Augmented reality -- Industrial applications, Virtual reality -- Industrial applications, Hierarchical decision model, Decision making
This study seeks to provide guidance in choosing the most suitable augmented reality enabled industrial wearable for use in the high-tech production and support environment. New development breakthroughs are coming to light every month in the world of VR (virtual reality), AR (augmented reality), and MR (mixed reality). The research data provided can be used to assist fab production and support personnel choose the AR-enabled wearable headsets. Many factors and agents are responsible for bringing cutting edge technology into use. Multiple criteria decision modeling was used to assist in the selection process for hardware for an augmented reality pilot and implementation across multiple sites. First, subject matters experts were identified. Second, interviews and product tests were conducted in participation with a functioning use case, Third, a hierarchical decision model was used and validated with a one site pilot program and an option selected with the highest level of agreement on specifications, Head Mounted Display (HMD) type, and overall inclusive cost.
The study produced for ETM coincided with a project that I am heading internally at Intel of the same result. The only limitation on the internal study was the budget to purchase testing hardware. Procedurally the HDM tool with its acknowledged flaws was an obvious hurdle which necessitated more pre-work and hand holding. In person sessions to walk through the HDM tool alleviated frustration and reluctance to complete the model.
In Copyright. URI: http://rightsstatements.org/vocab/InC/1.0/ This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
Richards, Roland, "Choosing the Most Suitable AR-enabled Wearable for Industrial Use" (2018). Engineering and Technology Management Student Projects. 2230.