**8. Conclusions and future work**

In this chapter we have proposed a methodology inspired in TRIZ principles to design mechatronic systems for a new rapid 3D physical modeling technique based on formative manufacturing processes. This chapter has several contributions that will be outlined in the following. First, it presents a match between the most important engineering design frameworks: engineering design process, product lifecycle management and project

TRIZ-Based Design of Rapid 3D Modelling Techniques with Formative Manufacturing Processes 189

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management. It also adds an experienced course published previously (Cárdenas 2009), the INNOWIZ framework and the TRIZ framework. Second, focused in the first two stage of such engineering design thinking an innovation funnel was proposed where the application of rapid prototyping techniques is outlined. Traditionally, rapid prototyping techniques are used once the concept is well defined (after detailed design) but previous research has proven to be used in early stages of design (e.g. conceptual design phase). Third, formative manufacturing processes are proposed as a new paradigm to explore the design of new rapid 3D physical modeling techniques. Fourth, a new rapid 3D physical modelling technique based on a particular case of formative manufacturing processes such as wire bending and inspired in TRIZ principles was proposed. The methodology is called MDSU (MUSU in English). Fifth, a design process for mechatronic systems of rapid 3D physical modeling techniques was proposed and consists of three stages. Making the 3D object by freeform hand, and then making the 3D object following the MDSU methodology, finally proposing new machines that automate the MDSU methodology. This new paradigm promise potential benefits in favor of sustainability issues. This design methodology does not follow the traditional engineering design path but presents an extension in the problem definition stage. Because the complexity of automating handwork operations the problem (stage one in the engineering design process) must be defined by experiencing the two first stages of the proposed design process. In other words, the first two stages of the proposed design methodology must be used in the problem definition stage of the engineering design process. The third stage consists of the rest of the engineering design process from researching the problem. Now, according to our experiments, the MDSU methodology increases the use a mix of geometrical forms in both novice and advanced designers. In general, the design criteria in both types of designers are increased if the MDSU methodology is used. Another positive impact of the MDSU methodology was the execution time. Execution time was shown to improve. It is expected that machines using this methodology will perform better in terms of time. The MDSU design methodology reduces the complexity to manufacture rapid 3D physical models, specifically rapid 3D wireframing objects. We have some evidence that, MDSU-based machines will reduce the time and complexity to manufacture 3D wireframing models but also will reduce the capacity to generate ideas. On the contrary, it will promise to improve work conditions. Finally, advanced student proposals met better the MDSU design requirements that novice student proposals except for the meshing sub-process. Finally, we provide advancements of our first prototype machine which by now process only basic two-dimensional figures.

As a future work, we are planning to finish the first prototype that follows the MDSU methodology. It will surely comprise hardware and software advancements with respect to the Figures 6b and 7 shown previously. We also plan to continue the evaluation of the same parameters used to conclude in this chapter and a deeper analysis of the current results. Finally, formative manufacturing processes are a wide potential area that has been less exploited and the different types of material might open new potential possibilities. We will explore the application of our MDSU process to new rapid 3D physical modeling techniques not only based on one-dimensional materials but two- and three-dimensional.

#### **9. Acknowledgments**

Authors would like to thank the support of CONACYT, the Mechatronics department at Tecnológico de Monterrey - Campus Querétaro, and the Master in Manufacturing Systems at the same Institution. This work has been supported by the Distributed and Adaptive Systems Lab for Learning Technologies, DASL4LTD (C-QRO-17/07) and by the Innovation in Design and Manufacturing Research chair, both from Tecnológico de Monterrey - Campus Querétaro.
