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Industrial IoT and AI implementation in vehicular logistics and supply chain management for vehicle mediated transportation systems

Author

Listed:
  • Amitabh Bhargava

    (Graphic Era Deemd to be University)

  • Deepshikha Bhargava

    (DIT University)

  • P. Naveen Kumar

    (Amrita Vishwa Vidyapeetham University)

  • Guna Sekhar Sajja

    (University of the Cumberlands)

  • Samrat Ray

    (Peter The Great Saint Petersburg Polytechnic University)

Abstract

Internet in the present time has deeply impacted the demand and supply of materials. The constant demand of fast supply of logistics at cheapest cost has built a pressure of competitiveness among the manufacturing industries. To fulfil the requirement of present customers has led to the development of IIoT for smart manufacturing and smart logistics. Smart logistics has become the essential need of industry 5.0 to minimise logistic time and cost and maximise the customer satisfaction and organisation profit. This work presents the IIoT model integrated with intelligent logistics, transportation management structure for optimised logistic, betterment of customer experience and customer satisfaction, minimise transportation cost, the present work focus on the certain paraments of logistic scheduling such as optimal route identification, real time monitoring of logistic vehicle parameters such as fuel, wheel axel and engine vibration, temperature monitoring, customise and efficient designing of maintenance schedule and predictive maintenance of logistic vehicle for efficient working. The present work shows the improvement from 77 to 98% in overall performance of the proposed model along with increase in customer satisfaction, process efficiency, decreasing cost of operation with energy efficient and low latency performance of the new IIoT based framework.

Suggested Citation

  • Amitabh Bhargava & Deepshikha Bhargava & P. Naveen Kumar & Guna Sekhar Sajja & Samrat Ray, 2022. "Industrial IoT and AI implementation in vehicular logistics and supply chain management for vehicle mediated transportation systems," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(1), pages 673-680, March.
    • Handle: RePEc:spr:ijsaem:v:13:y:2022:i:1:d:10.1007_s13198-021-01581-2
    DOI: 10.1007/s13198-021-01581-2
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    References listed on IDEAS

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    1. Dutta, Pankaj & Choi, Tsan-Ming & Somani, Surabhi & Butala, Richa, 2020. "Blockchain technology in supply chain operations: Applications, challenges and research opportunities," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
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    Cited by:

    1. Rashi Saxena & E. Gayathri & Lalitha Surya Kumari, 2023. "Semantic analysis of blockchain intelligence with proposed agenda for future issues," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(1), pages 34-54, March.
    2. Miljenko Mustapić & Maja Trstenjak & Petar Gregurić & Tihomir Opetuk, 2023. "Implementation and Use of Digital, Green and Sustainable Technologies in Internal and External Transport of Manufacturing Companies," Sustainability, MDPI, vol. 15(12), pages 1-25, June.
    3. Ihab K. A. Hamdan & Wulamu Aziguli & Dezheng Zhang & Eli Sumarliah, 2023. "Machine learning in supply chain: prediction of real-time e-order arrivals using ANFIS," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(1), pages 549-568, March.
    4. Maja Trstenjak & Tihomir Opetuk & Goran Đukić & Hrvoje Cajner, 2022. "Logistics 5.0 Implementation Model Based on Decision Support Systems," Sustainability, MDPI, vol. 14(11), pages 1-19, May.
    5. Khalid Zaman & Muhammad Khalid Anser & Usama Awan & Wiwik Handayani & Hailan Salamun & Abdul Rashid Abdul Aziz & Mohd Khata Jabor & Kamalularifin Subari, 2022. "Transportation-Induced Carbon Emissions Jeopardize Healthcare Logistics Sustainability: Toward a Healthier Today and a Better Tomorrow," Logistics, MDPI, vol. 6(2), pages 1-17, April.

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