Johnson Teegan

Dr. Johnson Teegan

Industrial Psychology and Human Factors, Centre for Structures, Assembly and Intelligent Automation, Cranfield University, Bedfordshire, MK43 0AL, UK

Research Focus & Metrics

Academic Career Length

13Years (2014-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 January 2022 in Applied Ergonomics
Verified
Journal Article
Open access
DADedy Ariansyah
Dedy Ariansyah
JEJohn Ahmet Erkoyuncu
John Ahmet Erkoyuncu
IEIveta Eimontaite
Iveta Eimontaite
JTJohnson Teegan
Johnson Teegan
AOAnne-Marie Oostveen
Anne-Marie Oostveen
SSSarah Sharples
Sarah Sharples
Head Mounted Display (HMD) based Augmented Reality (AR) is being increasingly used in manufacturing and maintenance. However, limited research has been done to understand user interaction with AR interfaces, which may lead to poor usability, risk of occupational hazards, and low acceptance of AR systems. This paper uses a theoretically-driven approach to interaction design to investigate the impact of different AR modalities in terms of information mode (i.e. video vs. 3D animation) and interaction modality (i.e. hand-gesture vs. voice command) on user performance, workload, eye gaze behaviours, and usability during a maintenance assembly task. The results show that different information modes have distinct impacts compared to paper-based maintenance, in particular, 3D animation led to a 14% improvement over the video instructions in task completion time. Moreover, insights from eye gaze behaviours such as number of fixations and transition between Areas of Interest (AOIs) revealed the differences in attention switching and task comprehension difficulty with the choice of AR modalities. While, subjective user perceptions highlight some ergonomic issues such as misguidance and overreliance, which must be considered and addressed from the joint cognitive systems' (JCSs) perspective and in line with the predictions derived from the Multiple Resources Model.

1 January 2019 in Applied Ergonomics
Verified
Journal Article
Open access
JTJohnson Teegan
Johnson Teegan
SFSarah Fletcher
Sarah Fletcher
WBW. Baker
W. Baker
RCR.L. Charles
R.L. Charles
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.

1 January 2020 in Computers & Industrial Engineering
Verified
Journal Article
Open access
SFSarah Fletcher
Sarah Fletcher
JTJohnson Teegan
Johnson Teegan
TATobias Adlon
Tobias Adlon
JLJon Larreina
Jon Larreina
PCPatricia Casla
Patricia Casla
MOMaría del Mar Otero
María del Mar Otero

1 October 2016 in Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture
Verified
Journal Article
Open access
PDF file
SFSarah Fletcher
Sarah Fletcher
JTJohnson Teegan
Johnson Teegan
JTJohn Thrower
John Thrower
It is going to be increasingly important for manufacturing system designers to incorporate human activity data and ergonomic analysis with other performance data in digital design modelling and system monitoring. However, traditional methods of capturing human activity data are not sufficiently accurate to meet the needs of digitised data analysis; qualitative data are subject to bias and imprecision, and optically derived data are hindered by occlusions caused by structures or other people in a working environment. Therefore, to meet contemporary needs for more accurate and objective data, inertial non-optical methods of measurement appear to offer a solution. This article describes a case study conducted within the aerospace manufacturing industry, where data on the human activities involved in aircraft wing system installations was first collected via traditional ethnographic methods and found to have limited accuracy and suitability for digital modelling, but similar human activity data subsequently collected using an automatic non-optical motion capture system in a more controlled environment showed better suitability. Results demonstrate the potential benefits of applying not only the inertial non-optical method in future digital modelling and performance monitoring but also the value of continuing to include qualitative analysis for richer interpretation of important explanatory factors.

1 January 2015 in Procedia CIRP
Verified
Journal Article
Open access
RCRebecca L. Charles
Rebecca L. Charles
JTJohnson Teegan
Johnson Teegan
SFSarah Fletcher
Sarah Fletcher
Visual inspection is a task regularly seen in manufacturing applications and is still primarily carried out by human operators. This study explored the use of job aids (anything used to assist the operator with the task, such as lists, check sheets or pictures) to assist with visual inspection within a manufacturing facility that inspects used parts. Job aids in the form of inspection manuals were used regularly during the inspection process, and how accurately they were followed was dependent on a number of factors such as size of part, experience of the operator, and accuracy of the inspection manuals. If the job aids were well structured, well written and accessible, then the inspectors were seen to follow them, however for certain jobs inspectors were seen to change the inspection order making inspection more efficient. The findings of the study suggest that prior experience can help in designing efficient, easy to use job aids and that a collaborative approach to design as well as using pictorial examples for comparison purposes would improve the inspection process.

10 July 2016 in Advances in Intelligent Systems and Computing
Verified
Book Chapter
Closed access
PDF file
JTJohnson Teegan
Johnson Teegan
GTGilbert Tang
Gilbert Tang
SFSarah Fletcher
Sarah Fletcher
PWPhil Webb
Phil Webb