Evaluating Impact of AI on Cognitive Load of Technicians During Diagnosis Tasks in Maintenance

Abstract

Even today, many maintenance activities are still done manually because maintenance is one of the most difficult areas to be automated in manufacturing. Many technicians spend their time on non-technical activities such as retrieving instructions from manuals. If AI (Artificial Intelligence) can alleviate some of these tasks, the time to diagnosis and repair can be shortened. However there are limited works about the effects of using AI during maintenance activities on a technician's cognitive load. Therefore, as an initiative, we conducted a pilot experiment with 10 participants to analyze the effects of the AI-based support system on diagnosis tasks in the manufacturing. In the experiment, participants were divided into two groups: the group used an AI-based support system and the other group used a Fault Tree (FT) based support system; two groups' mean task completion time and task load of participants using NASA Task Load were measured. According to the experiment results, the group which used the AI-based support system to diagnose the model completed task 53% lesser time than the group which used the FT-based support system. In addition, participants who used the AI-based support system reported relatively lower task loads compared to participants who used the FT-based support system. This experiment results imply that maintenance time and a variability can be reduced if an AI-based support system supports maintenance technicians

Cognitive Manufacturing in Industry 4.0 toward Cognitive Load Reduction: A Conceptual Framework

“…The authors of [30] developed an AI tool to test if, among other aspects, the cognitive load of the maintenance workers using an AI-based system would be lower. The authors of [31] studied a cognitive perspective and methodology for reverse engineering tools.…”

“…As the transfer of cognitive burden continues rising, society will undergo a cognitive revolution, characterized by technology's capability to augment the cognitive potential of humans [30]. Industry 4.0 is rich in new technologies; however, for the purpose of this research, it was important to separate the technologies related to human-computer interactions and a reduction in cognitive load, in order to keep track of the actual technologies that concerned this investigation.…”

“…Augmented reality (AR) reduces human errors and lightens the memory use of the operator, safely replicating the environment [47]. With AR, there is no compelling reason to change focus between the digital and physical worlds and no compelling reason to withdraw from a task to chase applicable data about what to do straight away or how to do it [30]. Augmented operators [40] have their working environment enriched by digital information, which reduces human error and improves decision-making by displaying feedback in real time [41].…”

Evaluating Technicians’ Workload and Performance in Diagnosis for Corrective Maintenance

“…The preliminary study was conducted with 10 participants to analyze the effect of the diagnosis support system [ 13 ]. This paper is a continuation of our previous work and the effort to design a human centered diagnosis support system for maintenance tasks.…”