Development of a Framework for Adaptable Augmented Reality Assistance Systems for Manual Assembly Tasks

In recent years, the use of Augmented Reality applications in an industrial context has become more established, especially for user guidance during manual assembly tasks. Despite the value of such applications for the industry, their drawbacks, such as high development costs or the fact that AR applications are often tailored to one specific use case, slow down their industry adoption. To address this problem, the authors developed a framework that enables the creation of complex AR assistance systems by using a condition-based approach. It helps to describe the assembly process for each step of the task by offering building blocks in the virtual environment. It can therefore superimpose visual guidance during manual assembly tasks such as work instructions. The frameworks’ goal is to improve the development of adaptable assistance systems but also decrease their overall development costs and therefore improve their acceptance for industry use cases. The authors developed the approach according to user requirements that they evaluated during prior research. To evaluate its efficacy, a software prototype was developed that guides workers during manual assembly tasks in line production for automobile components. The framework shows potential for quick setups and adaptability to changing work instructions through its modular structure.