Intelligent engineering coatings for in-manufacture and in-service monitoring of critical safety products (CoatIN)

Lead Research Organisation: University of Manchester
Department Name: Materials

Abstract

Coatings are key to the performance of most manufactured products and they contribute to sustainability by enhancing the efficiency and extending the life of the products that they protect, as well as by enabling the reduced use of scarce bulk materials. Coatings are a vital part of the nation's manufacturing industry, contributing to many sectors, including aerospace, energy, automotive, construction and healthcare. However, until now the UK coatings industry has been lagging behind compared to High Value Manufacturing sectors in terms of design, development, manufacture, and implementation into products, particularly in terms of the degree of digitalisation achieved.

This project will develop intelligent coatings with new functionalities that can self-monitor during manufacture and in-service. The multidisciplinary team will use a suite of modelling tools, sensing technologies and experimental deposition and characterisation facilities at The University of Manchester, the University of Sheffield, Cranfield University, Queen's University Belfast and Swansea University to embed new sensor functionalities within coatings, using a variety of deposition processes.

This EPSRC Exploratory Stream project will be a key step to address the challenges of digitalisation in the UK coatings manufacturing sector. The proposed research will assist UK PLC to develop manufacturing methods which are predictable, digital-enabled and more productive, providing a pathway to world-leading coating manufacturing processes. The research will support the coatings manufacturing industry to achieve best-in-class levels of High Value Manufacturing.

Planned Impact

Recent studies (such as the one by the industry-led Special Interest Group in Surface Engineering and Advanced Coatings) have demonstrated that the UK coatings market is worth about £11 billion annually. Moreover, coatings are vital to over £150bn of products made in the UK each year, and these products drive manufacturing turnovers greater than £380bn in UK companies. Nevertheless, the coatings sector in the UK lags behind other manufacturing process technology sectors, particularly with regard to the level of digitalisation achieved. Such digitalisation capability is needed for coatings to achieve their full potential to add value to products and to contribute optimally to sustainability objectives, given the critical role which coatings can play in conserving energy and materials resources.

This proposal will challenge the traditional mode of coating manufacture by extending the application of coatings beyond a simple protective layer to a functional sensing element, with a capability to monitor and regulate the coating growth process as well as, using the same sensing method, measure the functional performance of the component in-service. This project will establish a new way of thinking that will transform the way coatings are seen in the life-cycle of an engineering component. Establishing coatings as sensing elements that allow not only monitoring and gathering of the deposition process data but also continue to function in-service as an integrated, full life-cycle, cyber-physical devices is a step-change in transformational digital manufacturing and connectivity of safety critical engineering components. This proposal will address the critical need to eliminate waste in coating manufacturing, which accounts for significant productivity losses in UK businesses, and increases costs and lead times of engineering components.

This project will provide the vital first step in the journey towards digital transformation of the UK coatings industry, which will result in improved manufacturing quality, productivity, efficiency and sustainability. Through digitalisation, the coatings industry sector will be able to faster develop novel coatings with improved performance and functionalities directed by end-user needs. Since coatings are critical to the performance of most products, the impact of this project will expand to many sectors in UK industry, ranging from aerospace and automotive to healthcare and food & drink. This project addresses the outcomes of the recent "Made Smarter" review, which estimated that adoption of digitalistion throughout UK industry could add up to £455 billion for UK manufacturing over the next decade, by increasing manufacturing sector growth between 1.5% and 3% per annum. The successful implementation of digitalisation technologies in the UK coatings industry will contribute to making the UK a global leader in industrial digitalisation in the coatings sector.

Publications

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Viswanathan V (2021) Role of thermal spray in combating climate change in Emergent Materials

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Rogov AB (2020) Relaxation Kinetics of Plasma Electrolytic Oxidation Coated Al Electrode: Insight into the Role of Negative Current. in The journal of physical chemistry. C, Nanomaterials and interfaces

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Mahapatra SD (2021) Piezoelectric Materials for Energy Harvesting and Sensing Applications: Roadmap for Future Smart Materials. in Advanced science (Weinheim, Baden-Wurttemberg, Germany)

 
Description 1. Thermal spray monitoring systems developed. - LSBU
2. Digital Twins developed for plasma electrolytic processes. - The University of Manchester
Exploitation Route Ongoing work
Sectors Digital/Communication/Information Technologies (including Software),Energy,Manufacturing, including Industrial Biotechology,Retail

 
Description These are early days however, we do anticipate important transfer of systems developed to industry.
First Year Of Impact 2023
Sector Digital/Communication/Information Technologies (including Software),Manufacturing, including Industrial Biotechology
Impact Types Economic

 
Title Data supporting the publication 'Clay swelling: role of cations in stabilizing/destabilizing mechanisms' 
Description In the compressed dataset, there are two subdirectories, one in the name of 'Example' and another 'PostprocessData'. The Example directory contains input files, output data and postprocessed data for case Na12 starting at a d-space of onelayer value, where files starts with in.* are input files for lammps software, files ending with .dat or .lmptrj are output files from lammps, and files ending with .mat are matlab processed data. The 'postporcessedata' contains matlab processed results for all simulations in this study, contains simulation for NaMMT, KMMT, CaMMT and NaBD starting at onelayer, twolayer and threelayer d-space values. 
Type Of Material Database/Collection of data 
Year Produced 2022 
Provided To Others? Yes  
URL https://cord.cranfield.ac.uk/articles/dataset/Data_supporting_the_publication_Clay_swelling_role_of_...
 
Title Data supporting the publication 'Clay swelling: role of cations in stabilizing/destabilizing mechanisms' 
Description In the compressed dataset, there are two subdirectories, one in the name of 'Example' and another 'PostprocessData'. The Example directory contains input files, output data and postprocessed data for case Na12 starting at a d-space of onelayer value, where files starts with in.* are input files for lammps software, files ending with .dat or .lmptrj are output files from lammps, and files ending with .mat are matlab processed data. The 'postporcessedata' contains matlab processed results for all simulations in this study, contains simulation for NaMMT, KMMT, CaMMT and NaBD starting at onelayer, twolayer and threelayer d-space values. 
Type Of Material Database/Collection of data 
Year Produced 2022 
Provided To Others? Yes  
URL https://cord.cranfield.ac.uk/articles/dataset/Data_supporting_the_publication_Clay_swelling_role_of_...
 
Title Data supporting: 'Nanoindentation Response of 3D Printed PEGDA Hydrogels in a Hydrated Environment' 
Description Raw and processed data sets from nanoidentation response of 3D printed hydrogels. 1. Raw data of nanoindentation response. 2. Representative load-displacement curves for each type of hydrogel. 3. Representative data for creep for different types of hydrogels. 4. Representative data for NMR spectras of different types of hydrogels. 5. Representative data for glass transition of different types of hydrogels. 
Type Of Material Database/Collection of data 
Year Produced 2023 
Provided To Others? Yes  
URL https://cord.cranfield.ac.uk/articles/dataset/Nanoindentation_Response_of_3D_Printed_PEGDA_Hydrogels...
 
Title Data supporting: 'Nanoindentation Response of 3D Printed PEGDA Hydrogels in a Hydrated Environment' 
Description Raw and processed data sets from nanoidentation response of 3D printed hydrogels. 1. Raw data of nanoindentation response. 2. Representative load-displacement curves for each type of hydrogel. 3. Representative data for creep for different types of hydrogels. 4. Representative data for NMR spectras of different types of hydrogels. 5. Representative data for glass transition of different types of hydrogels. 
Type Of Material Database/Collection of data 
Year Produced 2023 
Provided To Others? Yes  
URL https://cord.cranfield.ac.uk/articles/dataset/Nanoindentation_Response_of_3D_Printed_PEGDA_Hydrogels...
 
Title Nanoindentation Response of 3D Printed PEGDA Hydrogels in a Hydrated Environment 
Description Raw and processed data sets from nanoidentation response of 3D printed hydrogels. 1. Raw data of nanoindentation response. 2. Representative load-displacement curves for each type of hydrogel. 3. Representative data for creep for different types of hydrogels. 4. Representative data for NMR spectras of different types of hydrogels. 5. Representative data for glass transition of different types of hydrogels. 
Type Of Material Database/Collection of data 
Year Produced 2023 
Provided To Others? Yes  
URL https://cord.cranfield.ac.uk/articles/dataset/Nanoindentation_Response_of_3D_Printed_PEGDA_Hydrogels...
 
Title Thermal response of multi-layer UV crosslinked PEGDA hydrogels 
Description All data sets are raw data from thermoresponse behaviour of hydrogels. 1. Swelling test for multi-150 um hydrogels with 1.8 mg/ml of photoabsorber.2. Swelling test for mono-5 mm hydrogels with 0 mg/ml of photoabsorber.3. Swelling test for multi-20 um hydrogels with 9 mg/ml of photoabsorber.4. Swelling test for mono-3 mm and mono-1.5 mm hydrogels with 0 mg/ml of photoabsorber.5. Cyclic test for multi-150 um hydrogels.6. Dried weight and solid residue weight of all hydrogels samples7. EWC, NWF, NVF-summary for all hydrogel samples8. DSC-TG-Thermogram-All sample types 
Type Of Material Database/Collection of data 
Year Produced 2022 
Provided To Others? Yes  
URL https://cord.cranfield.ac.uk/articles/dataset/Thermal_response_of_multi-layer_UV_crosslinked_PEGDA_h...
 
Title Thermal response of multi-layer UV crosslinked PEGDA hydrogels 
Description All data sets are raw data from thermoresponse behaviour of hydrogels. 1. Swelling test for multi-150 um hydrogels with 1.8 mg/ml of photoabsorber.2. Swelling test for mono-5 mm hydrogels with 0 mg/ml of photoabsorber.3. Swelling test for multi-20 um hydrogels with 9 mg/ml of photoabsorber.4. Swelling test for mono-3 mm and mono-1.5 mm hydrogels with 0 mg/ml of photoabsorber.5. Cyclic test for multi-150 um hydrogels.6. Dried weight and solid residue weight of all hydrogels samples7. EWC, NWF, NVF-summary for all hydrogel samples8. DSC-TG-Thermogram-All sample types 
Type Of Material Database/Collection of data 
Year Produced 2022 
Provided To Others? Yes  
URL https://cord.cranfield.ac.uk/articles/dataset/Thermal_response_of_multi-layer_UV_crosslinked_PEGDA_h...
 
Title Thermal response of multi-layer UV crosslinked PEGDA hydrogels 
Description All data sets are raw data from thermoresponse behaviour of hydrogels. 1. Swelling test for multi-150 um hydrogels with 1.8 mg/ml of photoabsorber.2. Swelling test for mono-5 mm hydrogels with 0 mg/ml of photoabsorber.3. Swelling test for multi-20 um hydrogels with 9 mg/ml of photoabsorber.4. Swelling test for mono-3 mm and mono-1.5 mm hydrogels with 0 mg/ml of photoabsorber.5. Cyclic test for multi-150 um hydrogels.6. Dried weight and solid residue weight of all hydrogels samples7. EWC, NWF, NVF-summary for all hydrogel samples8. DSC-TG-Thermogram-All sample types 
Type Of Material Database/Collection of data 
Year Produced 2022 
Provided To Others? Yes  
URL https://cord.cranfield.ac.uk/articles/dataset/Thermal_response_of_multi-layer_UV_crosslinked_PEGDA_h...