Multi-sensor in-process metrology of laser powder bed fusion additive manufacturing: Fusing form, texture and temperature measurement.

Lead Research Organisation: University of Nottingham
Department Name: Faculty of Engineering


This proposal is to develop a multi-sensor system for in-process metrology of parts made by the additive manufacturing (AM) process - laser powder bed fusion (L-PBF).
AM, also known as '3D printing', is changing the way that engineers solve the problems of today. Unlike subtractive manufacturing methods, where materials must be cut away to produce a finished part, AM processes build parts up layer-by-layer. This provides almost limitless design freedom, allowing the design of more organic, more lightweight, more bespoke solutions. However, the technology is not without its challenges. The current state of AM technology cannot produce parts with the consistency or geometric tolerances that are required for many applications. The production of metal parts by AM is particularly challenging. The most prominent technology for producing AM metal parts is L-PBF, also called selective laser melting. To produce parts economically the process must be fast with high laser power making L-PBF a highly energetic process that is sensitive to a changes in process variables. Defects can occur at any stage of the process: incomplete melting, aggregation of unmelted powder, pitting, balling, spattering, as well as defects caused by thermal or residual stresses: cracking, spalling and layer separation. Effective control of the L-PBF process is an extremely challenging task, and the subject of significant research both in the UK and global research communities. One aspect of that challenge that has become clear in the last few years is the need for step change improvements in in-process condition monitoring and metrology.
The key parameters for in-process control are the melt pool temperature, the powder bed temperature and the presence of physical defects in the powder laying and laser fusion stages. The laser fusion event that consolidates the powder takes place over a few hundreds of nanoseconds, making it very difficult to observe and control in real-time. Fortunately, a great deal of information about the melting conditions can be observed in the consolidated surface that fusion leaves behind; a so-called process signature or fingerprint. By capturing information on the form and the texture of the part surface it is possible to determine whether the laser and scan parameters have been chosen correctly, and critically it is also possible to monitor whether any major defects have occurred. AM processes, including L-PBF, are not yet mature enough that quality can be assured. Each machine will have slightly different performance characteristics, and the part quality can change from day to day, with small changes in the environment, the powder quality or the laser condition. For AM to be more widely adopted, industries need assurance, and that means highly robust in-process measurements.
Current in-process measurement methods are inadequate; 2D imaging methods cannot identify all of the common defects or measure surface texture in the process fingerprint. The few pre commercial 3D measurement systems that have been demonstrated, have been unable to accommodate the extreme range in texture observed for L-PBF. In simple terms the surfaces are either too reflective for some methods, or too diffuse for others, often producing misleading imaging artefacts or missing significant defects. This lack of robust in-process metrology, stymies development and slows the wider adoption of L-PBF. What is required is a robust measurement of form, texture and thermal distribution of the metal powder bed. This proposal will achieve that aim by the intelligent combination of measurement data captured by multiple sensor systems. Each sensor individually cannot capture the whole surface, but when combined, will offer the most complete in process measurement achievable to date. This multi-sensor system will have profound benefits for process control of L PBF processes as well as providing a wealth of in process data to feed into future research.

Planned Impact

The work in this proposal will have impact across the four domains identified by EPSRC: knowledge, commercial, personal and societal. As fundamental research, the immediate impact will be focused in the domains of knowledge and commerce. The field of AM is one of the largest and fastest growing fields in UK academia, up from £15m of research funding in 2012 to almost £30 million in 2014, across 244 research projects. The 2012 SIG report identified 81 organisations involved in research projects; tripled to 243 organisations by 2015. Similar growth has been seen in Europe, the US, China and Japan. The UK should work hard to maintain its position as a leader in AM technologies. As identified in the Academic Beneficiaries section, the outputs of this project will provide a step-change in AM process monitoring and a wealth of new knowledge that can catalyse new research. These outputs have impact beyond academic endeavour, with potential for great strides into new markets for companies that are able to leverage the new methods and insights that come from this work. The project partners will receive the greatest commercial impact from this work. Renishaw are keenly aware of the need to bring metrology in AM up to speed with other technological developments and are actively developing their own expertise in in-process measurement. This work will be greatly supported by Renishaw's experience, as likewise this work will provide Renishaw with a detailed understanding of a wholly novel multi-sensor measurement approach. Valuable IP generated by the project should be effectively exploited, and Renishaw are ideally situated to do so. Developing and selling L-PBF machines is a very competitive market; even a small edge in performance could mean a multi-million pound market advantage in a global sector worth £400m a year (Smartech 2014). The MTC will likewise benefit from the insights into the L-PBF process, alongside their own developments in the field. Previous collaboration ween the University of Nottingham and the MTC yielded the development of a novel laser ultrasound measurement approach for sub surface defect detection in L PBF. The multi sensor in process measurement system is a perfect corollary to that work, offering as it does a limited means to assess sub surface defects, but much greater information on form, texture and thermal distribution. Partnership with the MTC, a hub for UK AM activity, also ensures wide commercial visibility, supported by their commitment to project output dissemination activities, see Pathways to Impact document.
The personal impact of this project will be mostly seen by the PI and named researcher, creating a strong foundation for future research activities in the development of improved AM processing methods, of multi-sensor measurement methods and of data fusion techniques. For the PI this work represents an opportunity to build on their success in European and industrial funding, and for the named researcher a mechanism by which to translate a successful career in research in Canada into the UK academic system and gain familiarity with the EPSRC. AM is going to be an important technology for societal change, driving development of new healthcare technologies, reducing carbon emissions through light weighting and creating jobs in enterprising new markets as the traditional manufacturing model is disrupted. But change through AM will only come about if the metrology is in place to ensure quality and confidence in the AM production process. This proposal provides a foundation for that change.


10 25 50
Description While the award is not yet complete, and the majority of the impact and discovery is likely to occur in the remaining award period and impact period, there have been some notable contributions to date.

Our work has demonstrated the viability of a multi-sensor system for the measurement of complex surfaces produced by laser powder bed fusion (L-PBF), with the establishment of a prototype measurement instrument compatible with the challenging constraints of the in-situ measurement of L-PBF environment. To date we have demonstrated the suitability of both fringe-projection imaging and photometric-stereo techniques and continue to work towards their fusion. We expect to publish on the subject before the end of the award period and before the close of 2019. Most recently a number of novel developments have been made in the calibration of a multiple camera fringe projection measurement system. the work must be completed however before we can understand the impact that these developments might have for the wider community.
Exploitation Route We are already collaborating with the Manufacturing Technology Centre (MTC) on the development of an true in-situ measurement device. This will allow us, in partnership, to deliver a better understanding of this critically important additive manufacturing technology. In time these impacts will be seen in high value manufacturing, aerospace, defence and the energy sector.
Sectors Aerospace, Defence and Marine,Energy,Manufacturing, including Industrial Biotechology

Description Collaboration with the Manufacturing Technology Centre to Develop an in-situ prototype of the multi-sensor metrology system 
Organisation Manufacturing Technology Centre (MTC)
Country United Kingdom 
Sector Private 
PI Contribution We are bringing the knowledge and expertise developed in the production of our bench top multi-sensor instrument together with the expertise in laser powder bed fusion (L-PBF) at the MTC to produce an integrated prototype and demonstrate the suitability of the multi-sensor approach to in-situ L-PBF monitoring.
Collaborator Contribution The MTC are providing both their expertise and access to a range of equipment and facilities not available elsewhere in the UK HE infrastructure. This collaboration is a fantastic opportunity to accelerate the potential impact of the multi-sensor metrology system
Impact This new phase of work is still at an early stage. We expect to demonstrate impact and produce publication outputs in early 2020.
Start Year 2019