Integration of digital twin to augmented reality in industrial enrichment plants : an anticipated user experience study

Abstract

Understanding user experience is necessary in developmental phases of every service, program and system. However, when adopting new technology, the early developmental phases methods and metrics used in user experience are not sufficient in anticipation of situational use and use cases of users. Therefore, focus and perspective to anticipated user experience research early in the development phase is needed. These problems are also true in ubiquitous computing field of Industry 4.0 where human computer interaction is in constant flux. New types of technologies and solutions are emerging and constantly seeking ways to capture their market share, bring added value or to revolutionize the industrial field without first understanding the anticipated requirements. This is true also for different industrial process control applications like digital twins and ways that augmented reality could be utilized in the on-site and monitoring operations.

This thesis determines what the anticipated user experiences are for the professionals working in the industry and how applications can be integrated to augmented reality in industrial contexts. To tackle this issues artifact and gamification as design method will be utilized. Anticipated user experience study approach is applied and combined with early developmental artifact in the interviews. Research data is collected both qualitatively and quantitatively, but the main research method and data analysis is implemented with qualitative data.

Contributions of this thesis is to determine if the use of early developmental artifact helps with the anticipations of user experiences and use cases for new technology adaptations to augmented reality in industrial contexts. This thesis proposes the term artifact specificity constraint and contributes to a model for converged relations of virtual reality continuum and digital twins. This thesis outlays a coding scheme with nine categories to be used as a reference for similar focused research.