Next Generation Device Design & Manufacture
Lead Research Organisation:
Imperial College London
Department Name: Design Engineering (Dyson School)
Abstract
Next generation device design & manufacture is an interdisciplinary subject that stems from a range of research areas, including additive manufacturing (AM), molecular science, Internet of Things (IoT), mechatronics and cognitive computing. The subject's diversity of influences hence requires the cross-pollination of knowledge and research ideas to develop and expand its applications. Advancements in building the next generation of intelligent and connected devices
will involve enhanced automation of design and production, increased precision in sensing and actuation, and improved monitoring and control of connected devices (e.g., IoT), all of which will be key contributors to new changes in a wide range of sectors such as construction, healthcare, manufacturing, entertainment and consumer products. This will ultimately transform the way we live and experience our environments.
Research into the next generation of intelligent devices seeks to overcome several barriers across design, production and control. For instance, additive manufacturing (e.g., 3D printing) currently exhibits clear challenges that limit the full usability of the technology, such as inconsistent quality, limited multifunctionality for end-use and reliance on a designer or a computer-aided design (CAD) technician to transfer data from computers to printers. These limitations contribute to the high cost of AM and its need for specialist labour, making 3D printers inaccessible to the general public.
A practical strategy towards next generation intelligent devices lies in increasing software and hardware innovation for both the transitional stages - from design to product delivery - and the operation stage of intelligent devices. Such innovations may include the following:
1. Increased availability of parametric and automated approaches to design with inputs from digital sensors (e.g., 3D scanning, computer vision). This lowers the barrier to using design tools for people with no background in computer modelling. It also enables design tools to recognise a user's bodily parameters and environmental information, allowing for bespoke designs ready for AM through their incorporation of computer-aided engineering.
2. Expanded multifunctionality of the AM, wherein 3D printed parts have the ability to change their material character, physical shape and conductivity to suit the specific tasks required. This also means that complex 3D printed parts can serve as seamless extensions to traditionally fabricated materials without the aid of mechanical fixing or wires.
3. Expanded connectivity of sensor networks and devices, as well as increased independence of such devices from centralised communication systems. This would allow devices to perform in areas of sparse infrastructure, operate autonomously via their own situational and spatial awareness, and communicate directly with other IoT devices.
The purpose of this PhD is first to identify these loose developments within the chain of processes from design to product delivery and operation, then to propose novel ideas that improve the accessibility of this technology and expand its positive applications.
Methodology
Considering the time frame for the study and the practice-based character of this research, its primary focus is not to construct designed products for end users but rather to test different, novel ideas that contribute to the advancement of the overall device design system and achieve promising technical outputs during the research process. This process of finding and testing ideas can be carried out in the following phases:
- Rapid prototyping: conduct tests in a short period of time with the purpose of designing an extension or plugin to an existing machine, infrastructure or software
- Proof of concept: testing prototype and analysing its outcomes to assess validity of idea
- Feedback
- Build phase
will involve enhanced automation of design and production, increased precision in sensing and actuation, and improved monitoring and control of connected devices (e.g., IoT), all of which will be key contributors to new changes in a wide range of sectors such as construction, healthcare, manufacturing, entertainment and consumer products. This will ultimately transform the way we live and experience our environments.
Research into the next generation of intelligent devices seeks to overcome several barriers across design, production and control. For instance, additive manufacturing (e.g., 3D printing) currently exhibits clear challenges that limit the full usability of the technology, such as inconsistent quality, limited multifunctionality for end-use and reliance on a designer or a computer-aided design (CAD) technician to transfer data from computers to printers. These limitations contribute to the high cost of AM and its need for specialist labour, making 3D printers inaccessible to the general public.
A practical strategy towards next generation intelligent devices lies in increasing software and hardware innovation for both the transitional stages - from design to product delivery - and the operation stage of intelligent devices. Such innovations may include the following:
1. Increased availability of parametric and automated approaches to design with inputs from digital sensors (e.g., 3D scanning, computer vision). This lowers the barrier to using design tools for people with no background in computer modelling. It also enables design tools to recognise a user's bodily parameters and environmental information, allowing for bespoke designs ready for AM through their incorporation of computer-aided engineering.
2. Expanded multifunctionality of the AM, wherein 3D printed parts have the ability to change their material character, physical shape and conductivity to suit the specific tasks required. This also means that complex 3D printed parts can serve as seamless extensions to traditionally fabricated materials without the aid of mechanical fixing or wires.
3. Expanded connectivity of sensor networks and devices, as well as increased independence of such devices from centralised communication systems. This would allow devices to perform in areas of sparse infrastructure, operate autonomously via their own situational and spatial awareness, and communicate directly with other IoT devices.
The purpose of this PhD is first to identify these loose developments within the chain of processes from design to product delivery and operation, then to propose novel ideas that improve the accessibility of this technology and expand its positive applications.
Methodology
Considering the time frame for the study and the practice-based character of this research, its primary focus is not to construct designed products for end users but rather to test different, novel ideas that contribute to the advancement of the overall device design system and achieve promising technical outputs during the research process. This process of finding and testing ideas can be carried out in the following phases:
- Rapid prototyping: conduct tests in a short period of time with the purpose of designing an extension or plugin to an existing machine, infrastructure or software
- Proof of concept: testing prototype and analysing its outcomes to assess validity of idea
- Feedback
- Build phase
Organisations
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| EP/R513052/1 | 01/10/2018 | 30/09/2023 | |||
| 2295713 | Studentship | EP/R513052/1 | 01/10/2019 | 30/09/2022 | Tae Hong |