# Effect of Augmented Reality Support on Quality Inspection of Welded Structures
## 1 Introduction
Moreover, conducting inspections by human operators is costly in terms of human, financial, and time resources [10]. Traditional quality control techniques have certain limitations in the context of modern highly variable small batch production. There is thus a need for faster, more accurate, reliable, and flexible quality solutions [11]. The level of automation in today's manufacturing companies is increasing [12]. Due to the demands for high quality, speed, and repeatability, automation is also starting to develop in processes that are highly dependent on manual work, such as quality control processes. However, efforts to automate quality inspection are running into problems in some types of manufacturing [13]. To improve quality and efficiency in inspection processes, ICT (information and communication technology), artificial intelligence models, and dynamic data need to be optimally integrated [14]. At the same time, there are many types of production or tasks for which full automation is not suitable or possible for technological or other reasons [15]. Emerging technologies, such as AR and intelligent systems, are providing manufacturing companies with new opportunities to manage quality [16]. The principal aim of this work is to investigate the effects of AR support on the weldment quality inspection process. To achieve this, the following research questions (RQs) were formulated:  
RQ1: Can AR be used by weldment quality inspectors to effectively support inspection in an industrial environment? RQ2: Can HHD (hand-held display) AR facilitate inspectors' interaction with the inspected product and the process of data interpretation and decision making? RQ3: How can the AR approach affect user performance during weldment quality inspection? The main objective of the research is to propose an AR approach for weldment inspection in an industrial environment based on the theoretical research of general inspection models and their experimental verification with end users. To meet these main objectives, the following sub-objectives have been defined:* Conceptual design of a general AR approach for quality inspection;
* Design and development of a pilot AR software to support quality inspection;
* Conducting field experimental research with end users in a real working environment with the developed AR approach to validate it;
* Evaluation of the impact of the AR approach on inspector performance in terms of objective metrics compared to traditional paper-based inspection practices;
* Monitoring the impact of the AR approach on the perceived mental workload of users compared to traditional paper-based inspection practices;
* Evaluation of the usability of the proposed AR approach;
* Comparative analysis of the impact of the proposed AR approach on two groups of end users according to their experience in weldment quality inspection. From the theoretical research, the following hypotheses were defined:  
**Hypothesis 1 (H1):**_Using the proposed AR approach will reduce the time to complete the weldment inspection compared to conventional approaches based on printed documentation._  
**Hypothesis 2 (H2):**_Using the proposed AR approach will reduce the inspection error rate compared to conventional paper-based approaches._  
**Hypothesis 3 (H3):**_Using the proposed AR approach will reduce the mental workload perceived when inspecting a weldment compared to using conventional approaches based on printed documentation._  
The first hypothesis, H1, defines the correlation between the performance of users supported by the conventional approach and the proposed AR approach in terms of task completion time. It investigates whether, with the innovative AR approach, users can complete the inspection task in less time. The second hypothesis, H2, also compares the conventional and the proposed AR approach, this time in terms of the quality of task execution, which is monitored in terms of the error rate observed during the inspection task.