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<p>Reducing carbon emissions and achieving sustainability targets in manufacturing are crucial challenges. This study proposes the use of contextual Bayesian optimization (CBO) as a data-efficient method to optimize process parameters, specifically aiming to reduce the carbon footprint. The methodology is demonstrated using fused deposition modeling (FDM). The goal of this research is to develop and demonstrate an optimization framework that accounts for external factors—specifically, ambient temperature—in the optimization of process parameters such as nozzle temperature, infill percentage, and print speed. To model the relationship between inputs and outputs, a Gaussian process (GP) model is employed. The results show a 26% reduction in carbon footprint and a 22% cost saving, while still maintaining print quality. The study highlights the potential of CBO in sustainable manufacturing and outlines its applicability to other processes, such as turning, grinding, or milling.</p>

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Optimizing process parameters in manufacturing to reduce carbon footprint with contextual Bayesian optimization

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年7月17日

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  • Matteo C. Vincent,
  • Markus Maier,
  • Konrad Wegener

摘要

Reducing carbon emissions and achieving sustainability targets in manufacturing are crucial challenges. This study proposes the use of contextual Bayesian optimization (CBO) as a data-efficient method to optimize process parameters, specifically aiming to reduce the carbon footprint. The methodology is demonstrated using fused deposition modeling (FDM). The goal of this research is to develop and demonstrate an optimization framework that accounts for external factors—specifically, ambient temperature—in the optimization of process parameters such as nozzle temperature, infill percentage, and print speed. To model the relationship between inputs and outputs, a Gaussian process (GP) model is employed. The results show a 26% reduction in carbon footprint and a 22% cost saving, while still maintaining print quality. The study highlights the potential of CBO in sustainable manufacturing and outlines its applicability to other processes, such as turning, grinding, or milling.