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A conceptual framework for real-time adaptive supply chain systems based on Internet of Things (IoT)

  • Author / Creator
    Ramakrishnan, Parthasarathi
  • Supply chain (SC) systems are often subject to high operational dynamics due to the large number of resources involved, frequent interaction between them, exhaustive human participation and timely decisions being made. This dynamic nature of SCs can be organized more efficiently by adopting Internet of Things (IoT) to capture real-time SC information and its associated resources. Even though the modern industry has gained a remarkable benefit from IoT, the potential to improve Supply Chain Management (SCM) by integrating them into Enterprise Resource Planning (ERP) process, has not been fully explored. In response, this study examines how a robust information structure can be designed and real-time schemes for controlling the SCs inherent to real-life systems applied. Motivated by the comprehensive application of industrial Internet-of-Things (IoT) systems, this research investigates the typical SC execution processes to design cost-effective IoT solutions. The internal and external SC processes are first examined separately. A conceptual framework is proposed to study the capabilities of IoT on applied in SCM, starting with the IoT impact on SCM and then describes a theoretical framework that creates a system linking the four aspects of the supply chain (warehouse, supplier, logistics, and client) using IoT. It has been shown that the information sharing across the selected supply chain partners can be achieved using state-of-the-art technologies. This framework demonstrates how IoT could enhance SCM, which helps the members of the supply chain to improve their overall performance through improved information sharing, efficient resource utilization and reduced loss of merchandise along the supply chain. The significant components of the proposed framework are data collecting devices, the network for transmitting the received data and the integrated information management system where the data collected is processed and analyzed using big data analytical tools by end users. Additionally, this framework explores all possible supply chains for a product, and suggests an appropriate supply chain primarily, based on the client’s desires and demands. The ability of the framework to discover the viable supply chains is accomplished with the aid of data sharing among the suppliers. This research also proposes a mathematical model to measure the manufacturer’s SCM performance improvement by adopting IoT. The proposed mathematical model is expanded to measure the performance of the internal and the entire supply chain. Finally, the integration of the proposed frameworks with the existing ERP systems is discussed with the help of a case study.

  • Subjects / Keywords
  • Graduation date
    Spring 2018
  • Type of Item
    Thesis
  • Degree
    Master of Science
  • DOI
    https://doi.org/10.7939/R3542JQ31
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.