University of the Basque Country University of the Basque Country

Cabecera Cofund

Advanced Manufacturing Research Fellowship Programme Adagio

Advanced ManufacturIng Research Fellowship Programme in the Basque - New Aquitaine Region (ADAGIO)

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Host Research Group

ES20_Advanced manufacturing in 4.0 factories_Luis López de Lacalle Marcaide

Luis López de Lacalle Marcaide

946014216 600062880

norberto.lzlacalle@ehu.eus

www.ehu.eus/es/web/cfaa www.ehu.eus/manufacturing https://twitter.com/CfaaEhu https://youtu.be/ljfVBdfsTNE https://www.linkedin.com/company/19089554/admin/

Group description

The Advanced Manufacturing Group of the University of the Basque Country involves five research lines: advanced processes in machining, EDM, additive manufacturing and grinding, along with all aspects regarding digitalization and artificial intelligence in smart factories. Its history started in 1988.

Currently, it involves the three highest h-factor professors in manufacturing engineering in Spain and in top-ten list in Europe; h-factor is about 63 in scholar or 53 in Scopus. On the other hand, the technology development and transfer to companies gave opportunity for the new manufacturing lab known as Centre for Advanced Manufacturing for Aeronautics CFAA, located in Zamudio, 5 kmts away from Bilbao. CFAA is in partnership with 87 companies, both from aero engines (ITP aero is the main partner), machine tools and manufacturing. CFAA is shown in video: https://youtu.be/ljfVBdfsTNE

Currently 45 researchers worked there, Professors, Ass. Prof., lecturers, post docs, grant students and people from companies. There are people from different countries.

In 2021 a new unit devoted to Artificial Intelligence in Manufacturing for Sustainability (AIMS) is starting, giving new opportunities for post-doc visitors. The Unit includes a collaboration frame with the research center Ideko-Danobat, with the training center IMH and the Basque center for applied mathematics BCAM. Excellency but practical view is the purpose of the group and CFAA center and AIMS. The group can host post-doc researchers pretending to be in short stays at our partners.

Facilities involves: 5 big multitasking machines, 2 SLM printers, two grinding stations, 4 EDM machines, digital XR and metrology room, all kind of monitoring devices, 3 robotic stations for welding, deburring and additive by LMD, a broaching bench, and good means for digital purposes, edge computing, 5G, and data lake. Regarding gender, 60/40 is our male/female ratio, our only demand is a good attitude to wok with other colleagues.

Every year, more than 40 JCR papers are published, and more that 1.5 million euros are obtained from companies. Therefore, both faculty and CFAA are good working places for post-docs with real interest in making excellent technology in multidisciplinary teams, all thinking in getting the best skills valuated by industry. Our docs are hired by companies always.

All post-doc will be integrated in teams with doctoral and MSc students, and Ass. Professors. A team always achieve better results than isolated geniuses, that is our real belief. Short stays at Partner companies would be a real possibility.

Our group and CFAA is in a consolidation and reasonable growth phase, so new recruitment can help us and look for a fruitful career.

Keywords

  • Manufacturing
  • Machine tool
  • Aeroengines
  • Superalloys
  • Grinding
  • Machining
  • Non-conventional processes
  • Additive manufacturing
  • Digitalization
  • Artificial intelligence

Team Description

  • Luis Norberto López de Lacalle (Principal Investigator)

    ORCID: 0000-0002-1573-2787

  • Iñigo Pombo (Co-Principal Investigator)

    ORCID: 0000-0001-8222-3459

  • Aitzol Lamikiz (Co-Principal Investigator)

    ORCID: 0000-0002-8477-0699

  • Naiara Ortega (Research staff)

    ORCID: 0000-0001-8283-847X

  • Eneko Ukar (Research staff)

    ORCID: 0000-0001-9754-6154

  • Soraya Plaza (Research staff)

    ORCID: 0000-0003-1338-7577

  • Maria Helena Fernandes (Research staff)

    ORCID: 0000-0001-9391-9574

  • Leire Godino (Post-Doctoral Researcher)

    ORCID: 0000-0002-0137-2995

  • Iñigo Pombo (Research staff)

    ORCID: 0000-0001-8222-3459

  • Borja Izquierdo (Research staff)

    ORCID: 0000-0003-2943-7284

  • Unai Alonso (Research staff)

    ORCID: 0000-0002-5385-438X

  • Haizea González (Post-Doctoral Researcher)

    ORCID: 0000-0001-7607-6149

  • Ainhoa Celaya (Research staff)

    ORCID: 0000-0002-5070-9590

  • Gorka Urbikain (Research staff)

    ORCID: 0000-0002-7159-8199

  • Jon Iñaki Arrizubieta (Research staff)

    ORCID: 0000-0002-6030-4941

  • Amaia Calleja Ochoa (Research staff)

    ORCID: 0000-0002-4978-3443

  • Aitor Beranoagirre (Research staff)

    ORCID: 0000-0001-5730-0774

  • Jokin Muñoa (Post-Doctoral Researcher (scientific collaborator))

    ORCID: 0000-0002-8847-511X

  • Sarvesh Mishra (Post-Doctoral Researcher)

  • Pablo Fernández de Lucio (PREDOC)

    ORCID: 0000-0002-5617-6019

  • Ander del Olmo (PREDOC)

    ORCID: 0000-0002-1360-6242

  • Aner Jimeno (PREDOC)

    ORCID: 0000-0002-2117-1349

  • Gaizka Gómez Escudero (PREDOC)

    ORCID: 0000-0003-0446-0680

  • Francisco Javier Amigo (PREDOC)

    ORCID: 0000-0001-7425-5733

  • Mikel González Esteban (PREDOC)

    ORCID: 0000-0003-2257-442X

  • Felipe Marin (PREDOC)

    ORCID: 0000-0003-2628-8180

  • Jose David Perez (PREDOC)

    ORCID: 0000-0002-5189-1857

  • Marta Ostolaza (PREDOC)

    ORCID: 0000-0002-3637-3971

  • Jose Exequiel Ruiz (PREDOC)

  • Jose María Hernandez Vazquez (Research staff)

    ORCID: 0000-0002-9911-2074

  • Joan Ander Ealo (Research staff)

    ORCID: 0000-0002-6112-9575

  • Leonardo Sastoque Pinilla (PREDOC)

    ORCID: 0000-0002-7290-854X

  • Izaro Ayesta (Research staff)

    ORCID: 0000-0002-0873-9040

  • Adrian Rodriguez (Research staff)

    ORCID: 0000-0003-3661-2693

  • Asier Fernández (Research staff)

    ORCID: 0000-0002-9963-6994

  • Octavio Pereira (Research staff)

    ORCID: 0000-0003-3151-5763

  • Silvia Martínez (Research staff)

    ORCID: 0000-0002-4645-3131

  • Saioa Etxebarria Berrizbeitia (Research staff)

    ORCID: 0000-0002-0864-4092

Projects

  • Development and dissemination of Metal Additive Manufacturing technologies in the tooling sector for a smart and sustainable growth of the SUDOE - ADDITOOL space

    Pl: A. Lamikiz

    Funding Agency*: European

    Ongoing: yes

    Project reference: SOE4/P1/F1006

  • Impresion 3D Transfronteriza (Transfron3D)

    Pl: A. Lamikiz

    Funding Agency*: European

    Ongoing: no

    Project reference: EFA 90/15

  • Digital Solutions for advanced grinding Processes

    Pl: Iñigo Pombo

    Funding Agency*: National

    Ongoing: yes

    Project reference: PID2020-114686RB-I00

  • Analysis, design, and manufacturing using microstructures (ADAM^2)

    Pl: L.N. López de Lacalle

    Funding Agency*: European

    Ongoing: yes

    Project reference: H2020 FETOPEN19/04

  • INSPECTA- Un enfoque de las inspecciones de uniones críticas y defectos por métodos robustos y automatizables.

    Pl: Naiara Ortega Rodríguez

    Funding Agency*: Regional

    Ongoing: yes

    Project reference: ELKARTEK20/63

  • COPTER- Metrología aplicable a geometrías de alta complejidad para transmisiones de ultraprecisión

    Pl: Amaia Calleja Ochoa

    Funding Agency*: Regional

    Ongoing: yes

    Project reference: ELKARTEK19/46

  • All last five years projects are at

    Project reference: https://www.ehu.eus/en/web/cfaa/berriak/-/asset_publisher/S8Wy/content/2021_01_25_cfaa_annual_report_2020

  • Interlinked Process, Product and Data Quality framework for Zero-Defects Manufacturing

    Pl: L. Norberto López de Lacalle

    Funding Agency*: European

    Ongoing: yes

    Project reference: H2020-Industrial Leader-NMPB20/01

  • HUC Powder HIP for Ultrafan demo casing

    Pl: L. Norberto López de Lacalle

    Funding Agency*: European Clean Sky 2

    Ongoing: yes

    Project reference: H2020-JTI-CleanSky18/01

  • UN ENFOQUE GLOBAL PARA LA MEJORA DE PROCESOS EN CARCASAS DE TURBINAS DE NUEVOS MOTORES NEO (ITENEO)

    Pl: L. Norberto López de Lacalle

    Funding Agency*: National

    Ongoing: yes

    Project reference: MINECOR19/P72

  • Smart Factories of the Future (5G-Factories)

    Pl: Eduardo Jacob

    Funding Agency*: Regional

    Ongoing: yes

    Project reference: COLAB19/06

  • Technologies for geared turbofan

    Pl: L. Norberto López de Lacalle

    Funding Agency*: L. Norberto López de Lacalle

    Ongoing: yes

    Project reference: IPT19/04

* INT - International EU - European NAT - National RE - Regional

Publications

Research Lines

ADVANCED MATERIALS AND PROCESSES

Advanced machining of new superalloys for next generation aeroengines

  • CFAA is the leading a center of the University of the Basque Country for new manufacturing technologies in aeroengines, and machining is half of the techniques involved. Inconel 718, Astroloy, Hasteloy and Ti6Al4V are common challenges every day.
  • Our research covers:
    • Machining optimization
    • Modelling: both FEM and mechanistic approaches
    • Residual stresses and surface integrity
    • Multiaxis and five-axis machining
    • Alternative cooling techniques, such as CryoMQL and high pressure
    • New tools and double contact processes
  • The line offers a balance of high impart and excellence paper production and real application to one of the high-end applications in industry, aeroengines. We work for next generation geared turbofan engines.
  • CFAA works for new engine concepts, such as UltrafanTM, hybrid concepts and in full collaboration with CFAA companies. Machines are real ones, some 70 tons in weight. CFAA is in partnership with 87 international companies.

Non conventional processes for next generation hybrid engines

  • EDM is key in the group, both wire and sinking ones. Narrow and deep holes and slots, and new applications of control and AI (Artificial Intelligence) to achieve the highest precision. ONA electro erosion is our main partner, and ITP Aero and others.
  • AI can give new ways of optimizing processes: adjusting parameters to instabilities of the process or part geometry, predictive maintenance, generating digital twins or others.
  • On the other hand, the group is open to other non-conventional processes, if proposing post-doc can open lines of application on aero turbines. We would like to see more opportunities in other non-conventional processes, such as fast-hole EDM (in 2022) or even ECM. Our experts are leading ones in both EDM process and new application to very narrow features.
  • AI is making progress in this line, because all non-conventional process parameters show a great influence on final piece quality. Our interest is open new lines in AI and control to use the data acquired to obtain intelligent processes of manufacturing. People of data and control are welcome.

INTELLIGENT, FLEXIBLE & EFFICIENT PRODUCTION SYSTEMS

Machine tool production lines managed by digital and intelligent approaches

  • Machine tools and other good equipment are including powerful CNC and edge computing devices. New digital-twin concepts are developed base on the Siemens Sinumerik ONE platform, and on the fingerprint concept.
  • Thermal and mechanical deformations are always a problem in high-precision workshops. Currently we work with new sensors both for structural deformations and for process monitoring. 5g can help us in this line.
  • The line is about how to develop machine models improved by massive data gathering. Machine could be connected to 5G network providing new services to both end-users and machine tool manufacturers.
  • This line is a good opportunity for people from control and data fields, with interest in developing both excellent paper and utilities for next generation of machine tools in 5G plants.
  • At CFAA we have machines from Danobat, Hermle, Ibarmia, GMTK and others that will be open for testing new ideas. If you are a post-doc from the world of machines and knows about machine performance, this can be a good line for making further research. Added value applications are at hand, machine tool sector is key in the Basque Country.

DIGITAL AND CONNECTED FACTORY

Towards a Data-Driven Metal Additive Manufacturing Process for aerospace components

  • Metal Additive Manufacturing processes are gaining prominence in the production of highly complex and tailor-made parts. This trend is particularly important in the aerospace sector, where most aero-engine part designs involve complex features and extremely high requirements of lightweight and thermo-mechanical behavior.
  • Metal Additive Manufacturing processes, such as Laser Powder Bed Fusion (LPBF), are capable of producing highly complex parts directly from the CAD file, opening up new design-paradigms like lattice structures or designs based on topological optimization. However, the robustness of the process and the need for quality assurance is still a barrier. Although leading system OEMs are integrating complex monitoring methods, there is a lack of knowledge about the correlation between this data and the integrity of the parts.
  • The research line should be considered within this context, where an in-depth study of the capture, processing and analysis of this process data is proposed. The main objective is to obtain a correlation between the LPBF data obtained from different sensors and the integrity of the parts. Thus, the research involves data analytics for the processing of large volume of process data, obtained from a last generation LPBF system.
  • Research beyond the state of the art: To obtain an algorithm capable of detecting the LPBF defects by data-analytics.
  • There are two SLM machines at CFAA, Renishaw A400 and Renam 500

Digital Twin of the LPBF additive manufacturing process for virtual process testing and certification

  • The research line is focused on the full development of a digital twin of the laser powder bed fusion process (LPBF). LPBF is a metal additive manufacturing process capable of producing highly complex and fully dense parts. Its main applications are the manufacturing of medical implants and small but very complex turbine components. Due to the high-quality requirements of the parts, the testing, validation and certification of the LPBF process become a long and tedious job, with the need to adjust the process parameters and make refinements based on trial-and-error results.
  • The main objective of this research line is to develop a full Digital Twin where the process can be tested and validated virtually, without the need of experimental tests. This achievement would reduce the process set-up time, save production costs and environmental impact and increase the knowledge of the process.
  • The main challenges to be addressed in this line are the analysis and consideration of the main variables of the process, taking into account that the building chamber of the LPBF system is a multiphysical domain, where phenomena of different nature take place.
  • Research beyond the state of the art: To implement a full digital-twin of the LPBF involving different nature phenomena.

New approaches based on AI for smart factories management

  • CFAA is not only a lab for manufacturing process optimization and machine tool improvement. As a whole is pilot factory with all machines connected to network and some of them in new 5G. Therefore, the smart factory control and machining monitoring using intelligent approaches are of our interests.
  • Currently we work in data lake structure and advance use of data for early detection of machine failure, tools wear and prevent from very expensive part waste of time. Each component in aeroengines is about hundreds of euros, so intensive monitoring is key for us.
  • The collaboration with Ideko, IMH and BCAM would be a daily life aspect in this research line.
  • Those PhD with skills in AI and machine learning and with real interest in putting to work the new ideas, would be welcome here, application are in areas of machining, machine tools, robotic welding and others.

Digital Solutions for Advanced Grinding Processes (GrinDTWin)

  • Smart factories rely on the Internet of the Things to drive a deep change to next generation of manufacturing systems. During the next years manufacturing processes are going to be more digital and less mechanical. Grinding is a critical technology in the manufacturing of high-tech precision parts. It accounts for around the 20 -25 % of all machining cost in industrialized world. Continuous industrial challenges are placed on grinding from the leading industrial sectors, including aerospace, railways, energy, biomedical, etc. Joint actions towards digital transformation are required from all agents of the value chain. The GrinDTWin proposal looks at digitalization as the fundamental tool for the optimization of high added-value grinding processes. The concept of Digital Twin of the Grinding Wheel involves the integration of advanced numerical models (because of the composite nature of the wheel, DEM seems to be the optimum method), the development of specific-purpose mechanical tests, and the acquisition (advanced sensors and monitoring) of data as close as possible to the wheel-workpiece contact. The objectives of zero-defect manufacturing, the reduction of set-up times related to the use of virtual prototypes, and the development of customized abrasive materials for disrupting state-of-the-art applications will be accomplished throughout the project.
  • There is a line of collaboration with Ideko and Danobat Group.

ENERGY EFFICIENCY

<ul> <li>Smart factories rely on the Internet of the Things to drive a deep change to next generation of manufacturing systems. During the next years manufacturing processes are going to be more digital and less mechanical. Grinding is a critical technology in the manufacturing of high-tech precision parts. It accounts for around the 20 -25 % of all machining cost in industrialized world. Continuous industrial challenges are placed on grinding from the leading industrial sectors, including aerospace, railways, energy, biomedical, etc. Joint actions towards digital transformation are required from all agents of the value chain. The GrinDTWin proposal looks at digitalization as the fundamental tool for the optimization of high added-value grinding processes. The concept of Digital Twin of the Grinding Wheel involves the integration of advanced numerical models (because of the composite nature of the wheel, DEM seems to be the optimum method), the development of specific-purpose mechanical tests, and the acquisition (advanced sensors and monitoring) of data as close as possible to the wheel-workpiece contact. The objectives of zero-defect manufacturing, the reduction of set-up times related to the use of virtual prototypes, and the development of customized abrasive materials for disrupting state-of-the-art applications will be accomplished throughout the project.</li> <li>There is a line of collaboration with Ideko and Danobat Group.</li> </ul>

  • The reduction of energy consumption and any wastes in manufacturing are a paramount concern for us.  The new concepts of efficiency in machining integrating at CAM stages utilities for selecting toolpaths or process parameter with minimum energy can give both new models and applicative results.
  • The main goal is to achieve in 2035 a zero impact (neutrality) in manufacturing workshops. So, the line is open to people of electrical monitoring, programming of CAM utilities, and even to coolants reduction and evaluation of harmful aspects.
  • Machine tools can be optimized in these lines, so please feel free to propose new ideas, thinking out of the box as it usually said. We have the means (machines, a full pilot factory), so you can propose the new ideas. Results can be great!

SUSTAINABLE MANUFACTURING

Reducing the environmental impact of aero-engine industry by the remanufacturing of high added value parts

  • A large number of turbine parts are manufactured by a combination of high-performance machining, non-conventional processes, forging and investment casting. These manufacturing processes, besides being both expensive and difficult to implement, represent a high environmental impact. Moreover, if the part is damaged in a late step of the manufacturing process, all the dedicated resources and effort become scrap.
  • One of the main repair methods for turbine parts is the Laser Direct Energy Deposition (LDED) process. LDED is an additive manufacturing process capable of adding material into a damaged area. This process is certificated by most of the leading turbine OEMs and can be applied on tip blades, cases or turbine vanes. However, there is a limitation on materials and defects where the process can be applied. Moreover, the application of the procedure is based on visual inspections and manual procedures.
  • The research line is focused on two scientific pillars: First, the use of artificial intelligence for the detection, inspection and analysis of the possible defects, including the evaluation of the remanufacturing procedure. Second, the application of LDED process to repair the detected defects using a highly monitored system and assuring the quality of the result.
  • Research beyond the state of the art: To deploy a procedure for the repair of different turbine components, including the digital inspection and process full monitoring.

Nondestructive testing and quality control of new high-added value parts

  • The main driver of many applications, aircrafts, nuclear, precision components, scientific equipment is safety and quality. The metrology, defects detection and non-destructive testing methods are key in modern manufacturing. Zero-defects is a real challenge in modern industry.
  • CFAA involves a full metrology room with two CMMs machines, Revo 2 scanning system, structured blue light, Alicona and XR digital system with 3D tomography. To develop technologies, software and the management of massive information.
  • The new post-docs would be opening research lines in the use of tomography in micro and macro defects, along with metrology.
  • People with real knowledge in materials structure, residual stresses and use of advanced microscopy can help us and follow with his/her successful career. PhDs in fields of manufacturing, materials science and software can see interesting this line.
  • We have the high-end application, engines for new aircraft concepts. Ph.d can help with skills in NDTs, data analysis and metrology.

Cross-border Collaboration (if any)

In the field of Additive Manufacturing, there is a stable cooperation with the ESTIA of Bayonne. Since 2015, several actions have been deployed in the context of 2 transborder projects: Transfron 3D - already finished - and Additool - currently ongoing. Main indicators of this activity are one thesis with a European mention and the development of a transborder course for students from both universities.

There are good relations with some groups at Bordeaux, and with people of laboratory Trans Math in applied mathematics by means of our colleagues of dept of mathematics (Luis Vega). There are good relations with Ivan Iordanoff from ENSAM.