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Surrogate Model Development for Digital Experiments in Welding
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Carbon emission warning method for machine tool manufacturing process based on dynamic adaptive EWMA control chart.

Zhenan Song1, Dan Liu1, Hongyu Sha1

  • 1Shenyang University of Technology, Tiexi District, No.111, Shenliao West Road, Shenyang, China.

Environmental Science and Pollution Research International
|August 22, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a novel adaptive dynamic EWMA method for early carbon emission warnings in machine tool manufacturing. It enhances monitoring accuracy and responsiveness for sustainable industrial growth.

Keywords:
Adaptive dynamic EWMA control chartCarbon emission warningHHO algorithmMachine tool manufacturing process

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Area of Science:

  • Industrial Engineering
  • Environmental Science
  • Manufacturing Technology

Background:

  • Machine tools are critical industrial equipment with significant carbon footprints.
  • Effective management of manufacturing carbon emissions is essential for sustainability.
  • Existing methods struggle with uncertainties in monitoring abnormal carbon emissions.

Purpose of the Study:

  • To develop a novel method for early carbon emission warnings in machine tool manufacturing.
  • To address challenges in identifying and monitoring abnormal carbon emissions.
  • To foster environmentally conscious growth in the machine tool industry.

Main Methods:

  • An adaptive dynamic exponentially weighted moving average (EWMA) control chart was developed.
  • Dynamic sampling and adaptive principles were utilized for enhanced monitoring.
  • An enhanced Harris Hawks Optimization (HHO) algorithm was employed for multi-objective optimization.

Main Results:

  • The proposed method demonstrated rapid responsiveness to abnormal carbon emissions.
  • The adaptive dynamic EWMA chart effectively identified and alerted on emission anomalies.
  • The case study on a five-axis machine tool validated the approach's efficacy.

Conclusions:

  • The novel EWMA-based method provides a viable strategy for real-time carbon emission monitoring.
  • This approach supports high-quality and sustainable development in machine tool manufacturing.
  • The study confirms the feasibility and effectiveness of the proposed early warning system.