Optimization of process parameters for fused filament fabrication using tool path reversing

• Fused filament fabrication (FFF) is one of the most economical additive manufacturing techniques. The difficulty in estimating the effects of process parameters on the mechanical properties of the manufactured part, hinders the wide spread industrial adaptation of FFF. The quality of a part manufactured by FFF highly depends on the process parameters so, it is imperative to develop a technique to fine tune the process parameters. The large number of process parameters and complex relationship between the geometry, parameters and mechanical properties makes it impractical to derive an analytical or an empirical relationship and calls for the use of a finite element (FE) model. A few commercially available FE packages support the simulation of a select types of additive manufacturing techniques - such packages primarily focus on metal additive manufacturing. A novel method to automatically build a FE model from a geometry and given process parameters is developed in this paper. Image recognition techniques are used to analyse the GCode instructions to build a FE model. As the FE model is built by using the same instruction set a FFF machine uses to manufacture the part, the generated FE model will encompass the effects of all parameters which affect the mechanical behaviour of the manufactured part. The automatic generation of a FE model enables the optimization of the FFF parameters.

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Materialteknik -- Bearbetnings-, yt- och fogningsteknik (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Materials Engineering -- Manufacturing, Surface and Joining Technology (hsv//eng)

Nyckelord

Additive manufacturing

Fused deposition modelling

Fused filament fabrication

GCode parser

Optimization

Process parameters

Stiffness prediction

Tool path reversing

Additives

Composite materials

Fabrication

Image recognition

Mechanical properties

Automatic Generation

Complex relationships

Empirical relationships

Instruction set

Manufacturing techniques

Mechanical behaviour

Optimization of process parameters

3D printers

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