In this paper, the IoT concept is examined and its potential effects on traditional supply chain management appraised, with particular emphasis on the automotive industry.
The Internet of Things (IoT), comprising millions of interconnecting communication devices, linked via the internet, and enabling information sharing globally (Davenport, 2013), is a growing reality and one likely to change the shape of supply chain management.
A report by Gartner (2014) predicts that IoT, a disruptive technology (Christensen, 2015), will completely transform logistics, and the report forecasts a thirty-fold increase in internet-connected physical devices by 2020. IoT will support the assembly and communication of supply chains in previously unknown ways, and therefore impact on how information is accessed and shared by supply chain managers, according to Gartner (2014).
Introduction
The Internet of Things (IoT), comprising millions of interconnecting communication devices, linked via the internet, and enabling information sharing globally (Davenport, 2013), is a growing reality and one likely to change the shape of supply chain management. A report by Gartner (2014) predicts that IoT, a disruptive technology (Christensen, 2015), will completely transform logistics, and the report forecasts a thirty-fold increase in internet-connected physical devices by 2020. IoT will support the assembly and communication of supply chains in previously unknown ways, and therefore impact on how information is accessed and shared by supply chain managers, according to Gartner (2014). In this paper, the IoT concept is examined and its potential effects on traditional supply chain management appraised, with particular emphasis on the automotive industry.
The Internet of Things
Traditionally information, which may have been gathered from a variety of sources such as external contacts and internal reports, has been stored in databases, then used in a variety of ways to produce analyses, from which business decisions were made. However, information gathering and distribution methodology is changing rapidly as the physical world becomes an information system, for instance as a consequence of sensors present in human bodies, road systems and buildings; sensors and actuators, which can also communicate, when linked by wire or wireless systems, and enable access to huge amounts of data, employing internet protocols (IP) identical to those connecting the internet. This phenomenon related to sensors in physical objects is referred to as the internet of things (IoT), by Chui, Löffler and Roberts (2010). The Internet of Everything (IoE) is a similar concept, of which IoT could be considered a part, and refers to millions of devices that connect with the internet and, as processing power increases, these devices, which are already growing in number, are forecast to enable huge networks that will share knowledge, enhance innovation and understanding, so that more rapid and superior decision making will result (Davenport, 2013).
In the supply chain, Radio Frequency Identification (RFID) technology, which follows the movement of objects within a supply chain, has been in existence for over 20 years. The process frequently operates by attaching tags containing a product code to objects, which can be detected using a reader, by means of the wirelessly communicated signal between tag and reader (Chang, Klabjan and Vossen, 2010). The technology represents a fundamental example of the use of sensors attached to objects, which has enormous potential to reduce costs and increase efficiency and security by tracking and locating the objects (Teo et al., 2011). The uptake of RFID has been limited by the cost of implementation, low awareness and inadequate employee skills, as well as the lack of global standardisation of radio frequencies employed in different parts of the world, and poor accuracy in the presence of certain metals and liquids (Sarac, Absi. and Dauzere-Peres., 2010). However, RFID technologies are likely to develop further as the IoT concept progresses, since the sensors employed are able to provide a wide variety of other information, for instance the temperature change as a vehicle is transported from one location to another, a factor that impacts on quality, and driver specific data including speed and fuel efficiency, which can enable cost control as well as measurement of overall productivity (Shankar, 2015).
The IoT comprises of four elements: things, the internet, platform and hardware, figure 1. Things are represented by everyday objects, such as cars and telephones, which are the most important components, but without decision making capability. The internet with its corresponding hardware, acts as the communication medium and the hardware enables the things to function, to collect data and transmit it to the platform. The hardware may be embedded in the everyday object, for instance it may be SIM card or sensor, and the platform stores the data and uses logic and intelligence to make decisions; the platform is the most complex element, which connects the other three together. Proprietary platforms are available from software providers, such as Cisco and Microsoft (Keskin and Kennedy, 2015).
Abbildung in dieser Leseprobe nicht enthalten
Figure 1: The Internet and ThingAbbildung in dieser Leseprobe nicht enthalten
Source: Keskin and Kennedy, 2015, p. 1444.
The thing is usually an object purchased by as consumer, a durable good produced by a manufacturer, for instance a car; a smart durable good will represent significant additional value to the consumer in terms of added value, which in a car could embrace objects that make the driving experience more effective and safer. The manufacturer will purchase the platform/intelligent solution from a software manufacturer to be able to capture data transmitted by the object (Keskin and Kennedy, 2015).
The Automotive Supply Chain
The IoT is considered to be far wider reaching than information sharing between a few firms involved in a single supply chain, and to provide opportunities for firms to operate business models that involve a network of firms, an ecosystem of business partners (Turber et al. 2014). The transactions between firms are enabled by means of a technological platform that links the businesses together and connects them to the end user by means of the smart objects they have purchased (Keskin and Kennedy, 2015); the system also has the capacity to be cloud based, which reduces cost and improves speed and ease of integration (Chen, Chen and Tsu, 2014). In the automotive sector, the impact of IoT therefore embraces information sharing between the manufacturers, which have previously competed fiercely and retained market position by retaining secrecy regarding innovation, for instance. Hence exploiting the advantages of IoT, implies that a new mind-set will be required.
Every new car is expected to be a part of the IoT by 2017 (Scardilli, 2014) and the industry forecast envisages vehicles communicating with each other, and sending and receiving data via cloud; the technology already exist for lane compliance, parallel parking and setting insurance premiums according to driver capability. In addition, using data gathered in this way, enables manufacturers to improve product design, efficiency and safety (CG, 2015; Schutte, 2014). The design of new vehicles, will be driven by consumer demand to link vehicles and other devices in their homes and offices with the technology in the vehicle, according to Schmid (2014). These and other developments integrate the principle of creating customer value through co-creation of vehicles of the future, promoted by Gronroos and Ravald (2011), and represent new revenue streams for manufacturers (Ravi, 2015).
The IoT car described by Wong (2015) comprises wireless sensors, which can locate a leak, alert the driver to low tyre pressures and identify obstacles that might cause a problem with parking or manoeuvring by means of ultrasound and surround view camera sensors. In addition radar would be employed for cruise control and emergency braking and GPS for location and following traffic patterns. The types, positions and functions of such sensors in vehicles is exemplified by Advanced Driver Assistance Systems (ADAS) in vehicles and which generates huge quantities of data, which is processed and sent to cloud (Wong, 2015), are shown in figure 2.
Figure 2: ADAS in Vehicles
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Source: Texas Instruments[1]
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[1] http://electronicdesign.com/site-files/electronicdesign.com/files/uploads/2015/01/0215TR-IoT-fig-1-TI-ADAS-small.gif
- Quote paper
- Dipl.-Ing. Martin Greiner (Author), 2015, Automotive Supply Chain Management in the Internet of Things, Munich, GRIN Verlag, https://www.grin.com/document/308583
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