UNIVERSITI TEKNIKAL MALAYSIA MELAKA
MMFD 5023 SUPPLY CHAIN MANAGEMENT
“HOW WILL FOURTH INDUSTRIAL REVOLUTION IMPACT YOUR SUPPLY CHAIN”
NAME IC NO. MATRIX NO. NAME IC NO. MATRIX NO. COURSE
: : : : : : :
MUHAMMAD WAZIR SHAFIQ BIN ARIPIN 841213105217 M051620029 ABD HALIMNIZAM B ABDULLAH 740603016049 M051620026 MASTER IN MANUFACTURING ENGINEERING (INDUSTRIAL ENGINEERING) LECTURER NAME : PROF DR CHONG KUAN ENG
TABLE OF CONTENTS PAGE TABLE OF CONTENTS
i
LIST OF FIGURES
ii
CHAPTER 1.
2.
3.
4.
INTRODUCTION
1
1.1 Background of Study
1
1.2 Problem Statement
1
1.3 Objectives of Study
2
LITERATURE REVIEW
3
2.1 Industrial Revolution
3
2.2 Internet of Things (IoT)
5
2.3 Artificial intelligence (AI)
7
2.4 Big Data
8
2.5 Supply Chain in Fourth Industrial Revolution
9
FINDINGS AND DISCUSSIONS
12
3.1 New Technologies
12
3.2 Integrated Planning and Execution
12
3.3 Logistics Visibility
13
3.4 Procurement 4.0
14
3.5 Smart Warehousing
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3.6 Efficient Spare Parts Management
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3.7 Autonomous and B2C logistics
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3.8 Prescriptive Supply Chain Analytics
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3.9 Smart Supply Chain Enablers
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CONCLUSION
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REFERENCES
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i
LIST OF FIGURES
FIGURE
TITLE
PAGE
2.1
Timelines of Industrial Revolution
4
2.2
The supply chain at the center of the digital enterprise.
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2.3
The digitally enabled supply ecosystem vs. traditional linear supply 10 chain.
2.4
Expected impact of digital transformation on the cost situation in 11 companies.
2.5
Effect of push technologies and pull demand on the digital supply 11 chain.
ii
CHAPTER 1
INTRODUCTION
1.1
Background of study Manufacturing process changes aligned with industrial revolution time frame. Early
in industrial revolution, manufacturing focusing on homemade process. When First Industrial Revolution involved, manufacturing process started to using mechanization in their manufacturing process. In Second Industrial Revolution, manufacturing started produce in big scales or mass production. For Third and Fourth Industrial Revolution move to be automation production and digitalization. All industrial transformation phase, supply chain changes together to suit with the transformation. All these Industrial Revolution impact on your supply chain. In term of process/flow the supply chain, costing and strategies supply chain.
1.2
Problem Statement The Fourth Industrial Revolution is characterized by the convergence of
breakthrough technologies such as advanced robotics, artificial intelligence, the internet of things, virtual and augmented reality, wearables and additive manufacturing that are transforming productions processes and business models across different industries. Business leaders can no longer focus on developments and trends in their own sectors alone, but need to understand potential transformations and disruptions in the entire world of 1
suppliers, customers and adjacent markets. Systems are being transformed not specific products or services. Cyber physical systems combine communications, IT, data and physical elements integrating many core technologies Today the main focus is on the smart factory but what is the meaning for the supply chain management. The internet of things leads to a high transparency regarding the status of the supply chain and its nodes. The amount of information increases rapidly with the automatic acquisition of data/events. Standardized event information in high quality can be distributed within the supply chain with methods of the internet of things. But: transparency is not enough, the right conclusions have to be drawn at the right point (Akinlar, 2014).
1.3
Objectives of Study The objectives of this study are: i.
To investigate the effect of Fourth Industrial Revolution on Supply Chain in term of process/flow.
ii.
To determine effect of Fourth Industrial on Push/Pull view cycle in supply chain.
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CHAPTER 2
LITERATURE REVIEW
2.1
Industrial Revolution The First Industrial Revolution took place between about 1700s and early 1800s.
Early 1700s, manufacturing was often done in people’s homes, using hand tools or basic machines. Industrialization marked a shift to powered, special-purpose machinery, factories and mass production. The iron and textile industries, along with the development of the steam engine, played central roles in the Industrial Revolution, which also saw improved systems of transportation, communication and banking (History.com Staff, 2009). In this Industrial Revolution, manufacturing process focusing on mechanization production by using water power or steam power. The Second Industrial Revolution started around 20th century was created a wave of globalization expanded allowing for greater movement of people and ideas. Advances in electrical power drive the growth of mass production and the factory line or assembly line. In other words, during Second Industrial Revolution all manufacturing start change in their production activities. Location for manufacturing not any more focusing power source but spread to other city as long as have an electricity sources.
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The Third Industrial Revolution was driven by the widespread adoption of new digital technologies such as computer into the manufacturing for automate production. It makes manufacturing to more globalization. The Third Industrial Revolution was taking place from 1970 until nowadays. Nowadays, world already move to Fourth Industrial Revolution. Fourth Industrial Revolution are the cyber physical production system driven. It also called as Digital Industrial 4.0. The widespread adoption by manufacturing industry and traditional production operations of information and communications technology (ICT) is increasingly blurring the boundaries between the real world and the virtual world in what are known as cyber-physical production systems (Ralf C. Schlaepfer, 2015).
Figure 2.1: Timelines of Industrial Revolution (Quilligan, 2016)
Digital Industry 4.0 means combined communications, IT, data and physical elements. That allows the creation of digital factories or digital plants—in which machines “talk” to products and other machines, objects deliver decision-critical data, and information is processed and distributed in real time resulting in profound changes to the entire industrial
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ecosystem. This “connected everything” environment allows for more automation and personalized interactions (Quilligan, 2016). Like the revolutions that preceded it, the Fourth Industrial Revolution has the potential to raise global income levels and improve the quality of life for populations around the world. To date, those who have gained the most from it have been consumers able to afford and access the digital world; technology has made possible new products and services that increase the efficiency and pleasure of our personal lives (Schwab, 2015). Industrial Revolution 4.0 is the culmination of several technological innovations all coming to the forefront; sophisticated sensors, cloud computing, 3D printing, artificial intelligence, and advanced robotics. These connected devices utilize RFID, Wi-Fi, cellular networks and other technologies to communicate with each other and the cloud to become the Internet of Things. In terms of industry, this revolution entails the utilization of cyberconnected systems which monitor factory processes to maximize efficiency and reduce downtime (Bossard Group, 2017). Five key technologies, which are currently at different stages in terms of level of readiness and adoption across industry sectors, are expected to significantly impact supply chains, both individually and in combination: internet of things, artificial intelligence, advanced robotics, enterprise wearables and additive manufacturing (WEF, 2017).
2.2
Internet of Things (IoT) Organizations in today’s economic reality are on the verge of profound changes in
their operations. They are related to a quick progress in information technology and the economy entering the fourth phase of the industrial revolution. More opportunities to create systems integrating physical and virtual worlds are one of its key differentiators, and the Internet of Things is the underlying technology (Wielki, 2016).
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Nowadays Internet of Things (IoT) gained a great attention from researchers, since it becomes an important technology that promises a smart human being life, by allowing a communication between objects, machines and everything together with peoples. IoT represents a system which consists a thing in the real world, and sensors attached to or combined to these things, connected to the Internet via wired and wireless network structure. By the technology of the IoT, the world will become smart in every aspects, since the IoT will provides a means of smart cities, smart healthcare, smart homes and building, in addition to many important applications such as smart energy, grid, transportation, waste management and monitoring (Aldein Mohammeda and Ali Ahmed, 2017). For enterprises, IoT can underpin solutions that improve decision-making and productivity in manufacturing, retail, agriculture and other sectors. Machine to Machine (M2M) solutions - a subset of the IoT – already use wireless networks to connect devices to each other and the Internet, with minimal direct human intervention, to deliver services that meet the needs of a wide range of industries. In 2013, M2M connections accounted for 2.8% of global mobile connections (195 million), indicating that the sector is still at a relatively early stage in its development. An evolution of M2M, the IoT represents the coordination of multiple vendors’ machines, devices and appliances connected to the Internet through multiple networks (Shukla et al., 2017). Internet of things may be facing two major challenges in order to guarantee seamless network access; the first issue relates to the fact that today different networks coexist and the other issue is related to the big data size of the IoT. Other current issues, such as address restriction, automatic address setup, security functions such as authentication and encryption, and functions to deliver voice and video signals efficiently will probably be affected in implementing the concept of the internet of things but by ongoing in technological developments these challenges will be overcome. The internet of things
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promises future new technologies when related to cloud, fog and distributed computing, big data, and security issues. By integrating all these issues with the internet of things, smarter applications will be developed as soon. This paper surveyed some of the most important applications of IoT with particular focus on what is being actually done in addition to the challenges that facing the implementation the internet of things concept, and the other future technologies make the concept of IoT feasible (Aldein Mohammeda and Ali Ahmed, 2017).
2.3
Artificial intelligence (AI) Artificial intelligence (AI) was introduced to develop and create “thinking machines”
that are capable of mimicking, learning, and replacing human intelligence. Since the late 1970s, AI has shown great promise in improving human decision-making processes and the subsequent productivity in various business endeavors due to its ability to recognize business patterns, learn business phenomena, seek information, and analyses data intelligently. Despite its widespread acceptance as a decision-aid tool, AI has seen limited application in supply chain management (SCM) (Min, 2010). Machine-generated insights will pave the way for greater precision and accuracy. While repetitive tasks are performed by machines, people can focus on more complex activities. Physical assets replace low-skilled labor, which requires investment in and upskilling of the existing workforce. This represents a significant change for workers and should be accompanied by the appropriate communication and support of the employer (WEF, 2017) The benefits AI technologies bring to supply chain planning are the ability to provide speed and accuracy beyond human capabilities. It is possible to have a supply chain that’s smarter, faster and self-healing, meaning it continuously observes and measures data and automatically adjusts or repairs itself as it finds exceptions. The supply chain will be able to
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detect, predict and suggest, letting you answer those fundamental supply chain questions outlined above (Cheater, 2017)
2.4
Big Data Big Data is mainly driven by the widespread diffusion and adoption of mobile
devices, social media platforms including YouTube, Facebook and Twitter, and IoT related concepts such as RFID technology (Fosso et al., 2015). The cause of increasing attention of Big data analytics in SCM is its complexity and the influence that SCM have on the overall performance of companies. The SCM area is facing the challenges which may lead to inefficiency and wastage, e.g. delayed shipments, rising fuel costs, inconsistent suppliers or ever-rising customer expectations. Companies expects that Big data analysis will bring profits through the process visibility and effectiveness improvement, global supply chains integration and demand management improvement. In the area of strategic planning and management of supply chains, Big data analysis is especially important (Zdrenka, 2017). Traditional supply chain applications evolved to use transactional data to improve the supply chain response. The foundational element of supply chain systems is order and shipment data. These data forms are used extensively in the three primary applications of supply chain management: Enterprise Resource Planning (ERP), Advanced Planning Systems (APS) and Supply Chain Execution (SCE). The genesis of Enterprise Resource Planning (ERP) systems was to improve the order-to-cash and procure-to-pay functionality and maintain a common code of accounts for financial accounting. Similarly, Advanced Planning Systems (APS) applied predictive analytics to these two data types to plan and improve the supply chain response. In parallel, Supply Chain Execution (SCE) systems evolved to improve organizational order to shipment capabilities (Cecere, 2012)
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2.5
Supply Chain in Fourth Industrial Revolution In Fourth Industrial Revolution, all matter that have related with manufacture flow
will be change and become digitalization. It will be created new ecosystem in the manufacture process. Figure 3.1 below show how supply chain changes in this ecosystem. This ecosystem will be based on full implementation of a wide range of digital technologies the cloud, big data, the Internet of Things, 3D printing, augmented reality, and others. Together, they are enabling new business models, the digitization of products and services, and the digitization and integration of every link in a company’s value chain: the digital workplace, product development and innovation, engineering and manufacturing, distribution, and digital sales channels and customer relationship management (Schrauf and Berttram, 2016).
Figure 2.2: The supply chain at the center of the digital enterprise. (Schrauf and Berttram, 2016)
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The structure of supply chain also changes in this ecosystem. Where in traditional supply chain using linear structure but in digitalization supply chain become centralize with all supply chain process. Figure 2.3 below show differential between traditional supply chain and digital supply chain. Digital supply chain is based on four main attributes; Integrated, Intelligent, Flexible and Rapid (Capgemini, 2015). Integrated will be delivered through Supply Chain Tower as a centered in supply chain structure.
Figure 2.3: The digitally enabled supply ecosystem vs. traditional linear supply chain. (Schrauf and Berttram, 2016)
Digital technologies also can reduce costs by, for example, intelligent forecasts or operational support for the employee, thus also increasing productivity. Implementing these technologies can also improve customer relationships and open new business areas. The majority of companies in the manufacturing sector (79.9%), logistics services (85.5%), and retail (74.5%) recognize these and similar positive effects of a digital transformation (see Figure 3) (Kersten et al., 2017)
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Figure 2.4: Expected impact of digital transformation on the cost situation in companies. (Kersten et al., 2017)
Digitalization has created the opportunity to revolutionize old business models and in particular to implement new supply chain strategies. Many industries have moved from Push strategies to Pull strategies, just to find that these strategies lead to significant service and distribution problems. They eventually move to Push-Pull supply chains (Werner, 2013).
Figure 2.5: Effect of push technologies and pull demand on the digital supply chain. (Schrauf and Berttram, 2016)
Driving the transformation to the smart supply chain are two tightly intertwined trends. On one hand, new technologies like big data analytics, the cloud, and the Internet of Things are pushing into the market. On the other, more exacting expectations on the part of consumers, employees, and business partners are pulling companies to develop more reliable and responsive supply chains (Schrauf and Berttram, 2016). 11
CHAPTER 3
FINDINGS AND DISCUSSIONS
3.1
New Technologies Supply chains operate along the traditional Supply Chain Operation Reference
(SCOR) processes plan, source, make, deliver, return, and enable. Every one of these elements is rapidly being revitalized through technological innovation. We divide up the technologies into eight key areas: integrated planning and execution, logistics visibility, Procurement 4.0, smart warehousing, efficient spare parts management, autonomous and B2C logistics, prescriptive supply chain analytics, and smart supply chain enablers. All of these elements are interrelated, and they build on one another. Consequently, a digital supply chain strategy needs to consider all of them to leverage the full benefits of digitization.
3.2
Integrated Planning and Execution The business goal of the digital supply chain is to deliver the right product into the
customer’s hands as quickly as possible but also to do so responsively and reliably, while increasing efficiency and cutting costs through automation. This goal cannot be achieved unless the supply chain is fully integrated, seamlessly connecting suppliers, manufacturing,
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logistics, warehousing, and customers, and driven through a central cloud-based command center. With this level of integration, signals that trigger events in the supply chain can emanate from anywhere in the network and alert all to issues affecting supply or demand, such as shortages of raw materials, components, finished goods, or spare parts. In a world in which customized manufacturing is fast becoming the norm, and customers are becoming ever more demanding, the fully responsive supply chain is a huge competitive advantage and fast becoming a must-have.
3.3
Logistics Visibility The key to success for any supply chain is efficient exchange of information. The
traditional supply chain is fraught with friction, caused primarily by lack of complete and timely information. Potential for disruption is high; sudden shifts in demand, lack of raw materials, and natural disasters can wreak havoc on the best-laid supply chain plans. And the outsourcing of many necessary elements only makes it harder to understand the supply chain in full, fogging visibility into the transportation network and making it difficult to mitigate problems as they occur. That’s why the overarching goal of the digital supply chain is to open the supply network for all to see. B2C markets are pulling companies along to provide this level of visibility, demanding more information about shipment arrivals with real-time updates. In B2B networks, producers expect timely status information on their supply shipments, which are typically linked to production plans. Constantly updated and reliable transportation information can significantly improve the producer’s customer satisfaction as well.
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3.4
Procurement 4.0 Digitizing procurement will radically change the tools and talents required, add new
categories to be sourced, and transform the value proposition of the procurement function. Efficient integration and management of suppliers of raw materials and parts is a critical building block in the digital supply chain ecosystem. The digitization of many traditional aspects of procurement is already under way, as companies use a variety of big data tools and techniques to connect more closely with suppliers, aid the planning process, improve sourcing, actively manage supplier risk, and boost collaboration. The result is lower costs and faster delivery throughout the supply chain as it becomes increasingly automated.
3.5
Smart Warehousing The concept of adopting and implementing a smart factory solution can feel
complicated, even insurmountable. However, rapid technology changes and trends have made the shift toward a more flexible, adaptive production system almost an imperative for manufacturers who wish to either remain competitive or disrupt their competition. By thinking big and considering the possibilities, starting small with manageable components, and scaling quickly to grow the operations, the promise and benefits of the smart factory can be realized. The Smart Factory Logistics methodology created by Bossard meets customer needs and make inventory management leaner and more agile. Bossard has three specific solutions to make your facility smarter: i. Customer-specific evaluation – The Smart Factory Logistics approach includes a comprehensive logistics management analysis of delivery, supplier consolidation, operation and maintenance, and even encompasses strategic customer consultation.
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Smart Factory Logistics systems are engineered to suit different manufacturing environments and production setups ensuring maximum operation flexibility. ii. Intelligent systems – Patented technologies like SmartBin and SmartLabel communicate the current inventory levels from warehouses, holding areas, or lineside. Automatically triggered orders and replenishment means you have exactly what you need when you need it. iii. Big data software creates transparency – With our own supply chain collaboration software, ARIMS, we can collect and deliver data on a large scale to create transparency. Beyond plotting usage and deliveries, ARIMS can be used to plan and implement an increase or decrease in planned production. (Bossard Group, 2017)
3.6
Efficient Spare Parts Management The warehousing link in the supply chain is expensive, labor-intensive, and fraught
with potential error. Digitization will certainly eliminate much of its inefficiency and integrate the process into the entire supply chain. Meanwhile, 3D printing is poised to transform this critical link in the chain even further. Consider the problem of spare parts. At many warehouses, more than half of all orders shipped are one-time requests for spare parts, and the demand for them is highly erratic, almost impossible to predict. That’s why companies typically maintain huge inventories of parts, many of which must be kept for 30 years or more if customers are to keep operating older machines. Already, digitization is revolutionizing the warehousing and distribution of spare parts. Sophisticated analytics software allows demand for spare parts to be forecast much more precisely, through solutions such as predictive maintenance of industrial vehicles and
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machines. That in turn allows companies to optimize spare parts storage and distribution, as a great deal more information can be integrated, such as social listening and traffic and weather data, on which demand and distribution depend.
3.7
Autonomous and B2C logistics Few elements are likely to influence the general perception of the digital supply chain
as much as the rise of autonomous logistics. The notion of driverless cars already turns heads. Fleet management will deploy all manner of driverless vehicles and other robotic innovations that will play an increasing role in moving goods around the world. The most common use of autonomous vehicles in logistics will be driverless trucks. Like their car brethren, self-driving trucks will depend on mapping software and short-range radar to assess the vehicle’s surroundings. Wireless connections to other vehicles and to the road itself will provide additional information that will speed up traffic flow and reduce roadway congestion and accidents. The possibility of autonomous truck convoys — a modern-day wagon train with multiple trucks in a line — will reduce the need for human drivers and allow the trucks to drive more closely together. Internal sensors will help fleet operators assess damage to cargo and determine maintenance requirements.
3.8
Prescriptive Supply Chain Analytics The goal of the digital supply chain is to fully integrate and make visible every aspect
of the movement of goods. The key to this critical element of Industry 4.0 is big data analytics. Already, companies have the tools to describe much of the current state of their supply chains where the goods are, where the demand for specific items is currently coming from, and when items are likely to be delivered. And companies are learning to predict
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critical elements of the chain. Demand through the chain can be better anticipated thanks to more sophisticated signals from the market, which translates to demand for production capacity, storage and logistics needs, and changes in raw materials requirements. The next stage in the development of supply chain analytics will be the most important: the ability to prescribe how the supply chain should operate. The goal isn’t simply to optimize demand planning; or the supply chain’s distribution facilities, routes, and mobile assets; or the management of inventory and spare parts. Instead, the key lies in the ability to optimize for any number of factors across the entire chain, depending on circumstances, and then be able to actively modify the chain accordingly.
3.9
Smart Supply Chain Enablers Companies setting out to build the smart supply chain face a difficult task, one that
will likely prove impossible unless they develop a clear strategy that is fully responsive to the opportunities on offer in a fully digital environment. It must be based not just on the company’s current operations and business model but also on new business models available once digitization has been implemented, such as creating direct sales channels and leap frogging levels in the value chain. Once the strategy is determined, companies must put into place several key capabilities needed to carry it out, in addition to the supply chain applications discussed above. These key capabilities include the following: i. Processes. ii. Organization and Skills iii. Performance management. iv. Partnering. v. Technology.
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CHAPTER 4
CONCLUSION
Supply chain very important structure in manufacturing. History have been told that behind successful organization or company depends on their supply chain management. In Fourth Industrial Revolution, supply chain management must change and become digitalization. Indeed, the structure of supply chain management, integration strategies, technology drive the supply chain and so on must change follow the industrial transformation. Digital supply chain is a new era for supply chain management with four main attributes. The challenging for manufacturing are to prepare the equipment for digitalization such as highly technology software, big data storage, and including to prepare workforce that ready adopt the digitalization in work place. The biggest impact from the Fourth Industrial Revolution technologies and concepts is to be expected from a technological view especially for the procurement, production and distribution activities in the supply chain. The organization of the supply from a technological view will mainly change due to the implementation of Business Intelligence technologies, Smartphone Apps, and RFID-technologies and the miniaturization of electronics. However, structural changes to the organization are to be expected mainly in manufacturing processes. Impacting technologies are the Machine to Machine communication, and Smart Factory including Smart Logistics. With the combined
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implementation of Smartphone Apps and Smart Data tools, the interaction of people within the supply chain will face a huge impact in the sales departments of companies, where the customer can be integrated and organizational borders are eliminated.
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REFERENCES
Akinlar, D. S. (2014) ‘Logistics 4.0 and Challenges for the Supply Chain Planning and IT’, Presentation, pp. 1–20. Aldein Mohammeda, Z. K. and Ali Ahmed, E. S. (2017) ‘Internet of Things Applications, Challenges and Related Future Technologies’, (February). Bossard Group (2017) How will Industry 4.0 Impact your Supply Chain?. Generis Group. Available at: https://generisgp.files.wordpress.com/2017/04/bossard-final-ebook.pdf. Capgemini (2015) Digital Supply Chain Where Virtual and Physical Converge. Cecere, L. (2012) ‘Big Data’, Supply Chain Insight. Cheater, A. (2017) Artificial Intelligence in Supply Chain Management - Kinaxis, 21st Century Supply Chain Blog. Available at: https://blog.kinaxis.com/2017/01/artificialintelligence-in-supply-chain-management/ (Accessed: 14 November 2017). Fosso, S. et al. (2015) ‘Int . J . Production Economics How “ big data ” can make big impact : Findings from a systematic review and a longitudinal case study’, Intern. Journal of Production Economics. Elsevier, 165, pp. 234–246. doi: 10.1016/j.ijpe.2014.12.031. History.com Staff (2009) Industrial Revolution, A+E Networks. Available at: http://www.history.com/topics/industrial-revolution (Accessed: 11 November 2017). Kersten, W. et al. (2017) Trends and Strategies in Logistics and Supply Chain Management – Digital Transformation Opportunities. DVV Media Group GmbH. Min, H. (2010) ‘Artificial intelligence in supply chain management: Theory and applications’, International Journal of Logistics Research and Applications, 13(1), pp. 13– 39. doi: 10.1080/13675560902736537. Quilligan, A. (2016) Digital Industry, Accenture. Available at: https://www.accenture.com/gb-en/blogs/blogs-digital-industry-4-0 (Accessed: 13
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November 2017). Ralf C. Schlaepfer, M. K. (2015) ‘Industry 4.0. Challenges and solutions for the digital transformation and use of exponential technologies’, Deloitte, pp. 1–30. Schrauf, S. and Berttram, P. (2016) Industry 4.0: How digitization makes the supply chain more efficient, agile, and customer-focused, Strategy&. Available at: https://www.strategyand.pwc.com/media/file/Industry4.0.pdf%0Ahttp://www.strategyand. pwc.com/reports/industry4.0. Schwab, K. (2015) ‘The Fourth Industrial Revolution’, Nature Nanotechnology, 10(12), pp. 1005–1006. doi: 10.1038/nnano.2015.286. Shukla, A., Chaturvedi, S. and Simmhan, Y. (2017) ‘RIoTBench: A Real-time IoT Benchmark for Distributed Stream Processing Platforms’, Gsma Connected Living, (July), p. 15. doi: 10.5120/19787-1571. WEF (2017) ‘Impact of the Fourth Industrial Revolution on Supply Chains’, (October). Werner, H. (2013) ‘Supply Chain Management’, Supply Chain Strategy, pp. 174–182. doi: 10.1007/978-3-8349-3769-8. Wielki, J. (2016) ‘The Role of Internet of Things as a Key Technology Enabling the Fourth Industrial Revolution’, 7th International Multidisciplinary Symposium, (December), pp. 539–544. Zdrenka, W. (2017) ‘the Use and the Future of Big Data Analytics in Supply Chain Management’, Research in Logistics & Production, 7(2), pp. 91–102. doi: 10.21008/j.2083-4950.2017.7.2.3.
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