Elsevier

Computers in Industry

Volume 112, November 2019, 103127
Computers in Industry

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

https://doi.org/10.1016/j.compind.2019.103127Get rights and content

Highlights

  • End-to-end IoT communication infrastructure for Reverse Supply Chain Management.

  • RFID, BLE and MQTT standards cooperation for inventory-management.

  • LoRaWAN-based context information network for facility-monitoring.

  • Deployment of a heterogeneous IoT network solution for WEEE management.

  • A case study based on the recovery of computer components was deployed and tested.

Abstract

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-to-end 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.

Introduction

The circular economy (CE) is motivated by an increasing need to minimize the economic and environmental impact of end-of-life (EoL) products [1]. This industrial strategy refers to the long-lasting design, refurbishment, remanufacture, repair, recycling or reuse of products in order to achieve the maximum benefit and avoid negative impacts, with Waste Electrical and Electronic Equipment (WEEE) being a growing concern [2]. According to the United Nations University (UNU), 44.7 million metric tonnes of e-waste was generated in 2016, with future estimations being even larger [3]. While posing significant risks for the environmental and human health, it contains recoverable raw materials with an estimated value of 55 billion euros.

Reverse logistics (RL) has become a key competence of both the supply chain (SC) and reverse supply chain (RSC) [4], [5], in which products flow from customers to manufacturers. Reverse Supply Chain Management (R-SCM) emerges as a new challenge, given the necessity of managing every single stage where products should be handled and distributed towards manufacturers, with multiple recovery options increasing the uncertainties faced by companies [6].

The introduction of Information and Communication Technologies (ICT) in SC and, especially, the Internet of Things (IoT) can significantly improve process-oriented performance, reduce energy consumption and provide SC with a ubiquitous information infrastructure [7]. By enabling the cooperation of wireless technologies, IoT is an accelerator of the Fourth Industrial Revolution: Industry 4.0 [8], [9]. This brand-new concept is transforming the industrial paradigm, being Cyber-Physical Systems (CPS), cloud and fog computing essential pillars [10], [11]. The impact of IoT on industries is such that the concept of Industrial IoT (IIoT) is becoming increasingly popular and has consequently been adopted in several industrial applications governed by IoT technologies [12].

Despite the large body of literature addressing IoT applications in the supply chain management (SCM) domain, the RSC field specifically needs more integrated approaches based on IoT communication standards to manage the RL of WEEE in real contexts. To fill this gap in the literature, this paper presents a novel Industry 4.0 end-to-end IoT framework as a solution for WEEE management.

The following aspects of this work can be highlighted. First, the proposal of a heterogeneous IoT network enabling low-power and low-cost SCM operations in the context of Industry 4.0. For this, we propose the cooperation of three emerging IoT technologies for R-SCM, presenting a case study based on the recovery of WEEE from computer-based components. Second, the implementation of an end-to-end system, addressing the deployment of sensor-nodes, the network infrastructure, and its integration with a cloud-based inventory-management platform. In order to evaluate end-to-end performance, a set of experimental tests are proposed, carried out and discussed.

The three wireless technologies selected and addressed in this work are RFID [13], Bluetooth Low Energy (BLE) [14] and LoRaWAN [15], which are tested under different communication schemes and physical-layer parameters. Our results illustrate the suitability of the proposed IoT standards for R-SCM purposes, underlining communication optimizations for large-scale industrial deployments.

The paper is organized as follows: in Section 2 we review the literature; the IoT framework for R-SCM is presented in Section 3; Section 4 presents a WEEE-focused case study; Section 5 addresses the experiments, results and discussion; and finally, Section 6 provides conclusions and identifies future research lines.

Section snippets

Related works

This section provides a review of the most relevant works and applications of computer-based systems in the industrial sector, highlighting the main contributions and gaps that encourage us to propose and evaluate an end-to-end heterogeneous IoT framework for R-SCM purposes.

IoT framework for R-SCM

This section describes an IoT R-SCM framework proposal to manage WEEE, aimed at providing manufacturers with a novel ubiquitous information infrastructure behind SC for tracking of parts to be recovered. For this, we first select the set of IoT standards for the deployment (based on a communication-range criterion) and, then, the main stages of the framework are described according to their functionality and information flows.

Our proposed IoT-based WEEE management framework is supported by a

Case study

Personal computers have become one of the major concerns regarding waste-streams generation, given a considerable decrease in their average useful life over the years and a high environmental impact associated with their disposal. Nevertheless, most components found in computers are in good condition for reuse or refurbishment and, depending on their added value, these can be brought back to the required degree of quality as presented in [26].

Following this idea, the scenario selected for the

Results and discussion

The experiments were designed to satisfy a set of performance tests to assess the strengths and limitations of the R-SCM proposal under IoT criteria [76]. These tests are described in Table 5 and scaled according to real-world experiments with IoT devices instead of simulations.

The TNSC metric quantifies the influence of increasing Smart Containers on latency (BLE standard); TOA the Time-on-Air at LoRaWAN end-devices as a function of payload, complying with ETSI [77] regulations of 1% duty

Conclusions

This work presents an Industry 4.0 solution for R-SCM based on a heterogeneous IoT network following DSC objectives. BLE and RFID technologies are proposed for inventory management using Smart Containers, while a LoRaWAN context network is responsible for environmental monitoring of industrial facilities. The network is governed by a Hybrid Gateway, responsible for receiving BLE information and forwarding it to two back-ends: an inventory-monitoring platform in AWS (via MQTT) and a

Declarations of interest

None.

Acknowledgments

This work was partially supported by the Spanish “Ministry of the Economy and Competitiveness” and the European Union (FEDER Funds) under projects ECO2016-75781-P and RTI2018-098156-B-C52, and the Engineering and Physical Sciences Research Council (EPSRC), UK, grant no. EP/N018524/1.

References (83)

  • S. Farahani et al.

    Environmentally friendly disposition decisions for end-of-life electrical and electronic products: the case of computer remanufacture

    J. Clean. Prod.

    (2019)
  • X. Yang et al.

    Intelligent products: from lifecycle data acquisition to enabling product-related services

    Comput. Ind.

    (2009)
  • F.M. Asif et al.

    A practical ICT framework for transition to circular manufacturing systems

    Proc. CIRP

    (2018)
  • F. Gu et al.

    Internet of things and Big Data as potential solutions to the problems in Waste Electrical and Electronic Equipment management: an exploratory study

    Waste Manage.

    (2017)
  • A. Rajeev et al.

    Evolution of sustainability in supply chain management: a literature review

    J. Clean. Prod.

    (2017)
  • A. Gunasekaran et al.

    Information systems in supply chain integration and management

    Eur. J. Oper. Res.

    (2004)
  • G. Büyüközkan et al.

    Digital Supply Chain: literature review and a proposed framework for future research

    Comput. Ind.

    (2018)
  • K. Govindan et al.

    A review of reverse logistics and closed-loop supply chains: a Journal of Cleaner Production focus

    J. Clean. Prod.

    (2017)
  • H. Boyes et al.

    The Industrial Internet of Things (IIoT): an analysis framework

    Comput. Ind.

    (2018)
  • Y. Lu

    Industry 4.0: a survey on technologies, applications and open research issues

    J. Ind. Inform. Integr.

    (2017)
  • I. Lee et al.

    The Internet of Things (IoT): applications, investments, and challenges for enterprises

    Business Horizons

    (2015)
  • E. Hofmann et al.

    Industry 4.0 and the current status as well as future prospects on Logistics

    Comput. Ind.

    (2017)
  • I. Castelo-Branco et al.

    Assessing Industry 4.0 readiness in manufacturing: evidence for the European Union

    Comput. Ind.

    (2019)
  • M. Tao et al.

    Multi-layer cloud architectural model and ontology-based security service framework for IoT-based smart homes

    Fut. Gen. Comput. Syst.

    (2018)
  • C.P. Baldé et al.

    The Global E-waste Monitor 2017 – Quantities, Flows, and Resources

    (2017)
  • R. Dekker et al.

    Reverse Logistics: Quantitative Models for Closed-Loop Supply Chains

    (2013)
  • M. Hermann et al.

    Design principles for Industrie 4.0 scenarios

  • L.F. Bittencourt et al.

    Mobility-aware application scheduling in fog computing

    IEEE Cloud Comput.

    (2017)
  • S. Jeschke et al.

    Industrial Internet of Things and Cyber Manufacturing Systems

  • Bluetooth SIG

    Bluetooth 4.0, 4.1 and 4.2 Specifications

    (2014)
  • LoRa Alliance

    LoRaWAN v1.1 Specification

    (2017)
  • A.V. Kneese et al.

    Economics and the Environment: A Materials Balance Approach

    (1971)
  • F. Preston

    A Global Redesign? Shaping the Circular Economy

    (2012)
  • The Ellen MacArthur Foundation

    Towards the circular economy

    J. Ind. Ecol.

    (2013)
  • K. Vella

    The Circular Economy: An Investment with A Triple Win

    (2016)
  • Z. Pei et al.

    Consumers’ legitimate and opportunistic product return behaviors in online shopping

    J. Electron. Commerce Res.

    (2018)
  • European Parliament and Council

    Directive 2012/19/EU of the European Parliament and of the Council of 4 July 2012 on Waste Electrical and Electronic Equipment, WEEE

    Off. J. Eur. Union

    (2012)
  • European Commission

    Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions on a Monitoring Framework for the Circular Economy

    (2018)
  • Eurostat

    Your Key European Statistics: Circular Economy

    (2015)
  • D. Parker et al.

    Remanufacturing Market Study

    (2015)
  • F. Garcia-Mui na et al.

    The paradigms of Industry 4.0 and circular economy as enabling drivers for the competitiveness of businesses and territories: the case of an Italian Ceramic Tiles Manufacturing Company

    Soc. Sci.

    (2018)
  • Cited by (115)

    View all citing articles on Scopus
    View full text