1. ADDITIVE MANUFACTURING PROJECT CLUSTER MEETING Computational Methods and Optimization techniques for the improvement of properties of material and process parameter in metal additive manufacturing Fundació CIM C/Llorens i Artigas, 12 Parc Tecnològic de Barcelona Barcelona, Spain 2 May 2016 Flor Garcia Research Professor in Advanced Manufacturing Systems Center for Research and Innovation in Aeronautical Engineering CIIIA-UANL-FIME

2. > > The optimization of manufacturing processes and production time efficiency is dependent on the initial quality of the materials, particularly if the required design properties are influenced or, in some cases, determined by the processes employed by the component manufacturer. Computational Methods and Optimization techniques can be helpful tools to describe behavior of a material, such as mechanical and physical properties. The selection of optimum process parameters its very important, as the proper selection of parameters plays a significant role to ensure quality of product, to reduce the manufacturing cost and to increase productivity, and for it is necessary the optimization of manufacturing process. The aim of this project is to propose the computational methods and Optimization techniques required by the Additive Manufacturing for metals process so as to optimize their production processes and the efficiency of their products in service.

3. Exploitable results (ERs) > ER 1 Analysis of elements of AM process A Product B Process components, process specifications and process design. ER2 Computational models and Optimization techniques. A Helpful tools to describe behavior of a material and process. B Designing system for the process. ER3 Implementation & Monitoring A Identification of characteristic changes of a process. B Process quality determines the product quality, given that the entire manufacturing programme and product/process design is capable of meeting the requirements

4. > > > A Product B Process > A Aerospace and aviation industries B Medical sector. C Automotive manufacturing industries > A Cost savings B Quality of product C Methodologies for the application of strategies for transfer results to industry

5. > > Technological Readiness Level > A TL4 Milestones in the TRL progression up to TRL9 A TL4 B TL4 Main technical challenges in this result A Develop categorization matrix from of elements of the process. B Identify relationship between input-output and in process parameters. Time to market (Mth/yr): 24 Mth IPRs - Have you protected or will you protect this result before disclosing it? How? When?

6. > > IPRs Have you protected or will you protect this result before disclosing it? A Yes How? A It under Mexican laws give protection through IMPI in Mexico and abroad. When? A Given advances in the results

7. > > > A Develop computational models to predict the mechanical properties and physical of components. B Develop the modelling techniques of input-output and in-process parameter relationships are mainly based on statistical regression and finite element model. > A Aerospace and aviation industries B Medical sector. C Automotive manufacturing industries > A Quality in the product B Optimization of process additive manufacturing through its process parameters C Have a global model for the optimization of process additive manufacturing through its main parameters.

8. > > Technological Readiness Level > A TL4 Milestones in the TRL progression up to TRL9 A TL4 B TL4 Main technical challenges in this result A Setting up mathematical equations to describe the model, referring to the standard forms of input-output and state-variable descriptions of systems BDetermine the characteristics of the model from the data measured as the system’s output Time to market (Mth/yr): IPRs - Have you protected or will you protect this result before disclosing it? How? When?

9. > > IPRs Have you protected or will you protect this result before disclosing it? A Yes How? A It under Mexican laws give protection through IMPI in Mexico and abroad. When? A Given advances in the results

10. > > > A Product B Process > A Aerospace and aviation industries B Medical sector. C Automotive manufacturing industries > A Identify the productivity, capacity scalability, and part quality and thus, influence the lifecycle cost of the manufacturing system. B found the cause effect relations across process borders which have a significant influence on the behavior of a product during manufacturing. C Have a global model for the optimization of process additive manufacturing through its main parameters.

11. > > Technological Readiness Level > A TL4 Milestones in the TRL progression up to TRL9 A TL4 B TL4 Main technical challenges in this result A The flexible integration of the whole company to an optimal cooperation between human and intelligent technical means. B Systematization of all elements of the production and its set-up. Time to market (Mth/yr): 24 Mth IPRs - Have you protected or will you protect this result before disclosing it? How? When?

12. > > IPRs Have you protected or will you protect this result before disclosing it? A Yes How? A It under Mexican laws give protection through IMPI in Mexico and abroad. When? A Given advances in the results

13. Expressions of Interest > We want to participate in the develop Knowledge/educational products and Training curricula. Participate in Analysis of rapid manufacturing Techniques and Analysis and modeling of AM parts. Collaborate in the develop the optimization of processes for Ti printed parts. Develop by methods optimization for the fabrication of metallic components defect-free.