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Investigation of Printing Parameters of Additive Manufacturing Process for Sustainability Using Design of Experiments

Marwan Khalid, Qingjin Peng

2021Journal of Mechanical Design47 citationsDOI

Abstract

Abstract Additive manufacturing (AM) offers many advantages to make objects compared to traditional subtractive manufacturing methods. For example, complex geometries can be easily fabricated, and lightweight parts can be formed while maintaining the parts strength for the low carbon footprint, low material consumption and waste. But there are some areas for AM to improve in sustainability, reliability, productivity, robustness, material diversity, and part quality. Life-cycle assessment studies have identified that the AM printing stage has a big impact on the life-cycle sustainability of 3D printed products. AM building parameters can be properly selected to improve the sustainability of AM. This paper explores the fused deposition modeling (FDM) process parameters for sustainability to reduce the process energy and material consumption. Investigated parameters include the printing layer height, number of shells, material infilling percentage, infilling type, and building orientation. Taguchi design of experiments approach and statistical analysis tools are used to find optimal parameter settings to improve the sustainability of the FDM process. Models formulated in this research can be easily extended to other AM processes.

Topics & Concepts

SustainabilitySubtractive colorTaguchi methodsCarbon footprintMaterial flowProcess engineeringEnergy consumptionProcess (computing)Manufacturing engineeringLife-cycle assessment3D printingRobustness (evolution)EngineeringMechanical engineeringComputer scienceEngineering drawingReliability engineeringProduction (economics)Greenhouse gasElectrical engineeringBiologyBiochemistryVisual artsArtOperating systemEcologyGeneEconomicsMacroeconomicsChemistryMachine learningAdditive Manufacturing and 3D Printing TechnologiesInnovations in Concrete and Construction MaterialsManufacturing Process and Optimization
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