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IoT-Driven Intelligent Scheduling Solution for Industrial Sewing Based on Real-RCPSP Model

Author

Listed:
  • Huu Dang Quoc

    (Faculty of Economic Information System and E-commerce, Thuongmai University, 79 Ho Tung Mau, Cau Giay, Ha Noi City 100000, Vietnam)

  • Loc Nguyen The

    (Faculty of Information Technology, Hanoi National University of Education, 136 Xuan Thuy, Cau Giay, Ha Noi City 100000, Vietnam)

  • Truong Bui Quang

    (Faculty of Economic Information System and E-commerce, Thuongmai University, 79 Ho Tung Mau, Cau Giay, Ha Noi City 100000, Vietnam)

  • Phuong Han Minh

    (Faculty of Economic Information System and E-commerce, Thuongmai University, 79 Ho Tung Mau, Cau Giay, Ha Noi City 100000, Vietnam)

Abstract

Applying IoT systems in industrial production allows data collection directly from production lines and factories. These data are aggregated, analyzed, and converted into reports to support manufacturers. Business managers can quickly and easily grasp the situation, making timely and effective management decisions. In industrial sewing, IoT applications collect production data from sewing lines, especially from industrial sewing machines, and transmit that data to cloud-based systems. This allows businesses to analyze production situations, thereby improving management capacity. This article explores the implementation of IoT applications at industrial sewing enterprises, focusing on data collection during the production process and proposing a data structure to integrate this information into the company’s MIS system enterprise. In addition, the research also considers applying the Real-RCPSP problem to support businesses in planning automatic production operations.

Suggested Citation

  • Huu Dang Quoc & Loc Nguyen The & Truong Bui Quang & Phuong Han Minh, 2025. "IoT-Driven Intelligent Scheduling Solution for Industrial Sewing Based on Real-RCPSP Model," Future Internet, MDPI, vol. 17(2), pages 1-23, January.
  • Handle: RePEc:gam:jftint:v:17:y:2025:i:2:p:56-:d:1577920
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    References listed on IDEAS

    as
    1. de Sousa Jabbour, Ana Beatriz Lopes & Jabbour, Charbel Jose Chiappetta & Foropon, Cyril & Godinho Filho, Moacir, 2018. "When titans meet – Can industry 4.0 revolutionise the environmentally-sustainable manufacturing wave? The role of critical success factors," Technological Forecasting and Social Change, Elsevier, vol. 132(C), pages 18-25.
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