IoT and IIoT in supply chain management and global logistics
This article was first published on Dr. Craig Wright’s blog, and we republished with permission from the author.
The promise of systems based on the Internet of things (IoT) and industrial Internet of things (IIoT) for the supply chain industry is large and growing. Such technologies promise to increase the ability to collect data using a variety of sensors, from local recording using RFID technology to more complex wireless systems and sensors, up to the ability to log and analyze the movement of systems globally. As global interconnectivity increases with more widespread and stable wireless networks and mobile networks, the ability to send information becomes ubiquitous.
The supply chain process incorporates a range of entities and processes across the entire fabrication and distribution system, including factories, suppliers, and customers. It integrates the entire movement of systems from raw materials through to the manufacturing of parts to the delivery of those parts and the manufacturer of the final process, that is distributed through retailers to fulfill customer orders for products. Stewart (1997) defined a model for this process, known as the supply‐chain operations reference (SCOR) model. Models such as the SCOR model then led to the development of computer-assisted supply chain configuration such as the methodologies promoted by Huang, Sheoran, and Keskar (2005). While such models have demonstrated potential to revolutionize the supply chain industry, the fragmented nature of the various solutions and the lack of security have hampered adoption (Hall, Algiers, & Levitt, 2018). Nevertheless, the authors note that both vertical and horizontal integration improves the adoption of supply chain innovations.
The development of supply chain industries
Gutiérrez, van Meesnijk, and Arrowsmith (2012) researched and presented the development of more secure supply chains, focusing on developing better shipping containers. Even given the security problems and the risks associated with shipping containers (p. 3-4), the benefits presented by a standardized product demonstrate the gains achieved when a network effect is developed (p. 4). As the authors note, a combination of improved material science and miniaturized sensors fundamentally changes shipping containers, resulting in improved security and tamperproof transport. While the authors note that hybrid glass-carbon fiber panels would allow radar-transparent structures to be built (p. 4), that can be monitored to reduce people smuggling, and other illicit activities, the introduction of microsensors and IIoT could achieve such results at a far lower cost.
Importantly, shipping containers are, “above all, cheap practical vectors for commerce” (Gutiérrez, van Meesnijk & Arrowsmith, 2012, p. 5). Solutions that significantly increase the cost of transportation should be avoided; rather, economically inexpensive sensors should provide alternatives to high-cost materials. In addition, the decreasing cost of technology provides opportunities to implement different types of sensors or to integrate monitoring and control devices securely within shipping containers and transport vehicles, without necessitating the development of new metamaterials (Bandyopadhyay & Sen, 2011).
Qian, Härdle, and Chen (2020) studied industry interdependencies and the related network effects. In their analysis, the authors note that while it is difficult to precisely model interconnecting network structures amongst industries, dense, widely distributed systems can produce significant economic value. For instance, the development of standardized shipping containers increased the productivity of the initial suppliers that integrated such systems, leading to increased profitability (Kaluza et al., 2010), which in turn led to widespread adoption amongst other shipping companies. Finally, Ham and Johnston (2007) use a case study approach to document the integration of multiple systems and demonstrate how intra-industry supply chain management can be improved using distributed sensors and IoT-based monitoring.
Mohamed et al. (2020) further demonstrate that IoT systems can be extended into integrating unmanned aerial vehicles that can deliver products to the last mile or the customer. While existing problems with regulations and the integration of competing vendor products limit such deployment, such systems will eventually become part of the normal logistics deployment process. If correctly implemented, the promise, noted by Attaran (2017), of increasing interconnectivity coupled with decreasing costs will lead to the improved integration of systems and improvements across transport technology.
Qureshi and Abdullah (2013) demonstrated how intelligent transport systems could reduce operating expenses and reduce transport delays in global logistics. Subsequent research (Im, Shin, & Jeong, 2018) has demonstrated that unmanned autonomous shipping operations could become part of the distributed IoT architecture. Aslam, Michaelides, and Herodotou (2020) have referred to such developments as the Internet of Ship (IoS) paradigm and note that open challenges, including security and privacy, need to be considered fully for it to be realized. Yet, with the adoption of more secure systems based on blockchain and cryptographic technologies, peer-to-peer systems operating across a distributed network will securely implement such systems—using resilient systems that are not based on traditional centralized models (Hammi et al., 2018).
Requirements for global optimization
The development of global shipping accelerated with the integration of standardized shipping containers (Notteboom & Rodrigue, 2008). But, at present, the fragmented nature of monitoring in sensor systems, when combined with the lack of development in electronic data interchange (EDI) and other forms of shipping and logistics bills, has led to a wide fragmentation of solutions and standards. In addition, different countries, trading blocks, and regions have different requirements, and the range of proprietary systems has led to multiple proprietary systems failing to interact.
Consequently, the challenges associated with the lack of logistic standardization noted by Min et al. (2014) present both opportunities and problems for the industry. As the authors note, even within countries such as Korea, the lack of a total system architecture capable of integrating both inbound and outbound supply information limits the ability to fully utilize machine learning systems and monitor the movement of goods using advanced technologies.
Winkelhaus and Grosse (2020) argue that the development of logistic systems should mirror Industry 4.0 and seek to integrate within a wider range of structures. Of note, simple technologies such as RFID can be integrated using IoT bridges to create highly integrated smart factories (p. 20) that may be directly integrated with retail and logistic systems. In defining what the authors note to be Logistics 4.0, it is argued that the deployment of IoT systems will lead to new paradigms of mass customization (p. 20), improved logistics processes, and the creation of objects that go beyond simple identification toward the integration of complex device-based identity (p. 25).
Most critically, in conducting a literature review associated with the integration of smart technologies and IoT, Winkelhaus and Grosse (2020, pp. 25-29) demonstrate how the logistics process will be integrated from packing and the periphery of objects (p. 28) through to the wider distribution process in a manner that increases e-commerce opportunities, improves warehousing capabilities, and reduces transportation costs (p. 26). Such systems are also noted to improve order picking, storage, and just-in-time inventory management and reduce packaging and waste.
Standards organizations such as the ITU, IEC, ISO, and IMO have been instrumental in developing telecommunications and electronic system standards that have promoted the adoption of shipping and logistics technologies (Thomas & O’Malley, 2021, pp. 35-36). The ITU, for instance, was founded in 1865 and later integrated into the United Nations (UN) to standardize telecommunications protocols. Developing globally distributed systems that are enforced through national regulations will create a widespread uptake in global logistics systems that are linked to IoT technologies. Yet, the problem stems from the rapid change occurring within such industries and the current lack of integration within technologies, including 5G.
Paths to standardization and the integration of new technologies
The development of integrated and standardized systems has presented a challenge for as long as technology has existed. Still, over time, the gains through the network effect generally lead to the development of a dominant technology such as in the form of the Internet Protocol (IP), VHS, wireless standards, and other technology paths that enable widespread interconnectivity. Xiaohong, Jinlong, and Shuanping (2021) argue that evolutionary models may be used to represent the outcomes of supply chain and logistics standardization. Yet, while demonstrating that a single technology platform will become a dominant standard, such an approach fails to address the issue concerning which particular platform will become most widely deployed.
The difficulty with such an approach (Xiaohong, Jinlong, & Shuanping, 2021) is that many organizations will underinvest in the short term and monitor the investments and deployments of other suppliers and integrators. While some companies will gain significant advantages by investing in technologies that end up as a large-scale standardized platform integrating IoT and supply chain management systems, others will find the investment in obsolete technologies detrimental.
The lack of regulation and standardization in the global supply chain industry, and the fragmentation of industry bodies, have slowed the deployment of standardized systems (Thomas & O’Malley, 2021). The lack of systems in shipping operations alone has led to large-scale losses and even the injury and death of crew members (p. 33-45). In addition, the global logistics industry has failed to integrate standards even across the shipping industry, relying on trade secrets (p. 33)—in place of global standards that can increase efficiency and provide remote monitoring and maintenance even on larger vessels.
While the logistics and maritime industries are, in theory, the oldest industries focused on the development of solutions and systems for coordination by the International Standards Organisation (ISO) technical committee (Thomas & O’Malley, 2021, p. 34), many newer technologies have not been integrated into the process, and IoT-based solutions remain outside the control of the system. Given that the maritime electronic standards have been deployed for over a century and the integration of common standards for radio, radar, and shipping containers has proved so lucrative across the industry, it would be in the interest of global groups such as the United Nations (UN) to promote an integrated supply chain solution and set of standards.
Problems, barriers, and drawbacks
The integration of simple systems in IoT- and IIoT-based supply chain management can lead to many security and reliability problems if not done well. The standard systems used within sensor-based distribution, for instance, have not been created with much security or reliability in mind. Yet, integrating blockchain-based technologies into IoT-based systems may create a more resilient and secure system. In particular, integrating both agents and distributed hash table (DHT) databases linked and monitored for integrity against a blockchain network can lead to a more resilient and secure system (Wright & Savanah, 2021).
The current difficulty in implementing such a system is again tied to the lack of standardization. At present, while Cui, Gaur, and Liu (2020) demonstrate how companies are investing a significant amount in blockchain technology to increase the visibility and reliability of supply chain applications, they equally note how there are challenges in creating partnerships with companies that are offering competing solutions or using different blockchain technologies. Metka (1990) notes how multiple competing versions of a network protocol existed at the beginning of the 1990s. It was many years before the widespread adoption of the Internet Protocol led to increased network effects. At the time, many lenders and manufacturers would hold off implementing network-based systems or outsource them because of the risk associated with implementing technology that would quickly be obsolete. Similarly, many firms in the supply chain industry are waiting for a standard to be implemented across blockchain and distributed databases that will enable them to seamlessly integrate with other firms in a manner analogous to the deployment of standardized shipping containers.
Additionally, many firms have looked to the integration of technologies often referred to as ‘private blockchains’ (Cook & Zealand, 2018), not understanding that such systems are neither interoperable nor robust nor secure. Mistry et al. (2020, p. 2) note how the majority of existing IoT solutions are derived using centralized infrastructure with traditional client/server cloud structures. The difficulty derives from the single point of failure that this creates, which can “topple the entire system” (p. 2). Similarly, the authors note that the lack of trust between the entities engaged in exchanging transactions and commercial records limits the distribution range.
IoT and IIoT systems can be implemented to run over decentralized peer-to-peer architecture using advanced 5G-based network technologies (Mistry et al., 2020, p. 3). When linked to a single public blockchain, the ability to integrate simple authentication methodologies or even allow network nodes to validate transactions creates a methodology that can reduce the power consumption and computational overhead associated with such devices in integrating advanced cryptographic technologies. Yet, as the authors further note (p. 4), the lack of standards and regulations concerning both 5G and blockchain technologies has led to undesirable consequences and fragmentation.
Mumtaz et al. (2017) demonstrate how the fragmentation of wireless IIoT technologies limits the adoption and integration of such systems. Therefore, a three-level integration is recommended where industry-based solutions are developed over cross-technology integration from different suppliers, the cross-organization of information across different enterprises, and the cross-domain integration of business ecosystems across different industries (p. 31). In creating operability, different vendors also benefit from gaining access to a wider range of markets.
Creating such systems requires integration across more than mere supply chain- and logistics-based solutions. It is important to integrate the benefits that can occur outside of supply chain operations to fully recognize the benefits of such applications. Yet, the difficulty with such an approach lies in gaining agreement across different vendors, which requires gaining widespread industry adoption of particular standards. As 5G rolls out, creating new technologies provides opportunities for members to work in conjunction with each other and provide interoperable solutions (Giust et al., 2018).
Pitfalls and hurdles to avoid
Chen et al. (2014) noted the importance of standardization, and discussed the difficulties with integrating legacy applications and securing technologies based on early RFID implementations. Here, the privacy and security challenges are paramount. The requirements for IoT solutions in any industry, including supply chain management, are primarily based on low-cost, secure systems. Suppose secure systems such as the blockchain are not correctly implemented. In that case, the difficulty will be ensuring energy sustainability (p. 357) in such systems, so they may be run at low power-consumption levels. For such systems to be successful, simplified blockchain-based distributed control systems that leave verification to external nodes must be created and implemented in a standardized manner.
The promise of standardized communications that integrate secure GPS-, IoT- and IIoT-, and 5G-based communications will require the development of interoperable standards and their deployment across multiple vendors. While it may initially seem difficult, the long-term benefits mirror the creation of interoperable standards across the internet. Supply chain members need to push for interoperable standards that work across multiple industries. For instance, the growth of Web 2.0 applications occurred when standardized applications could be integrated with a process known as a mash-up (Anjomshoaa et al., 2009; Krishnan, 2019). Guinard et al. (2009) demonstrated early on how this form of integration could create a “Web of Things.” Such integration would benefit global logistics and enable the integration of supply chain management, purchasing, accounting, and sales applications to reduce cost and risk and increase profitability.
Anjomshoaa, A., Bader, G., & Tjoa, A. M. (2009). Exploiting mashup architecture in business use cases. In Proceedings of the 2009 International Conference on Network-Based Information Systems (NbiS 2009) (pp. 19-21). UIPUI. https://publik.tuwien.ac.at/files/PubDat_181268.pdf
Aslam, S., Michaelides, M. P., & Herodotou, H. (2020). Internet of ships: A survey on architectures, emerging applications, and challenges. IEEE Internet of Things Journal, 7(10), 9714-9727. https://doi.org/10.1109/JIOT.2020.2993411
Attaran, M. (2017). The Internet of things: Limitless opportunities for business and society. Journal of Strategic Innovation and Sustainability Vol, 12(1), 11. https://www.researchgate.net/profile/Mohsen-Attaran/publication/314089633_The_Internet_of_Things_Limitless_Opportunities_for_
Bandyopadhyay, D., & Sen, J. (2011). Internet of things: Applications and challenges in technology and standardization. Wireless personal communications, 58(1), 49-69. https://doi.org/10.1007/s11277-011-0288-5
Chen, S., Xu, H., Liu, D., Hu, B., & Wang, H. (2014). A vision of IoT: Applications, challenges, and opportunities with China perspective. IEEE Internet of Things Journal, 1(4), 349-359. https://doi.org/10.1109/JIOT.2014.2337336
Cook, B., & Zealand, W. N. (2018). Blockchain: Transforming the seafood supply chain. World Wide Fund for Nature. https://wwfnz.awsassets.panda.org/downloads/draft_blockchain_report_1_4_1.pdf
Cui, Y., Gaur, V., & Liu, J. (2020). Blockchain collaboration with competing firms in a shared supply chain: Benefits and challenges. Available at SSRN. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3626028
Giust, F., Sciancalepore, V., Sabella, D., Filippou, M. C., Mangiante, S., Featherstone, W., & Munaretto, D. (2018). Multi-access edge computing: The driver behind the wheel of 5G-connected cars. IEEE Communications Standards Magazine, 2(3), 66-73. doi: 10.1109/MCOMSTD.2018.1800013
Guinard, D., Trifa, V., Pham, T., & Liechti, O. (2009, June). Towards physical mashups in the web of things. In 2009 Sixth International Conference on Networked Sensing Systems (INSS) (pp. 1-4). IEEE. https://doi.org/10.1109/INSS.2009.5409925
Gutiérrez, E., van Meesnijk, W., & Arrowsmith, D. (2012). An overview of research programmes and prospective technology in the development of more secure supply chains: The Case of Shipping Containers. JRC Europia. https://publications.jrc.ec.europa.eu/repository/bitstream/JRC70120/lbna25298enn.pdf
Hall, D. M., Algiers, A., & Levitt, R. E. (2018). Identifying the role of supply chain integration practices in the adoption of systemic innovations. Journal of management in engineering, 34(6), 04018030. https://ascelibrary.org/doi/full/10.1061/%28ASCE%29ME.1943-5479.0000640
Ham, Y. N., & Johnston, R. B. (2007). A process model of inter-organisational SCM initiatives adoption. In Supply chain management: Issues in the new era of collaboration and competition (pp. 191-225). IGI Global.
Hammi, M. T., Hammi, B., Bellot, P., & Serhrouchni, A. (2018). Bubbles of Trust: A decentralized blockchain-based authentication system for IoT. Computers & Security, 78, 126-142. https://doi.org/10.1016/j.cose.2018.06.004
Huang, S. H., Sheoran, S. K., & Keskar, H. (2005). Computer-assisted supply chain configuration based on supply chain operations reference (SCOR) model. Computers & Industrial Engineering, 48(2), 377-394. https://doi.org/10.1016/j.cie.2005.01.001
Im, I., Shin, D., & Jeong, J. (2018). Components for smart autonomous ship architecture based on intelligent information technology. Procedia computer science, 134, 91-98.
Kaluza, P., Kölzsch, A., Gastner, M. T., & Blasius, B. (2010). The complex network of global cargo ship movements. Journal of the Royal Society Interface, 7(48), 1093-1103. https://doi.org/10.1098/rsif.2009.0495
Krishnan, K. (2019). Building Big Data Applications. Academic Press.
Metka, T. (1990). OSI product survey. Library hi tech.
Min, H., Ko, H. J., Lim, Y. K., Park, J. W., & Cho, Y. K. (2014). Challenges and opportunities for logistics standardisation in Asia-Pacific countries: a descriptive case study. International Journal of Logistics Systems and Management, 17(3), 357-380.
Mistry, I., Tanwar, S., Tyagi, S., & Kumar, N. (2020). Blockchain for 5G-enabled IoT for industrial automation: A systematic review, solutions, and challenges. Mechanical Systems and Signal Processing, 135, 106382. https://doi.org/10.1016/j.ymssp.2019.106382
Mohamed, N., Al-Jaroodi, J., Jawhar, I., Idries, A., & Mohammed, F. (2020). Unmanned aerial vehicles applications in future smart cities. Technological Forecasting and Social Change, 153, 119293. https://doi.org/10.1016/j.techfore.2018.05.004
Mumtaz, S., Alsohaily, A., Pang, Z., Rayes, A., Tsang, K. F., & Rodriguez, J. (2017). Massive Internet of Things for industrial applications: Addressing wireless IIoT connectivity challenges and ecosystem fragmentation. IEEE Industrial Electronics Magazine, 11(1), 28-33. https://doi.org/10.1109/MIE.2016.2618724
Notteboom, T., & Rodrigue, J. P. (2008). Containerisation, box logistics and global supply chains: The integration of ports and liner shipping networks. Maritime economics & logistics, 10(1), 152-174. https://doi.org/10.1057/palgrave.mel.9100196
Qian, Y., Härdle, W., & Chen, C.Y.-H. (2020). Modelling industry interdependency dynamics in a network context. Studies in Economics and Finance, 37(1), 50-70. https://doi.org/10.1108/SEF-07-2019-0272
Qureshi, K. N., & Abdullah, A. H. (2013). A survey on intelligent transportation systems. Middle-East Journal of Scientific Research, 15(5), 629-642.
Stewart, G. (1997). Supply‐chain operations reference model (SCOR): the first cross‐industry framework for integrated supply‐chain management. Logistics Information Management, 10(2), 62-67. https://doi.org/10.1108/09576059710815716
Thomas, D., & O’Malley, S. (2021). The Necessity of Standards for Maritime Informatics in Ship Operations. Maritime Informatics (pp. 33-45). Springer, Cham. https://doi.org/10.1007/978-3-030-50892-0_3
Winkelhaus, S., & Grosse, E. H. (2020). Logistics 4.0: a systematic review towards a new logistics system. International Journal of Production Research, 58(1), 18-43. https://doi.org/10.1080/00207543.2019.1612964
Wright, C. S., & Savanah, S. (2021). U.S. Patent No. 11,128,607. Washington, DC: U.S. Patent and Trademark Office. https://patentimages.storage.googleapis.com/20/7b/ca/6277c15389b134/US11128607.pdf
Xiaohong, Z., Jinlong, C., & Shuanping, G. (2021). Network effect in shared supply chain platform value co-creation behavior in evolutionary game. Journal of Intelligent & Fuzzy Systems, (Preprint), 1-12.
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