H2 Manufacturing: Hybrid-Hybrid machining of next generation aerospace materials
Lead Research Organisation:
University of Sheffield
Department Name: Advanced Manufacturing Res Centre Boeing
Abstract
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Organisations
Publications
Li X
(2022)
High temperature and strain-rate response of AA2124-SiC metal matrix composites
in Materials Science and Engineering: A
Kim J
(2019)
Hybrid machining of metal-matrix composite
in Procedia CIRP
Kim J
(2023)
Hybrid-hybrid turning of micro-SiCp/AA2124 composites: A comparative study of laser-and-ultrasonic vibration-assisted machining
in Journal of Manufacturing Processes
Dominguez-Caballero J
(2023)
Hybrid simultaneous laser- and ultrasonic-assisted machining of Ti-6Al-4V alloy
in The International Journal of Advanced Manufacturing Technology
| Description | To date, we established that the combined Laser and Ultrasonic Assisted Machining (LUAM) can reduce the cutting forces and surface roughness (Ra) compared to the conventional machining (CT) for Ti64 materials. The hybrid LUAM process demonstrates process improvement with wider range of cutting speeds and depths of cut, which is achieved due to the combined force reduction and thermal softening effect by the hybrid process. We have established that: Hybrid machining using ultrasonic vibrations has improved the machinability of metal-matrix composites significantly. We observed that there is a case for using cheaper cemented carbide tools instead of the expensive PCD tools, which are industry standard for machining metal-matrix composites. Similar improvement in terms of machinability has been found when using ultrasonic vibrations for Ti64 alloy material. The hybrid LUAM process demonstrated an improved machinability of Ti64 alloy material by further reducing the cutting forces at low speed, and even enhancing the surface roughness Ra for most of the tested cutting speeds and depths of cut, which was achieved due to the combined force reduction and thermal softening effect by the hybrid process. |
| Exploitation Route | Our findings have be shared with tool manufactures to consider designing improved tool in cemented carbides. Also, the finding of machinability improvement has also been shared with end-user manufacturers to consider the use of H2 in machining process. Noted that this still needs to be demonstrated in complex machining scenarios. |
| Sectors | Aerospace Defence and Marine Digital/Communication/Information Technologies (including Software) Education Manufacturing including Industrial Biotechology |
| URL | https://doi.org/10.1007/s00170-022-10764-5 |
| Description | To date, we established that the combined Laser and Ultrasonic Assisted Machining (LUAM) can be beneficial to improve the machinability of hard materials such as Ti64. Noted that for the full implementation of the LUAM in the industry, the Industrial impact is imminent with Sandvik and BAE participation for the full testing of our H2 technology, and this should be investigated for higher TRL research. In a meeting with the industrial board, they showed interest to follow up this investigation. We have established that cemented carbide tools instead of the expensive PCD tools have improve the machining of metal-matrix composites. Recently, we have establish that the machinability of Ti64 alloy material improved with the use of laser and assisted ultrasonic machining H2, and the use of carbide tools. Noted that the full implementation in complex machining processes, the Industrial impact is imminent with Sandvik and BAE participation for the full testing of our H2 technology, and this should be investigated for higher TRL research. |
| First Year Of Impact | 2023 |
| Sector | Aerospace, Defence and Marine,Digital/Communication/Information Technologies (including Software),Environment,Manufacturing, including Industrial Biotechology |
| Impact Types | Economic |
| Description | AMRC Members Sponsorship / EPSRC CDT (Simulation of Machining Induced Surface Damage in Metal Cutting) |
| Amount | £134,000 (GBP) |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 08/2018 |
| End | 09/2022 |
| Title | Established capability for high strain rate testing using a Split Hopkinson Pressure Bar (SHPB) system |
| Description | The Spilt Hopkinson Pressure Bar system has now been configured to test high strain rate of advanced alloys and composites. An experimental procedure has been produced and validated on Inconel 718 material as part of this project. |
| Type Of Material | Improvements to research infrastructure |
| Year Produced | 2018 |
| Provided To Others? | No |
| Impact | Customers of the group can now access this equipment. Further publications are in the pipeline using data collected from the system |
| Title | Laser and ultrasonic assistive machining research infrastructure |
| Description | The acquisition and technology development allowed AMRC to increase its research capability in the better understanding of assistive process optimisation techniques for machining. |
| Type Of Material | Improvements to research infrastructure |
| Year Produced | 2022 |
| Provided To Others? | Yes |
| Impact | The assistive machining research allowed to establish work looking to impact higher TRL research of our industrial partners. Different simulation methods that were generated will be implemented in different research areas specially related with process optimisation. The simulation methods are conforming the basics of our internal AMRC investigation and implementation for digital machining, which is a key area of work at the AMRC and interest of the AMRC industrial partners. |
| Title | Analytical model developments for cutting force and temperature predictions |
| Description | The model development gave an opportunity to develop analytical models linked to machine learning techniques, which were also investigated in this research to analyse the assistive machining process. |
| Type Of Material | Computer model/algorithm |
| Year Produced | 2022 |
| Provided To Others? | Yes |
| Impact | These modelling techniques are currently conforming the basics of future digital machining development. This has been impacting other internal development on process health condition for remaining useful tool life. This will also impact follow up research in the area of digital twin, and linkage of tool life and surface integrity investigation. |
| Title | Cutting trails of conventional turning and ultrasonic-assisted turning on Aluminium metal matrix composite |
| Description | Cutting trials were carried out to collect data for modelling the effect of ultrasonic-assisted turning on cutting forces and cutting temperature for Aluminium metal matrix composites with Sillicon Carbide particles. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2019 |
| Provided To Others? | No |
| Impact | The data collected during these trials has been shared within the research partners to carry out various modelling activities, and to test and benchmark the ultrasonic tool, which was developed during this research. |
| Title | Cutting trails of conventional turning and ultrasonic-assisted turning on a Titanium alloy |
| Description | Cutting trials were carried out to collect data for modelling the effect of ultrasonic-assisted turning on cutting forces and cutting temperature for Titanium alloy Ti-6Al-4V. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2020 |
| Provided To Others? | No |
| Impact | The data collected during these trials has been shared within the research partners to carry out various modelling activities, and to test and benchmark the ultrasonic tool, which was developed during this research. |
| Title | Flow stress data for MMC materials |
| Description | Databases and collections of samples/specimens that have been created as part of the high strain rate and high temperature testing of MMC materials. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2019 |
| Provided To Others? | No |
| Impact | The data analysis and flow stress data has been used for an input numerical models for the understanding of the machinability of the MMC materials. |
| Title | Further cutting trails of conventional turning and ultrasonic-assisted turning on a Titanium alloy |
| Description | Further cutting tests were carried out on Titanium alloy to continue the objectives of the grant work. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2020 |
| Provided To Others? | No |
| Impact | These latest trials are key for the data analysis and development of models relevant for this grant work. |
| Title | Further testing of the optimal artificial neural network evaluator for the prediction of machining induced residual stresses |
| Description | The algorithm was further tested to investigate the robustness of the NN evaluator alongside an empirical model; this was to predict the residual stresses and to account the shape of the stress profile rather than simulating single values as typically reported in literature. |
| Type Of Material | Computer model/algorithm |
| Year Produced | 2020 |
| Provided To Others? | Yes |
| Impact | This is now used at the AMRC for projects where residual stress modelling is required. |
| Title | Optimal artificial neural network evaluator and selector for cutting force modelling |
| Description | An algorithm was created to model cutting force data using an artificial neural network. This algorithm carries out an evaluation of different network architectures and hyperparameters to select the optimal network with the best performance, accuracy and low complexity (less prone to overfitting). This model was created in preparation for the data acquired from cutting trials on Aluminium metal matrix composites using ultrasonic-assisted machining and laser-assisted machining, where the cutting forces represent an important parameter to gauge the efficiency of both assisted machining operations. |
| Type Of Material | Computer model/algorithm |
| Year Produced | 2019 |
| Provided To Others? | No |
| Impact | This algorithm has been adapted and used for other research activities at the AMRC that investigate the effect of machining parameters in deflection. By using this algorithm, it has been possible to predict process parameters instead of carrying out further testing, which can be expensive and time-consuming. |
| Title | Testing on Aluminium MMC for publication with Loughborough University |
| Description | Specific testing with an Aluminium metal matrix composite was carried out to produce data for a publication being developed in conjunction with Loughborough University. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2020 |
| Provided To Others? | No |
| Impact | The results for these tests will be a key dataset for an upcoming publication in collaboration between the two organisations. |
| Title | Artificial neural network simulation and optimisation |
| Description | A program was developed for the selection and training of an artificial neural network, which tests several network architectures and hyperparameters to select the optimal network for a given dataset. The software carries out an analysis of the importance and influence of the predictor parameters based on the artificial neural network, as well as an optimisation of the key parameters using genetic algorithm, swarm particle optimisation, and pattern search, also coupled with the artificial neural network. |
| Type Of Technology | Software |
| Year Produced | 2020 |
| Impact | The software has a great impact on this research, as it provides a good way of generating relevant data without carrying out further testing, which can be expensive and time-consuming. Also, the algorithm created for network selection is a novel approach to the creation and training of artificial neural networks, which will be published in a conference publication in the 9th CIRP Conference on High-Performance Cutting entitled 'Cutting Force Prediction using Machine Learning for a Pocketing Toolpath on Aerospace Aluminium Alloys'. |
| Title | Methodology for High Strain Rate (HSR) and High Temperature testing in materials |
| Description | A methodology for the selection input parameters of testing at High Strain Rate and High Temperature for determining the flow stress data in MMC materials . |
| Type Of Technology | Systems, Materials & Instrumental Engineering |
| Year Produced | 2019 |
| Impact | The methodology has helped in characterising other materials with the correct selection of the testing at HSR and high temperature. |
| Description | AMRC Machining Group Internal Conference |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Other audiences |
| Results and Impact | The Machining Group Internal Conference is a bi-annual event organised internally here at the Advanced Manufacturing Research Centre, where research and applications teams showcase their current research work to other teams, postgraduate students and senior management staff. Each presentation has a duration of 10 to 15 minutes, with around 5 minutes of questions from the audience. This activity is a great opportunity to get expert advice and comments on research work as most attendees work in the are of machining. |
| Year(s) Of Engagement Activity | 2019 |
| Description | AMRC internal Tech Fellow conference updating industrial partners of the progress of the project |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Industry/Business |
| Results and Impact | AMRC industrial partners attended the event, which generated interest in the research asking questions of the developed simulations. This could lead further work with the AMRC industrial partners. |
| Year(s) Of Engagement Activity | 2020 |
| Description | AMRC internal project research direction |
| Form Of Engagement Activity | A formal working group, expert panel or dialogue |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Other audiences |
| Results and Impact | The outcomes of the research was of great interest among different research groups at the AMRC. This generated a new area of research to follow up the implementation of the current development and capability of the H2 to different processes and applications. |
| Year(s) Of Engagement Activity | 2022 |
| Description | Support for the STEM activities/event at the AMRC. |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Schools |
| Results and Impact | Around 50 school students attended a visit to our organisation through our STEM activities/event at the AMRC, which generated some interest of the school students in our Centres and activities that included our research.This activity is a great opportunity to engage with students to encourage them to study engineering to be the future engineers or researchers. |
| Year(s) Of Engagement Activity | 2019 |