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This chapter highlights recent developments and provides an overview of the rapid application of fused deposition modelling (FDM) for polymeric smart and composites. The review is divided into sections that describe the processing conditions and characteristics of FDM components made of polymer and its composites as well as shape memory polymers/composites. The chapter covers a wide range of applications, including PVDF structures and components. While FDM adoption has been rapid in this field, more coordinated efforts in the areas of smart polymer feedstock synthesis, process tuning, and testing are required. This chapter provides an overview of 3D printed smart polymer materials and composites as well as their properties, performance, and potential applications. Additionally, this chapter discusses the motivation for future 3D printing research.

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This chapter provides an analysis of the state-of-the-art in ML applications for optimizing the additive manufacturing process. This chapter primarily presents a review of the literature on the use of machine learning (ML) in optimizing the additive manufacturing process at various stages. The chapter identifies ML-researched areas in which ML can be used to optimize processes such as process design, process plan and control, process monitoring, quality enhancement of additively manufactured products, and so on. In addition, general literature on the intersection of additive manufacturing and machine learning will be presented. The benefits and drawbacks of ML for additive manufacturing will be discussed, as well as existing obstacles that are currently limiting applications.