Functionally Graded Materials (FGM) parts are heterogeneous objects with material composition and microstructure that change gradually into the parts. The distinctive feature of FGM structure gives the possibility of selecting the distribution of properties to achieve the desired functions. Today, multi-material parts manufactured with additive manufacturing processes are not functional. To move from these samples to functional and complex parts, it is necessary to have an overall process control. This global approach requires a control of process parameters and an optimal manufacturing strategy. This paper presents a process modeling and a system control to manufacture FGM parts with a direct laser deposition system. This works enable to choose an adapted manufacturing strategy and control process parameters to obtain the required material distribution and the required geometry.
The concept of Functionally Graded Materials (FGM) has been proposed in 80s to develop materials capable of withstanding thermal and mechanical stresses in propulsion systems and space shuttle fuselage (Niino et al., 1987). FGM parts are heterogeneous objects with materials that change gradually into the parts (Qian and Dutta, 2003). The result is a variation in composition and structure gradually over volume which enables to choose the distribution of properties to achieve required functions (Ocylok et al., 2010). These multi-material parts offer great promise for aeronautical (Domack and Baughman, 2005) and biomedical (Pompe et al., 2003) applications because it is possible to change physical, chemical, biochemical or mechanical properties.
Since the concept of FGM advent, some research studies was dedicated to manufacture these materials and a large variety of methods of production – gas phase, liquid phase and solid phase methods – has been developed (Kieback et al., 2003). Additive manufacturing processes are potentially suitable to manufacture FGM parts. Moreover they have the advantage to allowing the fabrication of morphologically complex parts by the addition of material which are fused with an energy source. Nowadays, with these processes, it is possible to obtain customized homogeneous parts from digital data with various materials: metals, ceramics and polymers (Bandyopadhyay et al., 2009). Although these processes seem adapted to produce FGM parts, the manufacturing of heterogeneous parts is limited to samples: parts are not functional, with simple morphology (Majumdar et al., 2009) and simple material distribution (Yakovlev et al., 2005).
To move from these samples to functional parts a global approach was proposed (Mognol et al., 2011). It is achieved by a methodology which enables to move from the concept imagined by a designer to the manufacturing of the FGM part (Fig. 1(a)). This methodology includes a description of part – geometry and material distribution – and manufacturing process (Hascoet et al., 2011). From these descriptions, an appropriate manufacturing strategy is determined with the manufacturing process modeling and all the process parameters are controlled with the automatic generation of a Numerical Code (NC) program (Muller et al., 2012).The manufacturing strategy determination has an important influence in the manufacturing procedure. Methodological tools of manufacturing strategies determination or process planning have been developed for additive manufacturing processes. With some of them, it is possible to optimize the slicing procedure (Ruan et al., 2010), to choose the part orientation (Pandey et al., 2007), to adapt paths (Kao and Prinz, 1998) or to determine a process plan (Ren et al., 2010) but they do not take into account the multi-material aspect. Methodological tools which are appropriate to the fabrication of heterogeneous parts propose a discretization of parts into areas with homogeneous material (Shin and Dutta, 2002) or do not propose path generation (Zhou, 2004).
For a manufacturing with a continuous approach of material distribution, the selection of a manufacturing strategy has a direct influence on the control of the powder distribution system. This is why a manufacturing process modeling is necessary to choose a strategy and control the commands of the system.
This paper presents a modeling of the direct laser powder deposition process which includes all the steps of the manufacturing procedure, in particular the step concerning the operation of the powder distribution system. A test-part was manufactured, analyzed and discussed in comparison with the model result. Moreover, the method of manufacturing strategy determination and the system control are described.
The direct laser powder deposition system which will be considered and used for this study is the CLAD® system. This system is based on the three dimensions layer by layer deposition of laser melted powders to build the profile of the requested part (Fig. 1(b)). Powders are injected into a high power laser beam. The energy input is partly used to melt both powders and the surface of the substrate. This system consists of a coaxial powder feed system and a fiber laser mounted on a five axis machine. The powders are supplied by two powder feeders, argon gas is used to prevent the melt pool form oxidizing throughout fabrication.
In this paper a modeling and a control of a direct laser powder deposition process for FGM parts manufacturing is exposed. The modeling takes into account all the steps of the manufacturing procedure, from the part description to the manufactured part. To model the process operation, experiments were conducted and two transfer functions are used to describe it. With this modeling it is possible to find an appropriate manufacturing strategy with the comparison between some strategies. Moreover, it is possible to control the signals used by the NC controller.
The control is made before the step of NC program generation in two stages. First, the signals are control with a virtual closed-loop controls and a PI controller. Second, the delay is compensated.
Further research will be conducted to manufacture functional FGM parts. The modeling will be used to compare manufacturing strategies to produce parts with complex material distribution. The choice of an adapted manufacturing strategy will be made by taking into account the possibility or not to correct signals.
