The Digital Transformation of Logistics. Группа авторов

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discuss e‐commerce in China and its CEP market, and highlight new challenges in the competitive environment that increase the burden on all market players. In addition, they share a case study about the successful application of artificial intelligence in a CEP company in China.

      Thanks to the inventor and entrepreneur Elon Musk and his company Tesla, autonomous vehicles have been pushed to the forefront of discussion about emerging technology. Many other automotive manufacturers are also hard at work creating their own versions of driverless vehicles. The topic has received a lot of attention in the logistics industry due to the potential cost savings of using autonomous truck fleets as well as the concerns that it will lead to the mass unemployment of truck drivers. The technology also has applications within factories and warehouses where autonomously guided vehicles could handle the picking and storage of goods. In Understanding the Impacts of Autonomous Vehicles in Logistics, Lionel Willems writes about the feasibility and timeline of rolling out automated trucks and warehouses as well as the intricacies of adopting these solutions.

      1 McAfee, A. and Brynjolfsson, E. (2014). The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies. Zurich: W. W. Norton.

      2 Schwab, K. and Davis, N. (2018). Shaping the Future of the Fourth Industrial Revolution: A Guide to Building a Better World. New York: Currency.

       Axel Neher

       Bosch Rexroth, Shanghai, China

      In this chapter, the topic of how this “new” world of connected Things impacts logistics and supply chain management (SCM) will be discussed. In analogy to Industry 4.0, some call this Logistics 4.0 (Bousonville 2017; Strandhagen et al. 2017).

       Identification and sensor technologyTo connect Things, the first step is to know about the Thing (what, where). So, one crucial aspect of IoT is the identification and sensor technology enabling the automated identification of an object (Thing) and collection of “sensed” real‐time data (e.g. temperature, acceleration, humidity, vibration, and location).

       Networking technology (e.g. 5G, Wi‐Fi 6)Enabling to connect the Things in a fast and reliable way to interact (network) with each other. With more Things to be connected and thus more data to be transmitted, new powerful networking technologies are required to provide the capability of transmitting big data volume of many Things in parallel with a short latency.

       Big dataAs a result (or intention) of connecting everything with everything, a lot of data are created. New technologies provide the possibility to transmit (see networking technology), store, and analyze a huge amount of data – big data. Especially the topic of big data analytics and decisions based on a huge amount of data is seen as one big lever to improve speed and quality of management and pave the way for artificial intelligence (AI).

       Artificial intelligenceEnabling automated and autonomous decision making and operations, based on self‐learning systems without the intervention of humans.

       Autonomous robots and vehicles (e.g. drones, automated guided vehicle [AGV])Material handling and transportation are done by robots or AGVs that execute the defined tasks in an automated or autonomous way in interaction with other Things.

       Augmented reality (AR) and virtual reality (VR)Devices supporting decisions and processes by providing instructions via augmented and virtual reality technologies (e.g. headsets or smart glasses showing the worker on a small display in the glasses what to do next).

      Logistics managers not only have to understand these new technologies, but also the overall concept of IoT and its implications for managing material and information flows in global supply chains.

      One prevailing “new” quality of IoT is “connection.” Therefore, the first new topic in logistics management is to think about how to get connected”. Acknowledging that the overall approach of IoT is to connect everything with everything, it is important to reflect what this will mean for logistics. What are the “Things” in the supply chain we want to connect to be able to operate faster and more efficiently?

      One of the major goals of having connected Things is to gather big data. Logistics management must define which data is needed, e.g. data about the on‐time delivery of products, quality of the product in transit, or security of facilities and vehicles, and how to make the best use of the data for their business customers. Hence, the second new topic in logistics management is to define how IoT is used to “get decisions in a better way than before.

Schematic illustration of IoT logistics.

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