New Interfaces for Data-Driven Design
Current limitation in industry
Product designers typically rely on a significant amount of creative “guess work” and/or many years of accumulated experience about what has worked well in the past to produce new designs that can be efficiently manufactured and are well tailored to the needs of their end users. Specifically, in traditional manufacturing systems, once the product blueprints leave the design studio the designers get relatively little feedback from either the fabricators (i.e. ways in which the design could be slightly adjusted to enable more efficient manufacturing) or the end users (i.e. how well the product is performing in the real-world). The key limitations of this fragmented product development cycle are that design innovation is slowed due to designers not understanding new usage demands, and manufacturing processes can be costly and inefficient. Ultimately, product designers are failing to exploit potentially valuable streams of product usage data that if unlocked could enhance efficiency and innovation by creating a new type of continuous product development that is more closely aligned to software development than traditional product design.
Current limitation in scope of research
Within industry and academia, research is largely focused on software tools that allow engineers to view usage data from physical products to monitor performance of high value assets (e.g. formula one cars) and/or aid on-site maintenance operations (e.g. fixing complex machinery with computer assistance). However, tools capable of unlocking this data to inform a more comprehensive and continuous product development cycle remain significantly underdeveloped. To unlock the value of product usage data and move beyond traditional asset management techniques, it is critical that we first develop sophisticated data-driven design tools that are specifically targeted at creative practitioners in order to allow them to intuitively visualise, understand, and make use of large amounts of data as part of a continuous product development cycle. Specifically, this challenge relates to new forms of data visualisation and design modelling techniques that remove the guess work in traditional design processes and allow designers to be more creative, agile, and efficient in their working methods.
The Value added to research
The primary value-add contribution for research will be the investigation of new interface techniques and visualisation methods that facilitate data-driven design. Specifically, our research will actively develop and test new ways in which creative designers can capture and visually interact with product usage data to enhance traditional design processes. In doing so, this research will more broadly contribute to existing fields of: data visualisation, human-computer interaction, and 3D design.
The Value added to industry
The primary value-add contribution for industry will be in developing methods that allow product designers to exploit new streams of product usage data to become more creative, agile and efficient in their working methods. This will be evidenced in two key ways. Firstly, we will develop software tools and visualisation methods that will allow creative designers to better understand how products are being used “in the wild” and to exploit these insights to accelerate product innovation. These tools will connect insights from other work packages in this project related to new forms of digital ethnography and AI-driven systems to inform design decisions. Secondly, we will develop software methods for automatically compiling digital designs into “hybrid” manufacturing instructions that combine advanced robotic assembly with human expertise and dexterity, along with methods of communicating these instructions to humans on the factory floor to support rapid reskilling and efficient manufacturing operations.
Visualising the future
•Streamline design and manufacturing processes to save time and money. The ability to generate insights from “in-the-wild” product use, combine this information with data related to manufacturing operations, and meaningfully provide this information to product designers will eliminate time-consuming market research, and allow companies to continuously fine-tune designs based on feedback to save time and money.
•Enhance product innovation and sustainability. The ability to understand products throughout their lifetime (and beyond) and use these AI driven insights to make informed design changes will enable companies to rapidly respond to the changing demands of their customers and possible products flaws, improve product quality and performance, and contribute to more sustainable products / eco-friendly products.
•Develop new digital manufacturing roles that fuse creative design with engineering skills. ‘Chatty’ Factories of the future will demand new and creative data-driven practitioners that operate across traditional domains of design and engineering to deliver product innovation. We will explore how enhanced digital interfaces can develop and support new manufacturing roles that transcend traditional disciplinary boundaries.