Complex data analytics in augmented manufacturing environments
Academic Institution: University of Edinburgh
Academic Supervisor: Dr Frank Mill
Industry Partner: ShapeSpace Ltd
PhD Student: TBC
Start Date: TBC
The proposed project seeks to investigate improved methods of supporting Augmented Reality (AR) tools so that they can more effectively support manufacturing applications.
Existing AR applications show potential for widespread use in manufacturing industry, particularly in process development, training, live instruction and in remote operation environments.
However a limiting factor in the use of AR is the inability to effectively track moving objects. This problem is a severe constraint on adoption - since it demands real time interaction - and has limited uptake by holding back the development of useful content and in turn impeding the development of useful pedagogical models for their use.
Experiments carried out by the applicants have shown considerable promise in their ability to develop novel and improved geometric reasoning algorithms that produce superior methods to track moving objects in real time and to keep moving objects updated with complex supporting data from, eg, PLM systems. These methods rely on domain specific knowledge in manufacturing.
ShapeSpace are currently working with a partner manufacturing analytics company (Theorem Solutions) and two large end-user companies (Babcock and Ford) to address some of these challenges but the proposed project would allow longer-term novel approaches to be investigated.
The specific objectives of the proposed project are:
To develop novel improved tracking tools for integrating complex data into AR environments with moving objects
To develop improved cost-effective processes for the production of AR environments in manufacturing
To develop further pedagogical uses of AR in manufacture.
The successful outcome of the project will lead to:
The establishment of a new area of business that will allow further development of ShapeSpace as a company.
The development of improved methodologies for training and simulation work in Scottish manufacturing and beyond.