4.7 Article

An end-to-end Internet of Things solution for Reverse Supply Chain Management in Industry 4.0

Journal

COMPUTERS IN INDUSTRY
Volume 112, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.compind.2019.103127

Keywords

Reverse Supply Chain Management (R-SCM); Waste Electrical and Electronic Equipment (WEEE); IoT; Industry 4.0; BLE; LoRaWAN

Funding

  1. Spanish Ministry of the Economy and Competitiveness [ECO2016-75781-P, RTI2018-098156-B-052]
  2. European Union (FEDER Funds) [ECO2016-75781-P, RTI2018-098156-B-052]
  3. Engineering and Physical Sciences Research Council (EPSRC), UK [EP/N018524/1]

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The recent increase in the number of products returned from customers to retailers, supported by the adoption of environment-friendly policies, has led to a growing need to manage backward materials and information flows in the supply chain (SC) domain. Although numerous authors are contributing towards circular economy (CE) with end-of-life (EoL) approaches minimizing the negative impact of Waste Electric and Electronic Equipment (WEEE), the information infrastructure behind SC calls for novel approaches based on Information and Communication Technologies (ICT). In fact, this is one of the major challenges for the so-called Industry 4.0, where wireless technologies governed by the Internet of Things (IoT) are expected to transform the industry as currently conceived. The present work proposes an end-toend solution for Reverse Supply Chain Management (R-SCM) based on cooperation between different IoT communication standards, enabling cloud-based inventory monitoring of WEEE through embedded sensors. A case study was deployed using IoT devices and sensors, carrying out a set of experimental tests focused on wireless communications to evaluate its performance. The network configuration adopted overcomes the near real-time challenge and provides sufficient coverage to interconnect industrial areas such as warehouses or shop floors. The results point to different communication bottlenecks that need to be addressed in order to enhance the reliability of large-scale Industrial IoT (IIOT) networks. (C) 2019 Elsevier B.V. All rights reserved.

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