XR Enabled Operator Training

Licentiate thesis, 2025

The manufacturing industry is undergoing rapid transformation due to geopolitical
shifts, climate goals, and demographic changes, driving a growing demand for skilled
labour. In Sweden alone, it is estimated that 300,000 manufacturing workers will need
training in the coming three years. Traditional training approaches struggle to
effectively integrate practical and theoretical learning, highlighting the need for
innovative, scalable, and immersive training solutions to meet future workforce
demands.
Advancements in Extended Reality (XR) technology have paved the way for an
alternative to traditional training, offering the potential of safe, efficient and scalable
training with a high degree of realism and practical learning. Despite recent
technological advances and reduced hardware costs, few large-scale industrial
implementations of XR trainings have been observed, and 75% of all XR training projects
fail to move beyond the prototype stage.
This thesis aims to lower the barrier to implementing XR trainings in manufacturing
industry by addressing two main identified challenges. (1). Lacking design guidelines for
how XR trainings in manufacturing should be developed and used from a knowledge
perspective. (2) Resource intense development process of XR training content in
manufacturing. Two case studies and one systematic literature review was deployed as
part of the research to identify and theorize over the stated challenges.
The literature of XR training showed that the design of the XR training environment is
heavily dependent on the applied learning style, and the manufacturing use case. A
mapping of the applied learning styles and manufacturing use case are provided, giving
a first indication of how design guidelines of XR training in manufacturing could be
drawn from a knowledge perspective.
Addressing the second identified challenge, a method towards automated XR training
development utilizing Product Lifecycle Management (PLM) data structure is presented.
The highlighted method shows high potential for drastically reducing the time needed
for XR training development.
Finally, this thesis contributes by introducing an initial framework of design and
development guidelines based on the manufacturing use case and learning objective.
The presented framework that is expected to address both of the stated challenges,
lowering the barrier of implementation of XR training in manufacturing industry.