Determination of quality classes for material extrusion additive manufacturing using image processing

Key Points

• Quality classes for material extrusion were effectively determined using image processing techniques, enhancing production reliability.
• Key evidence indicated that image analysis improved classification accuracy by at least 30%, facilitating better quality assurance.
• Data was collected through image processing assessments on various samples of additive manufacturing outputs across different settings.
• This highlights the importance of integrating image processing for quality control in manufacturing, potentially improving production workflows.