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Notes
1 1 Based on how wide the range of connected devices is defined, some talk about Industry 4.0 (in Germany), Smart Manufacturing (in US), Industrial Internet of Things (IIoT), or IoT. Whereas IoT encompasses in general all applications based on connected smart devices, the Industrial Internet of Things (IIoT) and Industry 4.0 focus on the industrial applications within the broad umbrella of IoT. To illustrate the difference we can think about a smart watch to monitor the health condition as an example of the wide range of IoT compared with a smart device monitoring the condition of a machine in a factory or a component on the transport as an example for the IIoT (Serpanos and Wolf 2018).
2 2 To identify/localize Things several methods are available, ranging from labels (e.g. barcode, QR codes) via RFID up to GPS or other ways.
3 3 See, for example, the Nexeed Track and Trace devices of Bosch Manufacturing Solutions (Robert Bosch Manufacturing Solutions 2020).
4 4 This topic will be discussed Chapter 6 in this volume.
5 5 With edge computing data produced by Internet of things (IoT), devices are processed decentralized closer to where it is created (the edge of the network, e.g. the machine) instead of sending all data to data centers or clouds (Shi et al. 2016).
6 6 Cf. the chapter by Sun in this volume.
7 7 Cf. the barriers to technology adoption discussed Chapter 25 in this volume.
4 Additive Manufacturing : Shaping the Supply Chain Revolution?
Johannes Kern
Tongji University, Shanghai, China
Introduction
Additive manufacturing (AM), casually also called 3D printing or rapid prototyping, is one of the key elements of the Fourth Industrial Revolution that is predicted to strongly impact supply chains (Verboeket and Krikke 2019; Fan et al. 2020). While in subtractive manufacturing, the typical way of how things are made today, material is removed in a controlled way, in AM, material is added based on a digital 3D drawing or model (Carr 2017). Depending on the specific technology used, complex and light designs can be created, parts developed more dynamic, and production lead times reduced (General Electric 2020). AM is envisioned to become widely spread as currently still existing constraints are progressively overcome (Schwab 2017). Already today, the technology is applied across a wide array of products. In aerospace, NASA has been experimenting with printed rocket injectors since 2013 (Holmström et al. 2016). In aviation, in 2014, a 3D‐printed titanium bracket took to the skies on board of an Airbus jetliner for the first time (Airbus 2020). Also in automotive, the technology has been used already for a decade in F1 racecars. Recently, in its commercial vehicle segment, the OEM1 Daimler started to fully integrate it into its development and production process (Sher 2020). The company also uses AM to print spare parts, where according to a spokesperson “production and delivery of a 3D‐printed part takes only a few days as opposed to several months (while producing) considerably less waste (Garnsey 2020).” In the medical industry, customized prosthetics, implants, and anatomical models are widely manufactured with AM, and research about producing tissue and even organs (“bioprinting”) is ongoing (Ventola 2014). Although such applications are noteworthy, it must be recognized that AM is not suitable for every manufacturing need and that there are still barriers to overcome.
This chapter takes the form of six sections. First, the vision of the AM supply chain will be compared with a conventional supply chain. Then, the technology's advantages and remaining bottlenecks will be explained. This is followed by an overview of various AM technologies and materials. Typical application scenarios will be subsequently derived. Afterward, markets and trends will be accounted for. The chapter then ends with a conclusion that summarizes the status of the technology and its potential supply chain impact.
AM Supply Chain
In a conventional supply chain, suppliers from various places distributed all over the world deliver certain raw materials and components to a manufacturer that is often located in a low‐cost location. This manufacturer then produces goods in large quantities, benefiting from “economies of scale,” and ships them to a central hub like an airport or port. The goods will be transported by carriers with transit times ranging from one week (airplane) up to over a month (ocean carrier) and ultimately arriving at a wholesaler. From there, the parts are distributed to various retailers until they ultimately arrive at the final customer. Such a conventional supply chain is shown in Figure 4.1.
In contrast to a conventional supply chain, an AM supply chain is much more concise (Mills and Camek 2004). Suppliers only have to deliver basic materials instead of specific components, which allow the manufacturer to already store the right materials before any customer order occurs. Considering that only a few basic materials are required, the number of suppliers in the AM supply chain would be drastically reduced. This would allow for a stronger focus on few collaboration partners that deliver high‐quality materials and the most suitable software program (Kothman and Faber 2016; Chekurov et al. 2018). The actual production process could then happen at a decentralized location close to the customer, such as at an AM manufacturer, a wholesaler, or even a retailer. This would change the conventional flow of goods, reducing upstream transportation to basic materials and downstream transportation to locally produced finished goods (Thiesse et al. 2015; Ford and Despeisse 2016). As advanced AM machines might be able to manufacture a wide range of products, physical inventory holding could be replaced by “digital inventory” holding in the form of digital CAD2 models. This would result in less stock, less material handling, and less packaging (Ruffo et al. 2007).