Implementation of Augmented Reality in Manufacturing: A Case Study Exercise

Brunner, Katrin E.; Perey, Christine; Rauschnabel, Philipp A.; Sage, Mark

doi:10.1007/978-3-030-37869-1_8

Cited by 5 publications

(5 citation statements)

References 14 publications

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“…From a technical perspective, users in the current study did not report confusion or issues stemming from a lack of precision in how the virtual information aligned with real-world objects as described by others (Brunner et al, 2020;Deshpande & Kim, 2018). This may be a result of improved processing power in the HoloLens 2 and/or the file size of computer-aided design models involved in the current study.…”

Section: Resultsmentioning

confidence: 75%

“…AR is relatively inexpensive and easy to procure, facilitating adoption. To date, research has explored AR applications in most manufacturing processes (i.e., product design, manufacturing, commissioning, inspection and maintenance; Brunner et al, 2020; Fite‐Georgel, 2011). Inspection is an important step for quality assurance across manufacturing organisations; its documentation ensures verification of the completeness, correctness and integrity of a product or process (e.g., quality assessment, correct product assembly, performance and maintenance).…”

Section: Introductionmentioning

confidence: 99%

“…A key benefit of AR is that it can promptly identify “discrepancies between a process‐as‐designed and a process‐as‐performed, providing training and prompting to ensure processes are compliant with business goals” (van Lopik et al, 2020, p. 1). Therefore, AR is a useful technology for addressing labour constraints (a current issue in Australian manufacturing; Australian Chamber of Commerce and Industry & Westpac Banking Corporation, 2021) and delivering critical business objectives, such as productivity, profit and customer satisfaction (Brunner et al, 2020). Successful introduction of an AR system is closely related to user acceptance (Quandt & Freitag, 2021) and such objectives will not be achieved unless the workforce accepts AR systems and uses them to their full potential (Mlekus et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

“…Advancements in AR technology and their applications have been expected to revolutionise the manufacturing industry (Carmigniani & Furht, 2011) with some researchers referring to this activity as “industrial AR” (Fite‐Georgel, 2011; Quandt & Freitag, 2021) or “iAR” (Gattullo et al, 2020). However, broader operational deployment has been constrained (Quandt & Freitag, 2021; Väyrynen et al, 2018; Wang et al, 2021) and industry use of AR beyond the prototype stage is generally low (Zigart & Schlund, 2020) due to factors, such as equipment costs (e.g., AR hardware, software and information technology [IT] infrastructure; Brunner et al, 2020), skills shortages (e.g., carrying out the manual “authoring” of AR, requiring programming, modelling and animation competencies; Palmarini et al, 2018; Wang et al, 2021) and technological limitations of AR devices (e.g., processing speed, resolution of images and size/weight of device; Cheng et al, 2021), some of which can result in user discomfort and fatigue (Baroroh et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

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Visual inspection with augmented reality head‐mounted display: An Australian usability case study

Howard

Jang

O’Keeffe

et al. 2023

Hum Ftrs & Erg Mfg Svc

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Augmented reality (AR) is an Industry 4.0 technology. For more than a decade, advancements in AR technology and their applications have been expected to revolutionise the manufacturing industry and deliver quality and productivity gains. However, due to factors such as equipment costs, skills shortages and technological limitations of AR devices, operational deployment beyond prototypes has been constrained. Real‐world, usability studies can explore barriers to implementation and improve system design. This paper details a mixed method usability case study of an AR head‐mounted display (HMD) to perform a short, simple visual inspection task. Twenty‐two participants from South Australian manufacturing businesses inspected a pump and pipe skid while working at height. Overall, workload demands for the task were considered acceptable and just below the “low” workload threshold (NASA Task Load Index, mean = 29.3) and the system usability was rated “average” (system usability scale, mean = 68.5). The results suggest the task did not place too high a burden on users and was an appropriate initial exposure to AR HMDs, but further refinement to the interface would be desirable before implementation to minimise frustration and promote learning. Users were enthusiastic and open‐minded about the AR HMD although results indicate that even with recent advancements in AR HMD technology, interactions between the task, technology and environment continue to cause human and technical challenges—some of which are relatively straightforward to address but others are dependent on larger‐scale efforts.

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Section: Resultsmentioning

confidence: 75%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Visual inspection with augmented reality head‐mounted display: An Australian usability case study

Howard

Jang

O’Keeffe

et al. 2023

Hum Ftrs & Erg Mfg Svc

View full text Add to dashboard Cite

show abstract

“…The solution should, therefore, support multiple deployment models, such as cloud, on-premises, and hybrid [79]. Moreover, these systems must be capable of load balancing and high availability [80].…”

Section: (Ir) Integration and Real-time Data Featurementioning

confidence: 99%

A Data-Driven MCDM Approach-Based Spherical Fuzzy Sets for Evaluating Global Augmented Reality Providers in Education

Nguyen

2024

IEEE Access

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Amidst the surge in the popularity of augmented reality (AR), particularly in education due to the impact of the COVID-19 pandemic on remote learning, this research targets the challenge of efficient AR provider selection for educational use. The core objective revolves around introducing an encompassing decision support model, harnessing Spherical fuzzy sets (SFSs) to amplify decision-making. The study's initiation entails pinpointing eight pivotal criteria shaping AR provider selection via a stringent SF-Delphi procedure. The model duly factors each decision-maker's relative significance to ensure a fair and informed evaluation. The Spherical Weighted Arithmetic Mean (SWAM) operator amalgamates criteria weights, guaranteeing an all-encompassing and unbiased assessment. The ensuing step applies the Technique for Order of Preference by Similarity to the Ideal Solution (SF-TOPSIS) approach to systematically appraise and rank ten global AR providers. The systematic framework established in this study facilitates an impartial comparison among AR providers based on predetermined criteria. Through this research, a dual contribution is offered. Firstly, the proposed decision support model systematically and efficiently guides AR provider selection, effectively equipping decision-makers to navigate the intricacies of AR technology choices. Secondly, the research's impact extends to education, enriching the understanding of AR's applications. This knowledge fosters well-informed and innovative AR technology utilization, enhancing the overall learning experience. In conclusion, this study introduces a groundbreaking decision support model that leverages SFSs to guide the selection of educational AR providers. This structured framework empowers decision-makers and advances comprehension of AR dynamics, further driving strategic integration of AR technology in education.

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Extended ELECTRE I method for decision-making based on 2-tuple linguistic q-rung picture fuzzy sets

Ahmad,

Khan,

Shhazadi

2024

Soft Comput

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Implementation of Augmented Reality in Manufacturing: A Case Study Exercise

Cited by 5 publications

References 14 publications

Visual inspection with augmented reality head‐mounted display: An Australian usability case study

Visual inspection with augmented reality head‐mounted display: An Australian usability case study

A Data-Driven MCDM Approach-Based Spherical Fuzzy Sets for Evaluating Global Augmented Reality Providers in Education

Extended ELECTRE I method for decision-making based on 2-tuple linguistic q-rung picture fuzzy sets

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