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105 Seiten, Note: 80.00
List of Abbreviations
I Literature review
1 The fourth industrial revolution
1.1 Historical perspective on the industry
1.1.1 The first industrial revolution: mechanisation
1.1.2 The second industrial revolution: electric power
1.1.3 The third industrial revolution: automation
1.2 The fourth industrial revolution
1.2.1 Criteria I: technology and elements
1.2.2 Criteria II: impact on economic systems
1.2.3 Criteria III: impact on social structures
2 Supply chain management
2.1 Оverview and concepts
2.2 Historical perspective on supply chain management
2.3 SCM model: categories and decisions
2.3.1 Logistic network and operations strategy
2.3.7 Product flows monitoring
2.3.8 Warehousing and products handling
2.3.10 Reverse logistics
3 The impact of the II0T on SCM based on the literature
3.1 Logistic network and operations strategy
3.7 Product flows monitoring
3.8 Warehousing and products handling
3.10 Reverse logistics
3.11.1 Data and process security
3.11.2 Cooperation and data property
3.11.3 Interoperability and standards
3.11.4 Cost and investment
3.11.5 Impact on labour
4 Qualitative surveys
4.2.1 Additional insights on sc categories and II0T challenges
4.2.2 Blockchain technology for data security, data property and trust
4.2.3 Current state of development of II0T applications
4.2.4 Should companies engage in the II0T today?
A Illustrations and graphics
A.l The vertical aspects of the I0T
A.2 Environments and technological nodes of the II0T
A.3 Responsibilities of integrated platform solutions in the case of Microsoft Azure
A.4 The impact of the fourth industrial revolution on the job market
A.5 Illustration of the traditional production line and smart factory production system
A.6 The automation pyramid: an example from the SMC Corporation
A.7 Technical flow chart of data communication between client and servei· using RFID
This paper brings my master’s degree in Business Engineering to an end. Writing it was the most rewarding achievement of my studies at the Louvain School of Management.
I would first like to thank my parents for their unconditional support throughout my entire academic journey. They proved me times over that support can take many shapes.
Naturally, I owe my deepest gratitude to my supervisors, Professor Per Agrell and Professor Christophe Lejeune, for their guidance from the very beginning. They provided me with key insights on the topic and recognised my growing interest in the fourth industrial revolution.
In addition, I am deeply grateful to Benoit Guru, Severin Loock, Yseult Petre and Sarah Deom for taking the time to read over parts of this paper and to share their thoughts.
Linally, I want to thank all my friends and family who supported me and knew just how to keep me motivated across the entire assignment.
This paper addresses the question of how the Industrial Internet of Things (II0T), defined as the industrial aspect of the fourth industrial revolution, will impact supply chain management (SCM) decisions. With this goal in mind, we first describe the conceptual and historical ap- preaches of both the industry and supply chain management. The question of the legitimacy of a new industrial revolution is answered positively and the supply chain management discipline is organised in a flow-based model of ten managerial categories.
A thorough cross-field literature analysis delivers the main changes, opportunities and chai- lenges that the upcoming II0T will bring to supply chains. A neutral approach is favoured and the generally optimistic literature regarding the II0T is questioned. Cyber-physical systems will indeed redefine the way we provide goods and services to customers and therefore, the way entire supply chains are managed, strategically and operationally. More information, connectivity and intelligence will optimise operations to enable mass customisation and faster than ever times-to-market. Those changes will gradually transform supply chains into smart supply ecosystems, where inter-company boundaries will fade, and the nature of cooperation will evolve. Nonetheless, there is still a long way to go. Early implementations are challenged by issues of cybersecurity, interoperability, missing regulations, inter-company cooperation, cost of investment, and fear of change due to potential job restructuring.
Our results are supplemented by qualitative surveys targeting SCM and II0T professionals. This methodology is meant to discuss additional insights, detect contradictions with the literature and assess the current state of developments.
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After the World Wide Web breakthrough in the 1990s, the massive adoption of social media in the 2000s and the emergence of cloud services a few years ago, the Internet of Things (I0T) is likely to be the next technological “wave of the Internet” (Case, 2016) and was brought up for the first time in 1999 by the British entrepreneur Kevin Ashton. He wanted to picture a system in which the physical world could exchange data with computers with the help of ubiquitous sensors (Witkowski, 2017). The I0T is imagined as “creating a world whereby every object has a digital identity and can connect to a data network” (Gershenfeld, Krikorian, and Cohen, 2004, p.80). The radio-frequency identification (RFID) technology has been widely adopted by companies among several sectors to grant objects, people and animals their digital identity (Tu, Lim, and Yang, 2018). A formal definition from the Oxford Dictionary states that the I0T is “the interconnection via the Internet of computing devices embedded in everyday objects, enabling them to send and receive data״ (Oxford Dictionary, n.d.). The novelty of the concept allows us to separate I0T applications in two categories. On one hand, the applications that are already well-known to the public and, if not yet invented, realistically imaginable in a near future. Examples are connected cars, that enable software providers to gain access to transport data, as well as connected heart transplants, that send real time data to hospitals to shorten the reaction time for treatment. No later than last year in China, along with the rise of sharing economies, tier-one cities welcomed the introduction of public bikes that do not require parking in specific storage places. The bikes are connected to the Internet, allowing their monitoring by bike sharing companies, their pre-location and booking using a smartphone, and the instant report of default and misconduct. On the other hand, the I0T also brings its lot of futuristic applications, already envisioned by numerous entrepreneurs, researchers and politicians around the globe. They include complete interconnection of buildings, cities, environments, supply chains and energy networks; affecting industries such as retail, financial services, health care, education, energy, transport and manufacturing.
The inclination for more connectivity is only a forerunner to the upcoming growth in technology applications. Using connectivity to drive new insights and optimisations can be applied to manufacturing processes and overall supply chains. According to the American IT professional Alasdair Gilchrist (2016), author of Industry 4.0: The Industrial Internet of Things, there are four I0T vertical strategies (see Appendix A.l), where the Industrial Internet of Things (II0T) is the one that encompasses the largest amount of disciplines, including energy production, manufacturing, agriculture, health care, retail, transport, logistics, aviation, space travel and many more. Claiming that the II0T is simply the I0T concept applied to the factory floor is thus an understatement. Several terminologies are used when describing the I0T applied to the industry, including the II0T, the “industrial Internet” (coined by General Electrics), the “Internet of Everything” (termed by Cisco) or the “Industry 4.0” (14.0). Even if those terms, mostly the three first ones, are often used interchangeably, a clear distinction is to be made with the 14.0 which does not have the same origin and involve different sets of stakeholders, goals and implications (Elrod, 2016). A paper from Błędowski (2015) of the MAPI Foundation lists their differences clearly:
- The 14.0 comes from the German government, whereas the II0T was coined by GE and other multinational companies to set up the nonprofit organisation Industrial Internet Consortium (IIC), comprising private companies and academic institutions around the world. The 14.0 thus has a national focus while the II0T is a global phenomenon.
- The 14.0 aims to ensure the German’s industrial leadership against threatening dataoriented competitors (e.g. Google) by effectively supporting innovation, while the IIC members started cooperating after realising that they could only gain from sharing best industrial practices.
- The 14.0 focuses on manufacturing (from design to customer semce integration) through embedded systems, automation and robotics, while the II0T targets all disciplines mentioned by Gilchrist where industrial components can be connected to the Internet, provide data as feedback and increase efficiency.
- The 14.0 further emphasises hardware - Germany’s comparative advantage being manufacturing- related, while the II0T is equally attentive to software, owing to the variety of lie members.
- The 14.0 is particularly relevant to SMEs (by focusing on Mittelstand companies working together) (Kohler and Weisz, 2016) while the II0T attracts many larger companies.
- The 14.0 pictures a “theoretical description of a vision of future manufacturing״, while the II0T ״is firmly embedded in things as they exist today while seeking to solve interoperability and security challenges for the future״.
While there are clear differences, those concepts are often used as synonymous and refer to similar movements. They are evolving in parallel without noticeable competition, they share some members and “occupy the same real estate of technology״ (Błędowski, 2015).
Across this paper, we will aggregate the technological innovations of the fourth industrial revolution under the label II0T rather than 14.0 for specific reasons. We see no interest in analysing the specific case of the German manufacturing sector and its SMEs, nor to focus on hardware applications. Rather, we aim to understand how an increasing connectivity and integration can benefit today’s factories and equipment, and potentially give rise to a fourth industrial révolution implying myriads of economic and societal implications. Moreover, the II0T targets sectors that are closely related to manufacturing without intrinsically being part of it (such as transport, inter-company logistics and product flows) which are key elements of supply chain management. Finally, most of the II0T and 14.0 literature on the technology is overlapping. This gives us some leeway to decide between the two labels, with an exception for specific terms coming directly from the Plattform Industrie 4.0 initiative.
This paper addresses the question of how the II0T, defined as the industrial aspect of the fourth industrial revolution, will impact supply chain management decisions. With this goal in mind, we will first conduct a literature review on the conceptual and historical approaches of the industry and supply chain management. Chapter 1 decomposes the evolution of the industry and discusses the legitimacy of a potential fourth industrial revolution and its implications. Chapter 2 explains the theory behind the supply chain management discipline, incorporates its history with that of the industry and proposes a tangible model to analyse supply chain management categories individually. After that, a thorough cross-field literature analysis in chapter 3 delivers the main changes, opportunities and challenges that the upcoming II0T will bring to supply chains by assessing its impact on the model. Finally, we discuss our results with qualitative surveys targeting SCM and II0T professionals in chapter 4. The main objective of this last chapter is to gather additional insights, detect contradictions with the literature and realise the current state of developments. Eventually, our contributions are threefold:
- Categorisation. The literature on the fourth industrial revolution is very novel. Regarding supply chains, most articles focus on broad and basic II0T and management concepts or on the opposite, tackle very technical areas. Consequently, there is a strong need of categorisation to better define how supply chains will be impacted.
- Centralisation of realistic assessments. A better categorisation will help US draw clearer and more organised conclusions for each sc categories in a single paper, which the literature fails to provide so far. Moreover, most of the literature is purposely optimistic. This thesis serves no politic or economic agenda and aims at providing a complete landscape of opportunities and challenges for a realistic vision of future supply chains.
- A call for action. The objective of our centralised and categorised analysis is to provide academics with a solid ground to pursue further research in this area, while supplying managers and entrepreneurs with a tool to understand how disruptive the fourth industrial revolution might be for their future business, no matter the industry.
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Figure 1 : Research questions
By working towards the completion of this paper, we encountered two types of limitations.
- Novelty of the subject. The concepts of 14.0 and II0T were used the first time, respectively, in the German Hanover Fair in 2011 and by General Electric in late 2012. This has three direct consequences on the scope of this thesis. First, very few companies are aware of an upcoming fourth industrial revolution, let alone the ones that initiated assessments or effective changes in their business models. II0T data is thus rare in many industries. Second and a fortiori, even if a handful of companies in the II0T implementation phase might observe results, they would never agree to share their springboard to a potential leadership position in future markets. A quantitative approach was thus discarded from the start. Third, new concepts will emerge in the following years that might perturb the accuracy of our results.
- SCM is very broad. Managing a supply chain implies dealing with a myriad of subdisciplines and decisions which are, most of the time, industry-specific. A master’s thesis could be written on the influence of the fourth industrial revolution on each SCM categories. We decided, instead, to provide a general support for further research and a call for action towards managers involved with those categories.
The II0T and the 14.0 both refer to a new industrial revolution. Even if some influent people such as Jeremy Rifkin, the American economic theorist, discuss the upcoming of a third industrial revolution, most of the scientific community seems to agree upon the arrival of a fourth revolution. The terminology is not to be concerned about in this paper, since all parties agree that an industrial revolution is indeed on the way. But what are the scientific criteria that allow such denomination of “revolution”? Schwab (2016, p.ll), founder of the World Economic Forum, describes a revolution as being an “abrupt and radical change”. He proceeds by portraying an industrial revolution as the appearance of “new technologies and novel ways of perceiving the world [that] trigger a profound change in economic systems and social structures”. In the following subsections, we will first list the revolutions already undergone by the industry and respecting those criteria of technological, economic and social changes. Since the three first legitimised industrial revolutions are not the main focus of this thesis, a general overview will prevail over a detailed explanation of the three criteria. Nonetheless, the fourth industrial revolution will be scrutinised according to them.
The manufacturing sector has evolved through different stages during the last two and a half centuries. Until the middle of the 18ř/í Century, industrial activities mainly took place in people’s homes or small workshops held by extended families, working together towards craft models, using simple machines and hand tools. The maker was the physical owner of its creation and his skills were valued. That changed drastically when what we commonly call the “Industrial Revolution” emerged in Great Britain in the end of the 18ř/í Century. The current convention is to date the first industrial revolution from the 1780s, when the British international trade statistics showed a significant upward movement (Deane, 1980). However, it cannot be seen as a fix date as it resulted from changes in many different social and technological factors driven by a need for other sources of energy for machines and high labour and animal costs (Agrell, 2017).
This period witnessed important developments in industrial sectors such as cotton, steel and mechanical construction. The first industrial revolution also introduced the adoption of large-scale production factories, fueled with high productivity equipment owing to technological advances in hydraulic force machines and steam power.
The textile industry was the one that earned the others. It went through five important developments. In 1733, John Käyne patented the flying shuttle, allowing the cloth to be woven faster. In order to improve the spinning wheel which processed one single thread at a time, James Hargreaves, a British weaver and carpenter, invented the spinning Jenny in 1764 (“James Hargreaves, Inventor of the Spinning Jenny,” 2010). This new frame allowed multiple threads to be woven at the same time and was the first real mechanised invention of the spinning wheel. In 1769, Richard Arkwright patented the water frame: the first powered, automatic and conţin- uous textile machine which spun strengthened threads faster than ever before. This invention marked the transition from home production to mass manufacturing in factories (“Richard ArkWright,” n.d.). In 1779, Samuel Crompton combined the best features of both Hargreaves and
Arkwright’s inventions to design the spinning mule and finally, Edmund Cartwright patented the power loom in 1785, further increasing the weaving speed (“The Industrial Revolution: Samuel Crompton and the Spinning Mule,” n.d.).
Two other notable developments are worth mentioning. The coke-fired blast furnace, invented by Abraham Darby in 1709, facilitated the production of cheaper iron in bigger quantities. It was mostly used to produce rails, bridges and building structures (Le Moigne, 2017). In addition, the first steam machine was invented by Thomas Newcomen in 1712 and improved by James Watt in 1781, introducing steam as a new source of mechanical power. It subverted the whole manufacturing sector by replacing hand power, windmills and water wheels as the main fuel for the production of food, clothing and shelter (Bachman, 2006). It allowed the development of steam-powered train in 1804 that sped the carriage of goods nationally, then internationally, before becoming a mean of transport for people.
Where the first industrial revolution drove the growth of industries such as coal, iron, textiles and railroads, the second industrial revolution marked the expansion of electricity, petroleum, steel and the first assembly lines. It was driven by layout and space requirements, efficiencies between humans and machines and Taylor’s work on the division of labour (Agrell, 2017). Historians agreed to date the peak of this revolution between 1870 and 1914 (Engelman, 2015).
The beginning of the revolution saw the massive adoption of electricity, thanks to Edison’s electric incandescent light bulb invention made for households in 1879. It changed the way people worked and lived, since most of the activities were done at daylight. This lead to a number of other inventions: first telephones, radio waves, small electric cars, elevators (leading to taller buildings), phonographs, motion pictures, electric generators (leading to refrigerators and washing machines) and so on (Engelman, 2015). Electricity progressively replaced steam- powered engines in various applications. Another great invention of the time was the internal combustion engine which helped the design of the first automobiles and airplanes. Finally, in the 1870s, the first large-scale assembly lines were created for the meat industry in Cincinnati’s slaughterhouses (“Assembly Line - History,” n.d.).
Regarding management, Frederic Winslow Taylor published “The Principles of Scientific Management” in 1911, stating a new work division following the principles of repetition and simplicity of tasks. It optimised individual processes conducted by workers who were paid according to their yield. A few years later, Henry Ford put those ideas into practice and initiated assembly lines for his Ford T in big factories. Lead times for car construction dropped drastically and mass production became the norm. The continuous search for performance led to a new breakthrough in the 1950s with Taiichi Ohno, a Toyota Motors engineer. He developed the Toyota Production System (TPS), which later became lean manufacturing.
Economically, two depressions are observed in 1873 and 1897, due to extraordinary but unstable growth in production. The competition among businesses was tough, especially in the steel and oil industry. In a nutshell, “the second industrial revolution was a period of extremes: great wealth and widespread poverty, great expansion and deep depression, new opportunities and greater standardization״ (Engelman, 2015). Poor work conditions, low wages, danger, long hours and no social protection were considered as the norm.
The third industrial revolution was triggered when the passage from mechanical and analogue electric technology to digital electronics and information technology allowed the first glimpses of automation. The main advancements of this era, starting from the early 1970s on, are the computer, the Internet and ICT. Altogether, they led to a digital revolution where the value of information gained significant momentum with regards to the value of physical goods. Manufacturing processes became gradually more complex, which roused needs for increased speed, consistent qualities, protected labour and more accurate planning (Agrell, 2017).
With those objectives in mind, the first programmable logic controller (PLC), the Modicon 084, was designed in 1969 for the automobile industry and purposed to control the manufacturing process, noticing instant complications and allowing the personnel to react faster to mishaps. A PLC is an “industrially hardened computer-based unit that performs discrete or continuous control functions in a variety of processing plant and factory environments״ (Romero Segovia and Theorin, 2012). Examples of its applications are controls of equipment, processes, motion and batch. Industrial computers are easy to programme and fit extreme environments, replacing hard wires, timers and sequencers that were costlier to install, maintain and allowed much more human errors.
Other mentionable inventions include the transistor in 1947, that built the way for the creation of PC and PLC. In the late 1980s, businesses started to view computers as a necessity to improve their operations. The first cell phone was designed in the same period. The next decade, the World Wide Web was introduced and by 1996, the Internet became part of households and most business operations. In the 2000s, the digital revolution spread across the developing world and Intemet/smartphones penetration grew exponentially (Janssen, n.d.). Within the current decade, cloud services took the digital era further, allowing mobile devices to handle extreme amounts of data from remote servers.
Digital technologies are still being improved today and the boundaries between the automation revolution and the next one might seem blurry at first sight. Let US have a look at what separates them in terms of technology, impact on economic systems and on social structures.
According to Alasdair Gilchrist (2016, p.3), author of Industry 4.0 - the Industrial Internet of Things, the II0T “provides a way to get better visibility and insight into the company’s operations and assets through integration of machine sensors, middleware, software, and backend cloud compute and storage systems״. The digitisation of the enterprise enables users to study large amounts of data via cutting-edge analytic methods, resulting in operational efficiency gains, accelerated productivity and thus, profits. Other benefits than integration, transparency, efficiency and profitability gains are flexible and reconfigurable supply chains (i.e. smart equipment can automatically reconfigure themselves to manufacture various types of items, allowing companies to deal with unstable demand and specific customisations), resource and energy efficiency (i.e. big data analytics enable accurate knowledge of processes and consistent quality through accurate planning, affecting resources as well as energy consumption) as well as friendliness to staff (e.g. no need to perform routine tasks that will be automated, user-friendly HMI, remote repair work through the cloud, etc.) (Wang, Wan, Li, and Zhang, 2016).
As discussed in the introduction of this paper, the main organisations working towards those objectives are the lie with the Industrial Internet of Things and the German government with the Plattform Industrie 4.0. The first one was founded in 2014 by General Electrics, AT&T, Cisco, IBM and Intel and gathers more than two hundred members in 2018 (“ПС Member Directory,” n.d.). The second one came from a sense of emergency by the German government to lose their industrial leadership in favour of developing countries (which have access to lower costs of labour with growing expertise) or data-oriented corporations (which hold users’ data and can potentially guide consumers’ choices). From the 2000s, Germany decided to apply more aggressive and collaborative policies regarding its industrial sphere: in 2005, the DFKI (German Research Centre for Artificial Intelligence) launched the “Smart Factory” project with a competition of industrial companies. In 2006, the BMBF (Federal Ministry of Education and Research) started to approach the cyber-physical systems (CPS) technology. All these initiatives lead to the official launching of the “Industrie4.0״ programme in 2011. First focused on the I0T, it nowadays affirm the equal importance of the Internet of Services (I0S) within the movement (Kohler and Weisz, 2016).
We now have an idea of what the II0T is, why it is valuable and who are the main actors thriving for its implementation. Before gaining more insights on how will the II0T reach the above- mentioned benefits via the technology in section 1.2.1 and what impacts it will have on economie systems and social structures in sections 1.2.2 and 1.2.3, let US mention the importance of the when: why is a fourth industrial revolution at sight now even though its technologies have been around for quite some time? There are three main reasons. First, the complex industrial systems caused by an increasingly customised demand resulted in the humans’ inability to address further efficiencies. This caused machines to run well below their capabilities. Second, the decrease in costs of equipment such as sensors, actuators as well as and services such as bandwidth, storage and analytics allows data interrogation at a larger and more meaningful scale. Third, even though they existed beforehand, technologies such as cloud computing, analytics and wireless networking matured and are now more affordable, available and reliable from an industrial perspective, creating novel opportunities (Gilchrist, 2016).
According to Charles Schwab, an industrial revolution involves new technologies and a novel way to perceive the world in terms of economic systems and social structures. Let US analyse the fourth industrial revolution according to each of those three criteria.
The fourth industrial revolution marks a split with the third by means of ubiquitous intercom nections between machines, made possible by a cyber-physical system (CPS). According to Acatech, the German National Academy of Science and Engineering, CPS are “systems with embedded software (as part of devices, buildings, means of transport, transport routes, production systems, medical processes, logistic processes, coordination processes and management processes), which directly record physical data using sensors and affect physical processes USing actuators; evaluate and save recorded data, and actively or reactively interact both with the physical and digital world; are connected with one another and in global networks via digital communication facilities (wireless and/or wired, local and/or global); use globally available data and sendees; have a series of dedicated, multimodal human-machine interfaces” (Acat- ech, 2011, p.15).
The CPS thus marry automation with the Internet, as the logical evolution of Computer Integrated Manufacturing (CIM), under which a factory’s processes are all automated and under computer control. Thanks to CPS, the II0T does not only represent a new technological layer on top of the others but interconnects all physical and non-physical elements together. In that sense, this industrial revolution can be called “interactional״ (Kohler and Weisz, 2016, p.27).
It is generally admitted that one of the Industry 4.0’s main objective is the arising of digital manufacturing, also known as the smart factory, that comprises “smart networking, mobility and flexibility of industrial operations and their interoperability, integration with customers and suppliers and in the adoption of innovative business models” (Barreto, Amaral, and Pereira, 2017, p. 1247). But what is “smart”? According to the German engineer and professor Detlef Zuehlke (2010), expert in the transition between the I0T and its integration in factories, the smart objective applies to everything, down to the tiniest piece of device, that has a certain level of built-in intelligence. The popular radio-frequency identification (RFID) technology is a pioneer in the field, pasting each raw material to be processed by the smart factory with readable and writable RFID tags. They contain information on how to organise machines and configure the production route around them, while saving the history in real time on the tag’s memory and contributing to the overall supply chain’s transparency. According to another study on the smart factories by Wang et al. (2016), the products and machines become smart when they are not only granted with communication, computing and controlling capabilities (which establish the bases for automation), but are also provided with autonomy and sociality. Being autonomous, the smart device makes decisions by itself and is not controlled by other entities. Being social, the smart device understands and follows a common set of language rules, that allows it to communicate with equipment from various vendors. This phenomenon is also called ‘ ‘interoperability’ ’.
To realise the benefits of the smart factory, we should bring our attention to the three types of integration allowed by an II0T organisational structure. The companies BITKOM, VDMA, and ZVEI (2015, p.16) published, through Acatech, a position paper stating the definitions in brackets below.
- The horizontal integration across the entire value creation network describes ‘7/7ť crosscompany and company-internal intelligent cross-linking and digitalisation of value ere- ation modules throughout the value chain of a product life cycle and between value chains of adjoining product life cycles״. The value creation network involves many agents, such as suppliers, partners and clients; and is built on business models and cooperation contracts to facilitate internal cooperation (Barreto et ah, 2017).
- The vertical integration of subsystems within a factory describes “the intelligent crosslinking and digitalisation within the different aggregation and hierarchical levels of a value creation module from manufacturing stations via manufacturing cells, lines and factories, also integrating the associated value chain activities such as marketing and sales or technology development״. This vertical networking pictures smart production systems, i.e. the integration from smart products (lowest level) to smart factories (higher level), to create a flexible and adaptable manufacturing system (Barreto et ak, 2017).
- The end-to-end engineering (or through-engineering) integration across the entire product life cycle describes “the intelligent cross-linking and digitalisation throughout all phases of a product life cycle: from the raw material acquisition to manufacturing system, product use, and the product end of life״. It enables the product’s customisation at each step.
In order to understand how those integrations work, let US have a look at the technology in greater detail. Vlad Krotov (2017), associate professor at the computer science and information systems department of Murray State University, summarises the technological nodes of the II0T and pictures it as a complex socio-technical system, divided into three different environments: technological, physical and broad socioeconomic (summarised in Appendix A.2).
The technological environment consists in the enterprise/factory’s tools: hardware/software, networking technologies, data, an integrated platform and technical standards that enable interactions of the objects in the physical environment.
1. Hardware. The information retrieved from I0T elements will be readable thanks to hardware components: computers, tablets, phones and wearable products (smart glasses or watches). A special mention is to be made for RFID technology. Its electronic tags will be stuck to I0T devices and wirelessly receive and transmit information about them, containing a cheap and low-battery integrated processor. They are also gratified with a memory and interface for wireless communications (Wang et ah, 2016). They provide the items with unique identifiers (electronic product codes or EPC) containing information that RFID readers and wireless sensors will then be able to capture in a centralised database. The connection from devices directly to the Internet can be achieved by embedded communication hardware, e.g. networking cards.
2. Software. There are two types of I0T software: application software (apps in the frontend and server-side supporting them in the back-end) as well as middleware. These latter play the role of “inter-operator” between software coming from different vendors, with different technology and communication protocols. For example, a middleware could ensure the connection between an ERP and a third-party e-commerce application such as Fazada.
3. Networking. Different types of networks can sustain machine-to-machine (M2M) and indirectly machine-to-human (M2H) communications. Within I0T technologies, wireless networks are privileged over Ethernet cables and allow objects to communicate data with each other via Bluetooth Personal Area Network (PAN), and with the Internet via Wi-Fi connection. Those two types of networks require close distance to the transmitter except for larger areas where an object may necessitate a connection to a mobile network (e.g. 4G) or a satellite. A good example would be the connection between a client’s mobile phone and a biker delivering food remotely via mobile application.
4. Data. In the world of I0T, big data are characterised by three “V’s”: volume, variety and velocity. The II0T challenge is to introduce machines that integrate real time updates (via sensors), broadcast (via networks), and mining (via cloud services) of data. Actuators will then allow machines to react to new data inputs automatically. Data is the primary raw material of this fourth industrial revolution (Frank, Roehrig, and Pling, 2017).
5. Integrated platforms. Present in the back-end of the solution, an Internet-based platform (or “cloud”) supports all I0T applications, integrates the hardware components and stores their relative data. The three building blocks or delivery ways of cloud services are SaaS, PaaS and IaaS, each of them offering a different level of flexibility and control. A company may also choose to keep all information within its walls. The integrated platform will then be built “on premises”. A differentiation between all those solutions can be found on Appendix A.3 within the specific example of Microsoft Azure.
6. Standards. The I0T technology is still fresh and there is a strong need for international interoperability standards for software and hardware integrations. In the field of SCM, an attempt is the GS 1 EPC Global Architecture Framework for unique identifiers of physical goods. Those EPC will have different formats to be readable by RFID technology (binary form) and suitable for interenterprise information exchange (text form) (“EPC/RFID - Standards,” n.d.). On a broader perspective, standards are being built in a collaborative way within industry associations. Early 2018, the lie and the Plattform Industrie 4.0 announced the publication of a joint paper on architecture alignment and interoperability between the two leading II0T reference architecture models: IIRA and RAMI 4.0 (Qua- tromoni, 2018). These models take into account all elements mentioned in this section.
The physical environment consists interconnected humans and objects working in an omnipresent wireless network that allows their automatic communication and interaction.
1. Humans and non-human objects. Humans, machines, products and even animals may become interconnected thanks to all the elements of the technological environment. For instance, receiving real time data from cattle with RFID tags and EPC would allow meat control and traceability across the entire supply chain (Case, 2016). On the shop floor, guided by a mobile interface, humans can act as knowledgeable “augmented operator” with the responsibilities of monitoring and verifying production processes and strategies and manually interfering with the system when necessary. They act as flexible problem solvers in the growing technical complexity (Mrugalska and Wyrwicka, 2017).
2. Physical surrounding. Two types of physical environments surround humans and nonhuman objects and may as well be connected with the I0T. The first type consists in substances such as air, water or soil, whose properties can be monitored thanks to wireless sensors and sent to the network. Those substances are considered similar to the other IoT devices, as they provide data in a similar way. The second environment is purely physical and differs in the way that it interacts with IoT-connected objects only in specific locations: a picking dock, a whole building or a factory. For instance, a sports company warehouse might set up a picking dock’s door equipped with RFID readers that will scan every product’s EPC. It will then send footwear in stock location A, sport uniforms in location В and products to returned to a reject location via different conveyor belts.
The broad socioeconomic environment embeds multiple actors and their respective impacts. Entrepreneurs and business leaders working in and for the IoT landscape tackle technical and legal challenges and set the course of the technology in the direction of smart factories. Legislative bodies strive for standards, industry associations for interoperability and consumer advocacy groups for consumers rights protection. At the end, customers take on a more important role in the value chain of the new IoT business models.
1. Customers. The implementation of II0T technologies should focus on delivering value for the customer (Gierej, 2017). He will be placed in the centre of new business models built around the IoT with his needs translated in the customer value proposition. He will have more decision leverage than ever as his order triggers the whole supply chain. His specifications dictates the product’s RFID tag that will in turn interact with the connected enterprise and its equipment. Integrating the client’s feedback at every stage of the PLM to ensure the product’s viability is an alteration of his place in the value chain (Kohler and Weisz, 2016). Using this logic, new business models will see each customer as a trigger for new product and service variations, and a catalyst for open innovation. A good illustration of the changing role of the customer lies in additive manufacturing that emerged from increasingly demanding requirements for speed and customisation. It helps customers moving from a passive role at end of the value chain to an active central position, triggering a portfolio of products and services aiming at individualising offerings (also called “batch size 1” or “mass customisation”) and accelerating time to market (Kiel, Arnold, and Voigt, 2017). Producing batch size 1 products at costs equivalent to those in mass production is one of the goal of the Plattform Industrie 4.0 initiative.
2. Legislative bodies. The legal risk for new I0T business models is high because of the changing nature of regulations. Compliance with current legislature and thorough analyses are required to anticipate national and international laws and decrees that could potentially dictate the company’s success or failure. Nevertheless, the collection of data will, in the future, ease legislative bodies’ efforts to track business compliance. In the food and health care industries, data monitoring will have a significant impact, especially in countries where corruption levels score high and SOP are ill-defined.
3. Industry associations. The cooperation of companies within similar industries enables synergies in terms of resources, leverage and time. It pushes the speed for the adoption of new technology standards, since companies act as a unified front to fight against or strive for new regulations. Some existing II0T associations are the GSI for retailers, the lie for the introduction of new systems and devices and the AGMA for American companies and consultants.
4. Consumer privacy groups. When discussing data gathering, privacy and security are major concerns for crowds of end-users. Many popular media, such as the television series Black Mirror, pictures the extreme consequences that proliferation and mishandling of data can bring: remote hack and control of devices, scan of private environment and collection of information about specific individuals against their will. Privacy groups have merged to prevent misuse of data, but can as well become a major hindrance to the development of I0T technologies.
5. Technology entrepreneurs and their strategies. The II0T entrepreneurs of tomorrow will have to deal with all the aforementioned elements. The innovations they will strive to achieve might be incremental or disruptive. Since we are addressing new technologies and talking about a fourth industrial revolution, the new ways of managing a company that the I0T offers will be likely to foster disruptive innovations in a near future, which themselves might change our society’s landscape and encourage new business entrants to do the same.
In order to be considered a legitimate revolution, the II0T and 14.0 phenomena must express drastic technological, economic and societal changes. The content of the two following sections will mainly be based on the book The Fourth Industrial Revolution by Klaus Schwab, as a general overview on the future of economic and societal changes.
The impact on global economy might be assessed through the two main criteria of GDP growth and employment, even though every main macro variable (e.g. GDP, investment, consumption, inflation, etc.) will be affected correlatively.
The period following ww II has been called the secular stagnation, due to a mild annual average GDP growth rate around 3-3.5%. Population ageing and productivity are two factors that will be influenced by the fourth industrial revolution before impacting future growth rates. Retired workforce is increasing and a new revolution enabling people to live longer and healthier will negatively affect consumption aspects and the proportion of entrepreneurial initiatives. Governments will thus need to tackle working age, retirement and individual life-planning questions, for an aging world is destined to grow slower unless a revolution in productivity allows smarter instead of harder work. Speaking of productivity, the past decade has shown that its growth remained slow despite technological progress (The Conference Board, 2015). To embrace a potential rise in productivity, there is a strong need to update its indicators that still do not capture the right value of smart services (e.g. Uber) whose efficiency addition remains uncounted. The fourth industrial revolution will increase our capabilities to deal with negative externalities (thanks to advances in the energy sector) and enable the inclusion of markets that still need to be integrated in the global economy (thanks to future omnipresence of ICT). All of this will spur growth. But in order to reach the most-awaited productivity explosion promised by the II0T and 14.0, entirely new economic and organisational structures will be required. The fourth industrial revolution will first affect advanced economies. There is thus a risk of a “winner-takes-afl” dynamie between countries, where the gaps between them increasingly widen in terms of income, skills and infrastructure. For example, the 14.0 initiative objects to re-shore industrial manufacturing to Germany if low-cost labour does not ensure competitiveness anymore (Kohler and Weisz, 2016). This would further divide economies while creating social tensions and conflicts.
Regarding employment, fears of an irreversible technological impact on jobs have burdened all industrial revolutions. This time, the speed, breadth and depth of the transformation might create more shaking. Technological progress has two competing effects on jobs: a destruction effect that forces employees to unemployment, and a capitalisation effect of new occupations and businesses creation coming from the demand for new goods and services. A study from Frey and Osborne (2013) analyses the potential effect of technology on employment across 702 different professions and their probability to be automated. Their summarising table can be found in Appendix A.4, and they conclude that the job destruction factor is likely to take place much faster than during the previous revolutions and towards greater polarisation. High-income cognitive and creative jobs and low-income manual professions will rise but middle-income routine jobs will decline.
Not only the job market, but also the nature of jobs will change drastically. In his book Free Agent Nation, Daniel Pink (2001) depicts the upcoming of a world where the leading work model is a series of transactions between a worker and a company rather than a lasting relationship. Within the “on-demand” economy, professional activities are separated into precise tasks and individual projects before being tossed in a virtual cloud of potential workers, called “free agents”, which are located anywhere in the world. The advantages for companies are the demise of legal obligations such as minimum wages, taxes and benefits; whereas those for independent workers reside in freedom, mobility, reduced stress and greater job satisfaction. This might either lead to a flexible work revolution that will empower any individual with an Internet connection and optimise the search for skills; or lead a world where a new working class suffers from a loss of labour rights and job security (Gratton, 2011).
Those macroeconomic factors will undoubtedly impact all individual businesses and the way they are led and organised. The overflow of information allows a portion of firms to reach lightspeed success (e.g. Snapchat) and disruptive innovations (e.g. Uber). For a business to prosper, its leader must constantly learn and adapt, when the race for innovation makes talent, more than capital, the key factor of success. After the challenge of digitisation brought up by the third industrial revolution, the fourth one implies the achievement of a much more complex innovation form based on the integration of multiple technologies. It is thus vital for companies to diagnose their capabilities for adaptation before losing their competitive edge.
Business across industries will be impacted in four major ways. First, customer expectations are shifting towards greater product and service experiences. More than ever, end users have a willingness to share data and interact. Data and metrics will provide, in real time, valuable insights on customer needs and behaviours. Transparency in supply chains also gives increasing power to clients, providing them with additional ways to compare products and services. Second, products and services are enhanced with data. This increases their value and gives space to improve supply chain productivity and efficiency. Third, new types of inter-company collaboration are formed to strive for innovation and prevent being casted out by disruptions. However, a complete cooperation is often difficult to implement and require businesses to develop their strategies and align their processes towards the common project, sometimes as far as by ere- ating innovative business models. Fourth, operating models are being not only digitised, but turned into virtual platforms connected to the physical world. For example, a shared transport economy such as Mobike in China allows end users to locate and rent a bike for the consumed time only. Thus, we no longer need to purchase the object, but rather pay for the service it underlies via the digital platform (Lan, Ma, Zhu, Mangalagiu, and Thornton, 2017). This also forces companies to invest in cybersecurity systems to avoid breakdowns or hacking.
Corporate decisions regarding supply chain management fall in this category, and this paper’s objective is to gain a comprehensive view on how the fourth industrial revolution might affect
them. Before tackling the SCM paradigm and the concrete analysis, we will have a look at the last required criteria to legitimise the fourth industrial revolution: its impact on social structures.
The impact on social structures might be assessed through changes across three structural layers: governments and countries, societies and individuals.
Governments, countries and international security
Generally speaking, public institutions will change the way they operate via digitised structures that will improve their overall performance. But the disruption digs deeper. Power is increasingly shifting from state to non-state actors as social media and their groups allow basically anyone to exercise influence by giving a voice and coordinating efforts. Public authority is thus increasingly constrained, while governments become unable to rule efficiently. Looking at the other side of the coin, the uprising of mass surveillance through big data might create very powerful public authorities. The Chinese “Social Credit system” initially planned for 2020 might be the first step in the creation of such public surveillance structure (Viswanath, 2018). In either scenario, governments will be mostly considered as public semce centers assessed on their capability to provide efficient individualised services. Today, legislative bodies are outrun by technological changes and unable to cope with them (e.g. the question on how to deal with blockchain-based finance). Their survival will require them to adapt to a world of disruption menaced by new and competing power structures. Maintaining governmental functions such as competitiveness, fairness, intellectual property and safety will be crucial in a society where, either everything that is not explicitly forbidden is allowed, either the opposite prevails.
Technology does not know any border. Geography has several implications for technology. Countries and regions that thrive in creating tomorrow’s international standards regarding new technologies will gain substantial economic advantages. In opposition, countries that establish conservatism might find themselves being the laggards of the digital economy.
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