Exploring Low-Cost Visual Assets for Conveying Assembly Instructions in AR

Lavric, Traian; Bricard, Emmanuel; Preda, Marius; Zaharia, Titus

doi:10.1109/inista52262.2021.9548570

Cited by 12 publications

(5 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Gender [28], age [28], lack of experience [29], lack of knowledge [30][31][32][33][34], fatigue [25], stress [2], body physique [35], poor health [36], poor memory [36], personal life problems [36], personality type [25], disappointment [25], lack of motivation [25], depression [25], fear of failure [37], poor error visual error perception [25], financial problems [25,38], haste in doing work [39], low intelligence coefficient [25,38], job dissatisfaction [39], lack of trust in performance [25], misunderstanding [39], unintentional unsafe acts [39], sleep deprivation/disorder [6,27,40], risk-taking [41], and understanding roles and responsibilities [25,38].…”

Section: Individual Factorsmentioning

confidence: 99%

“…Based on some previous studies [29], the experience factor is an important factor affecting human errors in assembly systems. Some studies, such as [30][31][32][33][34], demonstrated that the lack of experience and knowledge of the assembler were the most effective personal factors that led to assembly errors. In addition, some studies demonstrated many personal factors, such as misunderstanding [39], visual error perception [25,38,84], risk-taking [41], worker memory [35,36,39], fatigue [6,25,[85][86][87], stress [2], understanding roles and responsibilities [25,38], unintentional unsafe acts and haste in doing work [39], worker health [36], and intelligence coefficient [25,38], were the root causes of human errors in manual assembly processes.…”

Section: Ranking Factors Influencing Hes Based On the Fuzzy Delphi Me...mentioning

confidence: 99%

See 1 more Smart Citation

A New Model for Determining Factors Affecting Human Errors in Manual Assembly Processes Using Fuzzy Delphi and DEMATEL Methods

Alqahtani,

Noman,

Alabdulkarim

et al. 2023

Symmetry

View full text Add to dashboard Cite

Human errors (HEs) are common problems in manual assembly processes, impacting product quality and resulting in additional costs. Based on expert judgments, this study aims to identify the most significant factors affecting HEs in manual assembly processes and explore the cause-and-effect relationships among those factors. In order to achieve this objective, a proposed model is constructed using two types of Multi-Criteria Decision-Making (MCDM) techniques. Firstly, using two rounds of the fuzzy Delphi method (FDM), twenty-seven factors with an influence score of 0.7 or higher were found to have a major impact on HEs during manual assembly processes, with at least a 75% consensus among experts. After that, the twenty-seven factors affecting HEs were given to experts in a third round to analyze the cause-and-effect relationships among those factors using the fuzzy decision-making trial and evaluation laboratory (DEMATEL) method. In MCDM techniques, symmetry refers to an important property that can be used to find relationships between variables. It is based on the principle that the relative importance or preference between two variables should remain the same regardless of their positions or roles. Therefore, symmetry is a factor that MCDM approaches take into account to ensure that the relationships between variables are accurately represented, leading to more reliable decision-making outcomes. The reliability and normality of the surveying data were examined using the SPSS 22.0 software program. The study results revealed that training level, poor workplace layout, a lack of necessary tools, and experience were the major factors affecting HEs as root causes. Moreover, a failure to address the error-causing problem, unintentional unsafe acts, fatigue, and poor error visual perception were found to be effect (dependent) factors. The findings of this study can help organizations make better-informed decisions on how to reduce worker errors and interest in the factors that contribute to assembly errors and provide a good basis for reaching the quality of final assembled parts.

show abstract

Section: Individual Factorsmentioning

confidence: 99%

Section: Ranking Factors Influencing Hes Based On the Fuzzy Delphi Me...mentioning

confidence: 99%

A New Model for Determining Factors Affecting Human Errors in Manual Assembly Processes Using Fuzzy Delphi and DEMATEL Methods

Alqahtani,

Noman,

Alabdulkarim

et al. 2023

Symmetry

View full text Add to dashboard Cite

show abstract

“…The main objective of the field experiment presented in this section was to evaluate the effectiveness of the proposed low-cost-based AR training approach. A comprehensive description of the experiment set-up, participants, evaluation procedure, results and conclusions is presented in our previous work [16]. In this section, we present a summary of the most relevant findings reported in field experiment.…”

Section: Field Experiments 1 (Fe1)mentioning

confidence: 99%

“…A summary of the most significant challenges that an AR training system should address, to be considered for adoption in the considered use case are safety, user acceptance, viability, technical setup, existing digital resources, assembly environment and process. A detailed description of our case study and its findings are presented in [16].…”

Section: Introductionmentioning

confidence: 99%

“…We evaluated the proposed AR training method, particularly the conveyance of the AR step-by-step instructions by conducting two field experiments. The first [16], a preliminary one that involved 12 participants, aimed at assessing the effectiveness and usability of our proposed low-cost AR training method. The second [17], an extension of the first, involved 20 additional participants and aimed at assessing the worthiness of using CAD data for conveying manual assembly expertise via AR.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A low-cost AR training system for manual assembly operations

Lavric

Bricard

Preda³

et al. 2022

COMSIS J

Self Cite

View full text Add to dashboard Cite

This research work aims to provide an AR training system adapted to industry, by addressing key challenges identified during a long-term case study conducted in a boiler-manufacturing factory. The proposed system relies on low-cost visual assets (i.e. text, image, video and predefined auxiliary content) and requires solely a head-mounted display (HMD) device (i.e. Hololens 2) for both authoring and training. We evaluate our proposal in a real-world use case by conducting a field study and two field experiments, involving 5 assembly workstations and 30 participants divided into 2 groups: (i) low-cost group (G-LA) and (ii) computer-aided design (CAD)-based group (G-CAD). The most significant findings are as follows. The error rate of 2.2% reported by G-LA during the first assembly cycle (WEC) suggests that low-cost visual assets are sufficient for effectively delivering manual assembly expertise via AR to novice workers. Our comparative evaluation shows that CAD-based AR instructions lead to faster assembly (-7%, -18% and -24% over 3 assembly cycles) but persuade lower user attentiveness, eventually leading to higher error rates (+38% during the WEC). The overall decrease of the instructions reading time by 47% and by 35% in the 2nd and 3rd assembly cycles, respectively, suggest that participants become less dependent on the AR instructions rapidly. By considering these findings, we question the worthiness of authoring CAD-based AR instructions in similar industrial use cases.

show abstract

Augmented Reality Training in Manufacturing Sectors

Preda

Lavric

2023

The Digital Twin

View full text Add to dashboard Cite

Exploring Low-Cost Visual Assets for Conveying Assembly Instructions in AR

Cited by 12 publications

References 12 publications

A New Model for Determining Factors Affecting Human Errors in Manual Assembly Processes Using Fuzzy Delphi and DEMATEL Methods

A New Model for Determining Factors Affecting Human Errors in Manual Assembly Processes Using Fuzzy Delphi and DEMATEL Methods

A low-cost AR training system for manual assembly operations

Augmented Reality Training in Manufacturing Sectors

Contact Info

Product

Resources

About