Training methods for visual inspection tasks

Clemons, Alexander John

doi:10.31274/etd-180810-3350

Cited by 4 publications

(6 citation statements)

References 35 publications

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“…Our results and other research suggest that a systematic search strategy can improve inspection performance [ 50 , 134 , 135 , 136 ]. Playing the eye tracking video of an experienced inspector with a desirable structured and systematic search strategy to novices or inspectors who inspect unseen parts for the first time could have a positive effect on their learning process and search strategy, leading to improved inspection performance [ 65 , 133 , 137 ].…”

Section: Discussionmentioning

confidence: 99%

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Assessment of the Effect of Cleanliness on the Visual Inspection of Aircraft Engine Blades: An Eye Tracking Study

Aust

Mitrović

Pons

2021

Sensors

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Background—The visual inspection of aircraft parts such as engine blades is crucial to ensure safe aircraft operation. There is a need to understand the reliability of such inspections and the factors that affect the results. In this study, the factor ‘cleanliness’ was analysed among other factors. Method—Fifty industry practitioners of three expertise levels inspected 24 images of parts with a variety of defects in clean and dirty conditions, resulting in a total of N = 1200 observations. The data were analysed statistically to evaluate the relationships between cleanliness and inspection performance. Eye tracking was applied to understand the search strategies of different levels of expertise for various part conditions. Results—The results show an inspection accuracy of 66.8% and 86.8% for clean and dirty blades, respectively. The statistical analysis showed that cleanliness and defect type influenced the inspection accuracy, while expertise was surprisingly not a significant factor. In contrast, inspection time was affected by expertise along with other factors, including cleanliness, defect type and visual acuity. Eye tracking revealed that inspectors (experts) apply a more structured and systematic search with less fixations and revisits compared to other groups. Conclusions—Cleaning prior to inspection leads to better results. Eye tracking revealed that inspectors used an underlying search strategy characterised by edge detection and differentiation between surface deposits and other types of damage, which contributed to better performance.

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Section: Discussionmentioning

confidence: 99%

“…Eye tracking helps illuminate the visual processes of perception [ 36 , 61 ], task-specific human behaviour [ 62 ] and cognitive processing during complex tasks [ 62 , 63 ]. It is also useful for training purposes [ 64 , 65 ] to assess proficiency [ 51 ] and compare levels of expertise [ 36 ].…”

Section: Literature Reviewmentioning

confidence: 99%

Assessment of the Effect of Cleanliness on the Visual Inspection of Aircraft Engine Blades: An Eye Tracking Study

Aust

Mitrović

Pons

2021

Sensors

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“…The insights could be used by maintenance providers to tailor their training endeavours and focus them around the critical and difficult detectable defects and defect locations. The mentioned training implications have all the potential to improve the inspection performance and staff competency, thereby assuring flight safety [52][53][54].…”

Section: Training Implicationsmentioning

confidence: 99%

Evaluation of Influence Factors on the Visual Inspection Performance of Aircraft Engine Blades

2021

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Background—There are various influence factors that affect visual inspection of aircraft engine blades including type of inspection, defect type, severity level, blade perspective and background colour. The effect of those factors on the inspection performance was assessed. Method—The inspection accuracy of fifty industry practitioners was measured for 137 blade images, leading to N = 6850 observations. The data were statistically analysed to identify the significant factors. Subsequent evaluation of the eye tracking data provided additional insights into the inspection process. Results—Inspection accuracies in borescope inspections were significantly lower compared to piece-part inspection at 63.8% and 82.6%, respectively. Airfoil dents (19.0%), cracks (11.0%), and blockage (8.0%) were the most difficult defects to detect, while nicks (100.0%), tears (95.5%), and tip curls (89.0%) had the highest detection rates. The classification accuracy was lowest for airfoil dents (5.3%), burns (38.4%), and tears (44.9%), while coating loss (98.1%), nicks (90.0%), and blockage (87.5%) were most accurately classified. Defects of severity level S1 (72.0%) were more difficult to detect than increased severity levels S2 (92.8%) and S3 (99.0%). Moreover, visual perspectives perpendicular to the airfoil led to better inspection rates (up to 87.5%) than edge perspectives (51.0% to 66.5%). Background colour was not a significant factor. The eye tracking results of novices showed an unstructured search path, characterised by numerous fixations, leading to longer inspection times. Experts in contrast applied a systematic search strategy with focus on the edges, and showed a better defect discrimination ability. This observation was consistent across all stimuli, thus independent of the influence factors. Conclusions—Eye tracking identified the challenges of the inspection process and errors made. A revised inspection framework was proposed based on insights gained, and support the idea of an underlying mental model.

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“…Random searches that lack pattern have been found to not only take longer than a more systematic search but also be more vulnerable to defects being missed by the inspector (Gramopadhye, et al, 1997;Tetteh and Jiang, 2006). Systematic searching, on the other hand, has been found to result in better performance as measured by a significantly greater detection of defects, a quicker search (Gramopadhye, et al, 1997;Clemons, 2013), and increased perceptual sensitivity for defects (Watts, 2011).…”

Section: Individual Factorsmentioning

confidence: 99%

How and why we need to capture tacit knowledge in manufacturing: Case studies of visual inspection

et al. 2019

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Human visual inspection skills remain superior for ensuring product quality and conformance to standards in the manufacturing industry. However, at present these skills cannot be formally shared with other workers or used to develop and implement new solutions or assistive technologies because they involve a high level of tacit knowledge which only exists in skilled operators' internal cognitions. Industry needs reliable methods for the capture and analysis of this tacit knowledge so that it can be shared and not lost but also so that it can be best utilised in the transfer of manual work to automated systems and introduction of new technologies and processes. This paper describes two UK manufacturing case studies that applied systematic task analysis methods to capture and scrutinise the tacit knowledge and skills being applied in the visual inspection of aerospace components. Results reveal that the method was effective in eliciting tacit knowledge, and showed that tacit skills are particularly needed when visual inspection standards lack specification or the task requires greater subjective interpretation. The implications of these findings for future research and for developments in the manufacturing industry are discussed.

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Training methods for visual inspection tasks

Cited by 4 publications

References 35 publications

Assessment of the Effect of Cleanliness on the Visual Inspection of Aircraft Engine Blades: An Eye Tracking Study

Assessment of the Effect of Cleanliness on the Visual Inspection of Aircraft Engine Blades: An Eye Tracking Study

Evaluation of Influence Factors on the Visual Inspection Performance of Aircraft Engine Blades

How and why we need to capture tacit knowledge in manufacturing: Case studies of visual inspection

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