Application of Digital Manuals with a Retinal Imaging Display in Manufacturing: Behavioral, Physiological, and Psychological Effects on Workers

Nakanishi, Masayoshi; Sato, Tomomasa

doi:10.1002/hfm.20535

Cited by 10 publications

(5 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Nakanishi and Sato (2015) evaluated the psychological and physiological effect of digital manuals presented by a retinal imaging display on workers in the manufacturing industry. Rapaccini et al (2014) provided the results of a field study of user acceptance of AR to support the delivery of field services (e.g., maintenance activities) on installed products, and Olsson et al (2012) carried out a similar study to evaluate the user acceptance, potentials and risks associated to five different mobile AR scenarios.…”

Section: Conceptual Papersmentioning

confidence: 99%

Augmented reality technology in the manufacturing industry: A review of the last decade

2019

View full text Add to dashboard Cite

The aim of this article is to analyze and review the scientific literature relating to the application of Augmented Reality (AR) technology in industry. AR technology is becoming increasingly diffuse, due to the ease of application development and the widespread use of hardware devices (mainly smartphones and tablets) able to support its adoption. Today, a growing number of applications based on AR solutions are being developed for industrial purposes. Although these applications are often little more than experimental prototypes, AR technology is proving highly flexible and is showing great potential in numerous areas (e.g., maintenance, training/learning, assembly or product design) and in industrial sectors (e.g., the automotive, aircraft or manufacturing industries). It is expected that AR systems will become even more widespread in the near future.The purpose of this review is to classify the literature on AR published from 2006 to early 2017, to identify the main areas and sectors where AR is currently deployed, describe the technological solutions adopted, as well as the main benefits achievable with this kind of technology.ARTICLE HISTORY

show abstract

Section: Conceptual Papersmentioning

confidence: 99%

Augmented reality technology in the manufacturing industry: A review of the last decade

2019

View full text Add to dashboard Cite

show abstract

“…In the same study, workers using AI and other smart technology experience separation anxiety when away from devices (Meissner et al, 2020). Studies on the use of extended reality technologies (VR/AR) and smart wearables in the working context, indicate risks of information-processing overload, problem-solving difficulties and cognitive overload leading to operation errors (Chao et al, 2017;Marques et al, 2022;Nakanishi and Sato, 2015). Moreover, Brougham and Haar (2018) showed that workers show higher levels of job insecurity and lower levels of job satisfaction and organizational commitment (i.e., psychological engagement and dedication to their work) when they are aware of technological changes occurring in their workplace.…”

Section: Ejimmentioning

confidence: 90%

“…Several authors have concentrated on cognitive theories as framework to evaluate cognitive load in the interaction with technology (Chao et al, 2017). Nakanishi and Sato (2015) referred to information-processing theory (IPT) to focus on the employee's cognitive capacity. In their study, they evaluated the behavioral, physiological and psychological effects on workers in application of digital manuals with a retinal imaging display in manufacturing.…”

Section: Risks and Digital Innovationmentioning

confidence: 99%

“…It appears that whether a technological device is associated with simple or complex tasks can greatly influence the cognitive demand required of the worker which in turn can lead to risks for the individual. In this respect, when the digital innovation is not tailored on worker's previous experience with technology (Lowe et al, 2022), their perception of usefulness and ease of usability (Gangwar and Date, 2016;Panchetti et al, 2023) as well as the design and quality of user-machine interfaces (Nakanishi and Sato, 2015;Panchetti et al, 2023) can either simplify the worker's interaction with the technology or lead to an increase of risks.…”

Section: Risks and Digital Innovationmentioning

confidence: 99%

See 1 more Smart Citation

A human-centered perspective on individual risks for digital innovation management: an integrative conceptual review

Du Plooy,

Tommasi,

Furlan

et al. 2024

EJIM

View full text Add to dashboard Cite

PurposeFollowing the imperative for human-centric digital innovation brought by the paradigm of Industry 5.0, the article aims to integrate the dispersed and multi-disciplinary literature on individual risks for workers to define, explain and predict individual risks related to Industry 4.0 technologies.Design/methodology/approachThe paper follows the question, “What is the current knowledge and evidence base concerning risks related to Industry 4.0 technologies, and how can this inform digital innovation management in the manufacturing sector through the lens of the Industry 5.0 paradigm?” and uses the method of systematic literature review to identify and discuss potential risks for individuals associated with digital innovation. N = 51 contributions met the inclusion criteria.FindingsThe literature review indicates dominant trends and significant gaps in understanding risks from a human-centric perspective. The paper identifies individual risks, their interplay with different technologies and their antecedents at the social, organizational and individual levels. Despite this, the paper shows how the literature concentrates in studying risks on only a limited number of categories and/or concepts. Moreover, there is a lack of consensus in the theoretical and conceptual frameworks. The paper concludes by illustrating an initial understanding of digital innovation via a human-centered perspective on psychological risks.Practical implicationsFindings yield practical implications. In investing in the adoption, generation or recombination of new digital technologies in organizations, the paper recommends managers ensure to prevent risks at the individual level. Accordingly, the study’s findings can be used as a common starting point for extending the repertoire of managerial practices and interventions and realizing human-centric innovation.Originality/valueFollowing the paradigm of Industry 5.0, the paper offers a holistic view of risks that incorporates the central role of the worker as crucial to the success of digital innovation. This human-centric perspective serves to inform the managerial field about important factors in risk management that can result in more effective targeted interventions in risk mitigation approaches. Lastly, it can serve to reinterpret digital innovation management and propose future avenues of research on risk.

show abstract

“…Nakanishi and Sato 31 analyzed heart activity by Electrocardiogram (ECG) and brain blood flow in the right and left cerebral hemispheres by near infrared spectroscopy (NIRS) during an assembly task. The objective was to assess the stress digital manuals presented by a retinal imaging display (RID) on workers in the manufacturing industry.…”

Section: Affective Computing In Manufacturingmentioning

confidence: 99%

Applications of affective computing in human-robot interaction: State-of-art and challenges for manufacturing

Gervasi

Barravecchia

Mastrogiacomo

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part B:

View full text Add to dashboard Cite

The introduction of collaborative robots aims to make production more flexible, promoting a greater interaction between humans and robots also from physical point of view. However, working closely with a robot may lead to the creation of stressful situations for the operator, which can negatively affect task performance. In Human-Robot Interaction (HRI), robots are expected to be socially intelligent, that is, capable of understanding and reacting accordingly to human social and affective clues. This ability can be exploited implementing affective computing, which concerns the development of systems able to recognize, interpret, process, and simulate human affects. Social intelligence is essential for robots to establish a natural interaction with people in several contexts, including the manufacturing sector with the emergence of Industry 5.0. In order to take full advantage of the human-robot collaboration, the robotic system should be able to perceive the psycho-emotional and mental state of the operator through different sensing modalities (e.g. facial expressions, body language, voice, or physiological signals) and to adapt its behavior accordingly. The development of socially intelligent collaborative robots in the manufacturing sector can lead to a symbiotic human-robot collaboration, arising several research challenges that still need to be addressed. The goals of this paper are the following: (i) providing an overview of affective computing implementation in HRI; (ii) analyzing the state-of-art on this topic in different application contexts (e.g. healthcare, service applications, and manufacturing); (iii) highlighting research challenges for the manufacturing sector.

show abstract

Application of Digital Manuals with a Retinal Imaging Display in Manufacturing: Behavioral, Physiological, and Psychological Effects on Workers

Cited by 10 publications

References 26 publications

Augmented reality technology in the manufacturing industry: A review of the last decade

Augmented reality technology in the manufacturing industry: A review of the last decade

A human-centered perspective on individual risks for digital innovation management: an integrative conceptual review

Applications of affective computing in human-robot interaction: State-of-art and challenges for manufacturing

Contact Info

Product

Resources

About