Manufacturing in Hospital: BioMed 4.0
Lead Research Organisation:
University of Bath
Department Name: Chemical Engineering
Abstract
Although British healthcare/biomedical manufacturing generates £70 billion/year and 240,000 jobs; its most important yield is a healthy, functional, thriving society. Unexpected externalities such as supply chain disruptions, sustainability requirements and socioeconomic circumstances (e.g. Brexit, COVID-19) pose a threat to this sector and more importantly to the wellbeing of Britain's population. To cope with these threats, it is imperative to develop new and strengthen existing technologies capable of manufacturing precise high-value, patient-personalised products in decentralised settings.
Additive manufacturing technologies, such as 3D printing, have shown these characteristics as they enable prototyping and manufacturing customized products on-site in a rapid, and economic manner. Certainly, 3D printing has revolutionized manufacturing practices and generated tremendous economic benefits to economies worldwide; for instance, in the UK, 3D printing has a revenue of £2.4bn annually. Even so, this technology has major technical issues including, feedstock-performance dependency (printing needs to be calibrated depending of the plastic used), excessive plastic waste production (a major environmental concern), poor printing resolution (nanometer-size structures cannot be printed) and low flexibility in its operation mode (cannot produce long fibres, particles). These technical drawbacks significantly hinder the deployment of 3D printing in many healthcare/biomedical settings.
Inspired by the response of organisms to environmental conditions, this project will develop a novel responsive additive technology (named eHD-3D printing) capable of responding autonomously to feedstock and product requirements, while addressing each of the challenges present in modern 3D printing technologies. To achieve these transformative characteristics, we will integrate bio-inspired modalities (e.g. sensing, thinking and moving). We will employ novel analytical tools that enable sensing the type of material/plastic fed into the unit. This information coupled with the characteristics of the product will allow an AI-algorithm to determine the best operating conditions and operation mode. Beyond conventional 3D printing, the eHD-3D unit will be able to generate particles (0D) and fibres (1D) with a nano-metric resolution, enabling the manufacture of complex multi-scaled structures. Moreover, to demonstrate the transformative features of the eHD-3D unit, a range of geometrically and structurally diverse tissue scaffolds will be manufactured.
Additive manufacturing technologies, such as 3D printing, have shown these characteristics as they enable prototyping and manufacturing customized products on-site in a rapid, and economic manner. Certainly, 3D printing has revolutionized manufacturing practices and generated tremendous economic benefits to economies worldwide; for instance, in the UK, 3D printing has a revenue of £2.4bn annually. Even so, this technology has major technical issues including, feedstock-performance dependency (printing needs to be calibrated depending of the plastic used), excessive plastic waste production (a major environmental concern), poor printing resolution (nanometer-size structures cannot be printed) and low flexibility in its operation mode (cannot produce long fibres, particles). These technical drawbacks significantly hinder the deployment of 3D printing in many healthcare/biomedical settings.
Inspired by the response of organisms to environmental conditions, this project will develop a novel responsive additive technology (named eHD-3D printing) capable of responding autonomously to feedstock and product requirements, while addressing each of the challenges present in modern 3D printing technologies. To achieve these transformative characteristics, we will integrate bio-inspired modalities (e.g. sensing, thinking and moving). We will employ novel analytical tools that enable sensing the type of material/plastic fed into the unit. This information coupled with the characteristics of the product will allow an AI-algorithm to determine the best operating conditions and operation mode. Beyond conventional 3D printing, the eHD-3D unit will be able to generate particles (0D) and fibres (1D) with a nano-metric resolution, enabling the manufacture of complex multi-scaled structures. Moreover, to demonstrate the transformative features of the eHD-3D unit, a range of geometrically and structurally diverse tissue scaffolds will be manufactured.
Publications
Al G
(2024)
DiGeTac Unit for Multimodal Communication in Human-Robot Interaction
in IEEE Sensors Letters
Alkandari S
(2023)
Asymmetric membranes for gas separation: interfacial insights and manufacturing
in RSC Advances
Alkandari SH
(2024)
Recycling and 3D-Printing Biodegradable Membranes for Gas Separation-toward a Membrane Circular Economy.
in ACS applied engineering materials
Berri N
(2025)
Repurposing Laboratory Plastic into Functional Fibrous Scaffolds via Green Electrospinning for Cell Culture and Tissue Engineering Applications
in ACS Biomaterials Science & Engineering
Callaghan K
(2025)
Low-Cost, Multi-Sensor Non-Destructive Banana Ripeness Estimation Using Machine Learning
in IEEE Sensors Journal
Guo Q
(2024)
VibroTact: Soft Piezo Vibration Fingertip Sensor for Recognition of Texture Roughness via Robotic Sliding Exploratory Procedures
in IEEE Sensors Letters
Keirouz A
(2024)
Synergistic Interface Platforms: Designing Superhydrophilic Conductive Nanoparticle-Decorated Nanofibrous Membranes
in Advanced Materials Interfaces
Lightfoot J
(2023)
A molecular dynamics approach to modelling oxygen diffusion in PLA and PLA clay nanocomposites
in Materials Advances
Martinez-Hernandez U
(2023)
Soft Tactile Sensor With Multimodal Data Processing for Texture Recognition
in IEEE Sensors Letters
| Title | BioMed 4.0 logo and artwork |
| Description | Dr Jasmine Lightfoot PDRA in the BioMed project created the BioMed 4.0 logo and artwork for the website, seeking to make our projects more accessible to anyone who visits the website |
| Type Of Art | Artwork |
| Year Produced | 2023 |
| Impact | Seeking to make our projects more accessible to anyone who visits the website |
| URL | https://materialsforhealthlab.org/biomed4point0/members/ |
| Description | This cutting-edge technology integrates four different printing techniques into a desktop 3D printer using an embedded machine learning framework. Automatic transition among bioprinting techniques with diverse capabilities allows the incorporation of a wide range of biomaterials, printing resolutions (spanning from macro to nanoscale), and functionalities into a single 3D printing process. The applied machine learning framework not only improves the synergy among bioprinting approaches but also streamlines users' interaction with the printer by automatically optimising printing parameters based on the identified material and requested features in the design. |
| Exploitation Route | There is huge potential for this technology to be adopted by multiple sectors, including healthcare, pharmaceutical, energy/batteries. The machine learning software could also be integrated into existing 3D printers. |
| Sectors | Digital/Communication/Information Technologies (including Software) Energy Healthcare Manufacturing including Industrial Biotechology Pharmaceuticals and Medical Biotechnology |
| Description | Faculty Equipment Bid - Infrared system and probe |
| Amount | £73,500 (GBP) |
| Organisation | University of Bath |
| Sector | Academic/University |
| Country | United Kingdom |
| Start | 09/2021 |
| End | 03/2022 |
| Description | Royal Society International Exchange Scheme |
| Amount | £12,000 (GBP) |
| Funding ID | IEC\R2\212100 |
| Organisation | The Royal Society |
| Sector | Charity/Non Profit |
| Country | United Kingdom |
| Start | 12/2021 |
| End | 11/2023 |
| Description | University Equipment Bid Nanobioprinter |
| Amount | £510,000 (GBP) |
| Organisation | University of Bath |
| Sector | Academic/University |
| Country | United Kingdom |
| Start | 01/2023 |
| End | 03/2023 |
| Title | Dataset for "DiGeTac Unit for Multimodal Communication in Human-Robot Interaction" |
| Description | The dataset is divided into 2 main folders containing hand gesture and touch data. Gesture_Data folder contains data collected by performing four hand gestures; up, down, left, and right. There's also error data on mistakes made during these gestures. Touch_Data folder contains IMU data collected from the tactile sensor applying force on four different contact locations and from the idle case where no contact was made with the tactile sensor. The aim of this data collection is to present that the proposed sensing module can establish reliable multimodal communication channels between humans and industrial robots, thereby enhancing the interaction efficiency and user experience in automated environments. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2024 |
| Provided To Others? | Yes |
| URL | https://researchdata.bath.ac.uk/id/eprint/1388 |
| Title | Dataset for "Low-Cost, Multi-Sensor Non-Destructive Banana Ripeness Estimation Using Machine Learning" |
| Description | Processed datasets containing all numerical sensor data used for training and testing the ML algorithms discussed in the associated publication. Data from temperature, pressure, humidity, VOC and spectral sensors is included. The data is split into four datasets (as defined in Table V of the associated publication), each containing a different combination of sensor data and each subdivided into data ("x") and labels ("y") for both testing and training data. 30% of the cleaned data is randomly taken to form the testing data, while the remaining 70% forms the training data. Each data subset is balanced, as discussed in section 3.E.3 in the associated publication. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2025 |
| Provided To Others? | Yes |
| URL | https://researchdata.bath.ac.uk/id/eprint/1459 |
| Title | Dataset for "Soft Tactile Sensor with Multimodal Data Processing for Texture Recognition" |
| Description | The dataset is composed of 5 folders that contain tactile data from 5 different textures. Each folder has 15 files: 5 text files with data collected from piezovibration sensing modality, 5 text files with data collected from velostat (piezoresistive) sensing modality, 5 files with data from IMU (accelerometer, gyroscope) and pressure data. This dataset was collected to investigate the potential of the proposed multimodal soft tactile sensor to read data using multiple different sensing elements and their combination for texture recognition. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2023 |
| Provided To Others? | Yes |
| URL | https://researchdata.bath.ac.uk/id/eprint/1303 |
| Title | 3D PRINTING |
| Description | The invention relates to three-dimensional (3D) printing, and in particular to characterisation of a material to be printed (the characterisation optionally being performed in-line), optionally with action taken 5 based on that characterisation, and to printing mode-switching options. The disclosure may have particular relevance to multi-model 3D printers, and in particular to 3D printers which can switch between more traditional filament extrusion-based 3D printing and electrohydrodynamic jet printing and spraying 3D printing techniques. Current additive manufacturing technologies have an intrinsic antagonism between their degree of 10 structural resolution and their manufacturing speed or "printing efficiency". Resolution is primarily dictated by the size of the printing nozzle, which directly affects the size of the meniscus of the "ink" formed at the nozzle tip (it will be appreciated that the "ink" for 3D printing may be a polymeric filament, or indeed a solution for solution electrospinning, and that the term "ink" is used here in the general sense of a material to be printed). In an attempt to get around these limitations, the electrohydrodynamic (eHD) emission 15 phenomenon has been coupled with more traditional additive manufacturing to provide a multi-modal, multi- dimensional printing technology. However, this multi-modal printing technology has not been made commercially viable due to difficulties in control - instability in product quality and the need for careful post-printing analysis of all parts to check for both internal and external defects have held the technology back. There have been difficulties in integrating the differing requirements and limitations of various 20 printing modes into an automated device. |
| IP Reference | KSH142727P.GBA |
| Protection | Patent / Patent application |
| Year Protection Granted | 2023 |
| Licensed | No |
| Impact | preparing iCURE bid at present |
| Title | Controller for 3D printer with electrospinning |
| Description | Software controller that has been developed to have full control of a 3D printed and monitor printing parameters. This software will also allow us to continue with the development of a hybrid system capable of 3D printing by switching between electromelting teachnology and standard fuse deposition modelling technology. |
| Type Of Technology | Systems, Materials & Instrumental Engineering |
| Year Produced | 2022 |
| Impact | Full control of a low-cost 3D printer that can adapted for automation processes. Potential integration with ROS middleware for interoperability with other systems. |
| URL | https://github.com/inte-R-action/smartPrinting |
| Description | I am scientist ask me anything |
| Form Of Engagement Activity | Engagement focused website, blog or social media channel |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Public/other audiences |
| Results and Impact | The research team, Sandhya Moise, Sadeka Nujhat and Hannah Leese, took part in a a Reddit ask me anything event, where we discussed our research in ovarian cancer detection and shared information of our research. We had over 1000 upvotes and about half a million user views. |
| Year(s) Of Engagement Activity | 2022 |
| URL | https://www.reddit.com/r/IAmA/comments/zg01mt/were_sadeka_nujhat_hannah_leese_and_sandhya_moise/ |
| Description | I'm a scientist ask my anything |
| Form Of Engagement Activity | Engagement focused website, blog or social media channel |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Public/other audiences |
| Results and Impact | We took part in the University of Bath I'm a Scientist Ask Me thing "Hi, we're Hannah and Xiang from the University of Bath. We create new materials and devices to support sustainable healthcare. Our passions include microneedles (tiny painless needles), electrospinning, mechanical energy harvesters & 3D-printing. Ask Us Anything!" |
| Year(s) Of Engagement Activity | 2023 |
| URL | https://www.reddit.com/r/IAmA/comments/179wpdj/hi_were_hannah_and_xiang_from_the_university_of/?rdt=... |
| Description | Online talk for Public Engagement - Latin America |
| Form Of Engagement Activity | A broadcast e.g. TV/radio/film/podcast (other than news/press) |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Public/other audiences |
| Results and Impact | This activity was an online webmnar/presentation, intended to inform the general public in Latin America of our research. The space was provided by Fundacion UNAM - a philanthropic organization from the National University of Mexico. The activity instilled questions from people all over Latin America and the webinar has received >200 views. |
| Year(s) Of Engagement Activity | 2022 |
| URL | https://www.youtube.com/watch?app=desktop&v=Mm74he_dEcM |
| Description | Seminar talk at the Mathematics Applications Consortium for Science and Industry (University of Limerick) |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Postgraduate students |
| Results and Impact | ~50 academics (including professors, staff, PhD students and undergraduates) from he Mathematics Applications Consortium for Science and Industry at the University of Limerick attended the seminar, which sparked questions about the idea of having a system agnostic to feedstock. This talk instilled conversations for future collaborations and we are currently looking into applying for an EPSRC-SFI grant. |
| Year(s) Of Engagement Activity | 2022 |