted material and sintering. This technology was initially developed at the Massachusetts Institute of Technology (MIT) in 1993.

In 1995, Z Corporation obtained the exclusive license, applying the process in its Inkjet Z Corporation technology (Zcorp). Inside the build chamber the powder is distributed in equal layers and a binder agent is applied through jet nozzles which “glue” the particles below in the programmed shape. After the print is finished, the remaining powder is cleaned off and recycled. The drops applied by the mechanism are colored as they are applied (by combining basic colours, similar to a regular printer), hence the printer is capable of printing the entire CMYK colour range (Bogers, Hadar & Bilberg, 2016). Z Corporation was bought by 3D Systems in 2012, but its technology is still used in machines able to “print” layers with thickness varying between 0.09 and 0.2 mm.

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Figure 1.12. The Inkjet Z Corporation process.

Sheet lamination

ISO 17296-1 defines sheet lamination process as: “AM process in which sheets of material are bonded to form an object”. The process can be fed in two ways, using rolls to have a continuous flow or using discontinued sheets subsequently deposited one on another to feed the process. Key features of this process are:

• Feedstock: typically sheets of paper, metal foil, polymers or composite sheets formed by metal or ceramic powder material held together by a binder. • Binding mechanism: thermal reaction, or chemical reaction bonding,

ultrasound.

• Source of activation: localized or large-scale heating, chemical reaction and ultrasonic transducers.

• Secondary processing: removal of waste material, and optionally sintering, infiltration, heat treatment, sanding or machining to improve surface finish. The process finds its main application in the Laminated Object Manufacturing (LOM) technology, an established technique to create solid prototypes. LOM was first

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being studied by an industry-university collaborative team led by University of Dayton and Helisys (Klosterman et al., 1996).

In LOM machines, sheets of material are welded together by ultrasonic welding in layers and then CNC milled into a proper shape. When using paper sheets, the “welding” process is obtained using glue, then glued sheets are cut in shape with precise blades. Currently, a leading company in this field is the US company Fabrisonic, whose machines work with metal sheets. Accuracy of the process is related mainly to positioning of the ultrasonic/thermal emitter. Precision is in the order of ± 0.005 mm and production speed is around 304.8 m/h, thus quite fast. For machines operating with plastic materials or paper it is also possible to reach a full chromatic range on the finished product (Fabrisonic, 2017).

Figure 1.13. The LOM process.

Direct energy deposition

The definition of directed energy deposition according to ISO 17296-1: “AM process in which focused thermal energy is used to fuse materials by melting as they are being deposited”. Multiple axis capability, typically from 3 to 6-axis, is

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achieved moving the nozzle using a robotic arm and move/rotate the build table. Key features of the process are:

• Feedstock: powder or wire, typically metal, for certain applications ceramic particles can be added to the base material.

• Binding mechanism: thermal reaction bonding via melting and solidification. • Source of activation: laser, electron beam or plasma transferred arc.

• Secondary processing: surface finish treatments such as machining, micro blasting, laser re-melting, grinding or polishing and improving material properties (e.g. heat treatments).

Note that this is the only process among those analysed which is considered “hybrid”: in the same device there are both the additive and the subtractive specific tools.

Technology associated to direct energy deposition process is Laser Metal Deposition (LMD), also referred to as Laser Engineered Net Shaping (LENS). The primary application is in rapid manufacturing and in the high-tech metal industry. Machines mainly differ for alternative material feeding systems: powder fed in through the energy beam, powder fed into the energy focal point, or filament fed into the energy focal point. Moreover, complex three-dimensional geometries may require support material to be deposited and melted or even support structures. In LMD machines, degree of precision by laser generated molten pool is typically 0.25 – 1 mm in diameter and 0.1 – 0.5 mm in depth, resulting layer thicknesses typically are 0.25 – 0.5 mm.

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Figure 1.14. The LMD and LENS processes.

1.3. Main Applications

In this section, a review of the main industrial applications for 3DP technologies is presented. We start from the results of the 2014’s annual survey by Wohlers Associates, Inc. on the yet cited “applications” dimension. In the attempt of mapping how organizations are using industrial AM systems, Wohlers asked the 111 interviewed firms3_{the following question: “How do your customers use the parts}

built on your AM systems?” (Wohlers Associates, Inc., 2014). Answers are reported in Figure 1.15.

3_{Interviewed firms in 2014 included 29 manufacturers of professional-grade, industrial AM systems and}

82 service providers worldwide. Their customers are other organisations using acquired machines and services to 3D print parts and/or final products.

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Figure 1.15. Final applications of AM systems. Source: Wohlers Associates, Inc. (2014).

Despite the number of applications listed in different reports from consultancy firms and institutions, the academic literature focuses on three main applications for 3DP. These are:

• Rapid prototyping (RP); • Rapid tooling (RT);

• Direct manufacturing (DM).

Hereafter, we go through each of these applications, analysing the related main features.

Rapid prototyping

This is the first field in which AM technologies have ever been used, and by far it is the most frequent application still nowadays. In the RP case, the additive process is applied in the creation of prototype objects on which operating aesthetic and/or functional studies. The use of 3DP in this field started right after its first appearance. in the 1980s. Nevertheless, at that time, the introduction of RP, only had a marginal effect on the way companies planned and carried out their business activities. Indeed, the main purpose of a prototype is to identify design flaws, such as compatibility or usage issues. With the introduction of RP it became possible to significantly cut down the process of building a prototype from weeks (sometimes months) to a matter of days or even hours (Rayna & Striukova, 2016). Moreover, it

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is extremely advantageous for the possibility of jumping directly from the design phase to the production phase, without the necessity of going through intermediary steps of tools and moulds creation.

Rapid tooling

The second application of 3DP technologies that showed up in time is RT. It represents the following stage of technology application’s development path. RT involves the fabrication of moulds and dies for a long-term use, which are able to form several thousand or even millions of parts before final wearing-out (Levy, Schindel & Kruth, 2003). Referring to tooling, plastic injection moulds are primarily considered, since these are the most frequently used tools. The adoption of AM in this context drives down the cost of tooling and, subsequently, cost of production meaning that a greater variety of products can be offered. Still, RT has a little impact on companies’ business model. Indeed, just like RP, RT accelerates the production, process without radically changing it. RT still remains an integral part of “traditional” manufacturing processes. Nowadays, RT is mostly used in niche markets by companies needing intermediate tooling to produce a small number of prototypes or functional test samples for evaluation and market (Rayna & Striukova, 2016).

Direct manufacturing

The last application of AM technologies, which is by far the one that everyone, from researchers to engineers and entrepreneurs, wishes to see commonly adopted in the next future in the manufacturing world is DM. While the impact of RP and RT on business activities is rather limited, this next stage of application has the potential to profoundly disrupt the manufacturing world. DM guarantees long-term consistent production of finished products and components, thus enabling firms to completely reconfigure their production processes. These parts are usable for the entire product life-cycle, or at least for a determined period of time. Nonetheless, in most cases, the cost of manufacturing with 3DP machines

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still remains higher than traditional manufacturing. Thus, companies using 3D printers to manufacture do so because they intend to leverage the unique advantages of 3DP (and not just as straight replacement) (Rayna & Striukova, 2016). DM can even help businesses to overcome challenges, and increase efficiency in maintenance and repair activities. In fact, increased customization is having a particular knock-on effect on the manufacturing process: special or custom machine parts are usually produced in small batches, or even as “lot-size-one” (EY, 2016). These small batches are expensive to manufacture leveraging on traditional techniques, since they require tooling activities and long lead-times. AM helps controlling these costs since the technology enables flexible adjustments to custom parts during development phase and allows cost-effective repair of components.

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CHAPTER 2: Additive Manufacturing and Global

Value Chain

After having analysed the technical features of Additive Manufacturing (AM) and the potential of its applications, it is important to deepen the understanding on the impact this technology might have on the activities that firms carry on, nationally and internationally. The final intent is to identify what will be the future scenario in Global Value Chains (GVCs) in case of a widespread adoption of 3D Printing (3DP) for product and service provision. In order to do this, first we propose a deep focus on how AM can impact the activities carried out within firm’s boundaries, leveraging on the well know “Porter’s Value Chain” model. Secondly, we expand the analysis to the wider perspective of the GVC. In particular, we use the Smiling Curve as a concept framework in trying to identify which are the potential changes coming from the 3DP innovation. This is done after an historical review of the effects of previous disruptive innovations.

2.1. Porter’s Value Chain and 3D Printing

AM can be considered one of the most disruptive technology for the entire Value Chain (VC) (Mohr & Khan, 2015). AM’s impact, in fact, is not only limited to the manufacturing stage. In particular, elimination of design constraints, simplification of the assembly process, complexity for free and reduction of the time to market are only few examples of the transformative potential of AM (Mashhadi, Esmaeilian & Behdad, 2015). For all these reasons, we adopt the Porter’s Value Chain

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model as a reference framework to make a summary of the several implications of 3DP technology.

Porter's Value Chain is a model to schematize and providing in a glance any

company’s set of activities. This framework comes from the process view of organisations: “the idea of seeing a manufacturing (or service) organisation as a system, made up of subsystems (i.e. activities) each with inputs, transformation processes and outputs, which involve procurement and consumption of resources (i.e. money, labour, materials, equipment, buildings, land, administration and management). Each subsystem can be classified as a primary or secondary activity” (Porter, 1985). A graphic representation of the VC is presented in Figure 2.1.

Figure 2.1. Porter’s Value Chain. Source: Porter, Michael (1985).

According to Porter, primary activities are:

• Inbound Logistics – Relationships with suppliers and all the activities required

to receive, store, and allocate inputs.

• Operations – All the activities required to transform inputs into outputs (i.e.

products or services).

• Outbound Logistics – All the activities required to consolidate, store, ship and